By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a loosely coupled environment in which the actual execution environment might differ significantly from the one with the presupposed conditions during application design. Therefore, although an appropriate Web service might have been selected, by passing time, the Web service may not be efficient enough or may not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and use a similar service instead of the one which causes the above mentioned problems. Finding a similar service means specifying the proper services which fulfill the same requirements as those fulfilled by the problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on functional similarity. The user must select one of these services based on his/her preferences. One important metric in selecting a similar service is considering QoS properties and user preferences about QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which, in addition to functional similarity, QoS properties and user preferences are also considered in selecting a similar service.
QOS Aware Formalized Model for Semantic Web Service SelectionIJwest
Selecting the most relevant Web Service according to a client requirement is an onerous task, as innumerous number of functionally same Web Services(WS) are listed in UDDI registry. WS are functionally same but their Quality and performance varies as per service providers. A web Service Selection Process involves two major points: Recommending the pertinent Web Service and avoiding unjustifiable web service. The deficiency in keyword based searching is that it doesn’t handle the client request accurately as keyword may have ambiguous meaning on different scenarios. UDDI and search engines all are based on keyword search, which are lagging behind on pertinent Web service selection. So the search mechanism must be incorporated with the Semantic behavior of Web Services. In order to strengthen this approach, the proposed model is incorporated with Quality of Services (QoS) based Ranking of semantic web services.
This paper focuses on various concepts of Quality of Service associated with web services. Various QoS parameters like performance, availability, reliability and stability etc. are formalized in order to enhance the pertinence of web service selection. A QoS mediator agent based Web Service Selection Model is proposed where QoS Consultant acts as a Mediator Agent between clients and service providers. Model suggests user’s preferences on QoS parameter selection. The proposed model helps to select pertinent Web Service as per user’s requirement and reduce the human effort.. Further process of adding ontology with semantic web services is also illustrated here.
AGENTS AND OWL-S BASED SEMANTIC WEB SERVICE DISCOVERY WITH USER PREFERENCE SU...IJwest
Service-oriented computing (SOC) is an interdisciplinary paradigm that revolutionizes the very fabric of
distributed software development applications that adopt service-oriented architectures (SOA) can evolve
during their lifespan and adapt to changing or unpredictable environments more easily. SOA is built
around the concept of Web Services. Although the Web services constitute a revolution in Word Wide Web,
they are always regarded as non-autonomous entities and can be exploited only after their discovery. With
the help of software agents, Web services are becoming more efficient and more dynamic.
The topic of this paper is the development of an agent based approach for Web services discovery and
selection in witch, OWL-S is used to describe Web services, QoS and service customer request. We develop
an efficient semantic service matching which takes into account concepts properties to match concepts in
Web service and service customer request descriptions. Our approach is based on an architecture
composed of four layers: Web service and Request description layer, Functional match layer, QoS
computing layer and Reputation computing layer.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their
functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services. In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in
distributed environment. This service composition in the heterogeneous environment may suffer from
various kinds of service failures. These failures interrupt the execution of composite web services and
lead towards complete system failure. The dynamic recovery decisions of the failed services are
dependent on non-functional attributes of the services. In the recent years, various methodologies
have been presented to provide recovery decisions based on time related QoS (Quality of Service)
factors. These QoS attributes can be categorized further. Our paper categorized these attributes as
space and time. In this paper, we have proposed an affinity model to quantify the location affinity for
composition of web services. Furthermore, we have also suggested a replication mechanism and
algorithm for taking recovery decisions based on time and space based QoS parameters and usage
pattern of the services by the user.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in distributed environment. This service composition in the heterogeneous environment may suffer from various kinds of service failures. These failures interrupt the execution of composite web services and lead towards complete system failure. The dynamic recovery decisions of the failed services are dependent on non-functional attributes of the services. In the recent years, various methodologies have been presented to provide recovery decisions based on time related QoS (Quality of Service) factors. These QoS attributes can be categorized further. Our paper categorized these attributes as space and time. In this paper, we have proposed an affinity model to quantify the location affinity for composition of web services. Furthermore, we have also suggested a replication mechanism and algorithm for taking recovery decisions based on time and space based QoS parameters and usage pattern of the services by the user.
QOS Aware Formalized Model for Semantic Web Service SelectionIJwest
Selecting the most relevant Web Service according to a client requirement is an onerous task, as innumerous number of functionally same Web Services(WS) are listed in UDDI registry. WS are functionally same but their Quality and performance varies as per service providers. A web Service Selection Process involves two major points: Recommending the pertinent Web Service and avoiding unjustifiable web service. The deficiency in keyword based searching is that it doesn’t handle the client request accurately as keyword may have ambiguous meaning on different scenarios. UDDI and search engines all are based on keyword search, which are lagging behind on pertinent Web service selection. So the search mechanism must be incorporated with the Semantic behavior of Web Services. In order to strengthen this approach, the proposed model is incorporated with Quality of Services (QoS) based Ranking of semantic web services.
This paper focuses on various concepts of Quality of Service associated with web services. Various QoS parameters like performance, availability, reliability and stability etc. are formalized in order to enhance the pertinence of web service selection. A QoS mediator agent based Web Service Selection Model is proposed where QoS Consultant acts as a Mediator Agent between clients and service providers. Model suggests user’s preferences on QoS parameter selection. The proposed model helps to select pertinent Web Service as per user’s requirement and reduce the human effort.. Further process of adding ontology with semantic web services is also illustrated here.
AGENTS AND OWL-S BASED SEMANTIC WEB SERVICE DISCOVERY WITH USER PREFERENCE SU...IJwest
Service-oriented computing (SOC) is an interdisciplinary paradigm that revolutionizes the very fabric of
distributed software development applications that adopt service-oriented architectures (SOA) can evolve
during their lifespan and adapt to changing or unpredictable environments more easily. SOA is built
around the concept of Web Services. Although the Web services constitute a revolution in Word Wide Web,
they are always regarded as non-autonomous entities and can be exploited only after their discovery. With
the help of software agents, Web services are becoming more efficient and more dynamic.
The topic of this paper is the development of an agent based approach for Web services discovery and
selection in witch, OWL-S is used to describe Web services, QoS and service customer request. We develop
an efficient semantic service matching which takes into account concepts properties to match concepts in
Web service and service customer request descriptions. Our approach is based on an architecture
composed of four layers: Web service and Request description layer, Functional match layer, QoS
computing layer and Reputation computing layer.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their
functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services. In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in
distributed environment. This service composition in the heterogeneous environment may suffer from
various kinds of service failures. These failures interrupt the execution of composite web services and
lead towards complete system failure. The dynamic recovery decisions of the failed services are
dependent on non-functional attributes of the services. In the recent years, various methodologies
have been presented to provide recovery decisions based on time related QoS (Quality of Service)
factors. These QoS attributes can be categorized further. Our paper categorized these attributes as
space and time. In this paper, we have proposed an affinity model to quantify the location affinity for
composition of web services. Furthermore, we have also suggested a replication mechanism and
algorithm for taking recovery decisions based on time and space based QoS parameters and usage
pattern of the services by the user.
AN ADAPTIVE APPROACH FOR DYNAMIC RECOVERY DECISIONS IN WEB SERVICE COMPOSITIO...ijwscjournal
Service Oriented Architecture facilitates automatic execution and composition of web services in distributed environment. This service composition in the heterogeneous environment may suffer from various kinds of service failures. These failures interrupt the execution of composite web services and lead towards complete system failure. The dynamic recovery decisions of the failed services are dependent on non-functional attributes of the services. In the recent years, various methodologies have been presented to provide recovery decisions based on time related QoS (Quality of Service) factors. These QoS attributes can be categorized further. Our paper categorized these attributes as space and time. In this paper, we have proposed an affinity model to quantify the location affinity for composition of web services. Furthermore, we have also suggested a replication mechanism and algorithm for taking recovery decisions based on time and space based QoS parameters and usage pattern of the services by the user.
A review on framework and quality of service based web services discoveryMustafa Algaet
In consequence these services are nowadays accessible to the final clients. In the last few years, more
and more Web Services providing the same functionalities are available in the environment. In order to
select the best service adapted to client’s requests, we need some method capable to evaluate and
compare different services providing the same functionalities. In this context, Quality of service can be defined as the capability to respond to the requirements (constraints) of a client and to fulfill these
needs with the best criteria (preferences) established by the client. It is calculated based on the non-
functional properties of the service. This paper provides an overview of a research progress in Quality
of Service Based Web Services Discovery; it also highlights the issues that need to be investigated in
Quality of Service Based Web Services
Location-Aware and Personalized Collaborative Filtering for Web Service Recom...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Location-Aware and Personalized Collaborative Filtering for Web Service Recom...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Evaluation of QoS based Web- Service Selection Techniques for Service Composi...Waqas Tariq
This document discusses quality of service (QoS) based techniques for selecting web services for service composition. It begins by providing background on service-oriented computing and defining service composition. The document then reviews three approaches to web service selection: functional, non-functional, and user-based. It focuses on non-functional (QoS-based) service selection, describing the specifications of QoS-based service selection techniques, including QoS modeling, categorization, user preferences, evaluation criteria, and aggregating evaluation results. The document aims to evaluate various QoS-based service selection techniques and identify criteria for comparing them.
WEB SERVICE COMPOSITION IN DYNAMIC ENVIRONMENT: A COMPARATIVE STUDYcscpconf
This document provides a comparative study of 16 recent research papers on web service composition in dynamic environments. It evaluates the papers based on their approach to adapting to environmental changes, the composition phase they consider for detecting changes, whether they account for quality of service attributes, their main contributions, and whether they include experiments. The study finds that most approaches handle dynamism during the execution phase, treating earlier phases as static, and that more work is needed to detect and handle changes across all composition phases to build more reliable plans. Accounting for quality of service attributes and including experiments are also areas for improvement.
WEB SERVICES DISCOVERY AND RECOMMENDATION BASED ON INFORMATION EXTRACTION AND...ijwscjournal
This paper shows that the problem of web services representation is crucial and analyzes the various factors that influence on it. It presents the traditional representation of web services considering traditional textual descriptions based on the information contained in WSDL files. Unfortunately, textual web services descriptions are dirty and need significant cleaning to keep only useful information. To deal with this problem, we introduce rules based text tagging method, which allows filtering web service description to keep only significant information. A new representation based on such filtered data is then introduced. Many web services have empty descriptions. Also, we consider web services representations based on the
WSDL file structure (types, attributes, etc.). Alternatively, we introduce a new representation called symbolic reputation, which is computed from relationships between web services. The impact of the use of these representations on web service discovery and recommendation is studied and discussed in the
experimentation using real world web services.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
This document summarizes a research paper that proposes a user-centric approach for evaluating and optimizing constraint-based web service compositions using fuzzy logic and genetic algorithms. The approach uses fuzzy logic to model user preferences through quality criteria rankings. It then uses a genetic algorithm to optimize the composition process to maximize user satisfaction based on those fuzzy preferences. The results showed that the fuzzy-genetic algorithm system enables users to more easily and efficiently participate in and guide the web service composition process according to their needs and preferences.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed environments. In such systems, however each service responds the user request independently, it is essential to compose them for delivering a compound value-added service. Since, there may be a number of compositions to create the requested service, it is important to find one which its properties are close to user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem. Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of web service composition easier and more efficient.
User-Centric Optimization for Constraint Web Service Composition using a Fuzz...ijwscjournal
ABSTRACT
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed
environments. In such systems, however each service responds the user request independently, it is
essential to compose them for delivering a compound value-added service. Since, there may be a number of
compositions to create the requested service, it is important to find one which its properties are close to
user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or
response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on
quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem.
Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of
web service composition easier and more efficient.
International Journal of Computer Science, Engineering and Information Techno...ijcseit
Web Services are independent software systems which offer machine-to-machine interactions over the
Internet to achieve well-described operations. With the advent of Service-Oriented Architecture (SOA),
Web Services have gained tremendous popularity. As the number of Web Services is increased, finding the
best service according to users requirements becomes a challenge. The Semantic Web Service discovery is
the process of finding the most suitable service that satisfies the user request. A number of approaches to
Web Service discovery have been proposed. In this paper, we classify them and determine the advantages
and disadvantages of each group, to help researchers to implement a new or to select the most appropriate
existing approach for Semantic Web Service discovery. We, also, provide a taxonomy which categorizes
Web Service discovery systems from different points of view. There are three different views, namely,
architectural view, automation view and matchmaking view. We focus on the matchmaking view which is
further divided into semantic-based, syntax-based and context-aware. We explain each sub-group of it in
detail, and then subsequently compare the sub-groups in terms of their merits and drawbacks.
WEB SERVICE DISCOVERY METHODS AND TECHNIQUES: A REVIEWijcseit
Web Services are independent software systems which offer machine-to-machine interactions over the
Internet to achieve well-described operations. With the advent of Service-Oriented Architecture (SOA),
Web Services have gained tremendous popularity. As the number of Web Services is increased, finding the
best service according to users requirements becomes a challenge. The Semantic Web Service discovery is
the process of finding the most suitable service that satisfies the user request. A number of approaches to
Web Service discovery have been proposed. In this paper, we classify them and determine the advantages
and disadvantages of each group, to help researchers to implement a new or to select the most appropriate
existing approach for Semantic Web Service discovery. We, also, provide a taxonomy which categorizes
Web Service discovery systems from different points of view. There are three different views, namely,
architectural view, automation view and matchmaking view. We focus on the matchmaking view which is
further divided into semantic-based, syntax-based and context-aware. We explain each sub-group of it in
detail, and then subsequently compare the sub-groups in terms of their merits and drawbacks.
Web service discovery methods and techniques a reviewijcseit
Web Services are independent software systems which offer machine-to-machine interactions over the
Internet to achieve well-described operations. With the advent of Service-Oriented Architecture (SOA),
Web Services have gained tremendous popularity. As the number of Web Services is increased, finding the
best service according to users requirements becomes a challenge. The Semantic Web Service discovery is
the process of finding the most suitable service that satisfies the user request. A number of approaches to
Web Service discovery have been proposed. In this paper, we classify them and determine the advantages
and disadvantages of each group, to help researchers to implement a new or to select the most appropriate
existing approach for Semantic Web Service discovery. We, also, provide a taxonomy which categorizes
Web Service discovery systems from different points of view. There are three different views, namely,
architectural view, automation view and matchmaking view. We focus on the matchmaking view which is
further divided into semantic-based, syntax-based and context-aware. We explain each sub-group of it in
detail, and then subsequently compare the sub-groups in terms of their merits and drawbacks.
CLUSTERING-BASED SERVICE SELECTION FOR DYNAMIC SERVICE COMPOSITIONIJwest
The increase in the number of available web services led to the increase in the similarity of services functionality offered by different providers each with different QoS parameters. Therefore, in web service composition, the selection of the optimal service to satisfy the QoS values required by user is one of the significant requirements. Moreover, the dynamic nature of web services adds more challenges to obtain the accuracy of the selection process. Most of the existing service composition approaches deal with services changes during composition execution, causing a re-planning or re-selection that affecst the service composition performance. In this paper, we introduce the clustering-based service selection model that outperforms the existing ones. The proposed model has the ability to detect and recover the changes in service repository by monitoring the composition process from a global point of view. The approach is a two-levels-based web service clustering. The proposed model encompasses a clustering process, a planning process, a selection process and a recovery process.
A Privacy-Preserving QoS Prediction Framework for Web Service RecommendationIRJET Journal
This document discusses a privacy-preserving QoS prediction framework for web service recommendation. It begins with an introduction to web services and the importance of quality of service (QoS) metrics in selecting web services. It then discusses existing recommender system techniques like collaborative filtering for web service recommendation. The document proposes a new technique for predicting QoS values based on known QoS data while preserving privacy. It reviews related work on QoS-aware and location-aware web service recommendation techniques. Finally, it outlines the framework of a proposed location-aware and privacy-preserving QoS prediction approach for web service recommendation.
FUZZY-BASED ARCHITECTURE TO IMPLEMENT SERVICE SELECTION ADAPTATION STRATEGYijwscjournal
One of the main requirements in service based applications is runtime adaptation to changes that occur in
business, user, environment, and computational contexts. Changes in contexts lead to QOS degrade.
Continues adaptation mechanism and strategies are required to stay service based applications(SBA) in
safe state. In this paper a framework for runtime adaptation in service based application isintroduced. It
checks user requirements change continuously and dynamically adopts architecture model. Also it checks
providers QOS attributes continuously and if adaptation requirement is triggered, runs service selection
adaptation strategy to satisfy user preferences. Thusit is a context aware and automatically adaptable
framework for SBA applications. Wehave implemented a fuzzy based system for web service selection unit.
Due to ambiguity of context’s data and cross-cutting effects of quality of services, using fuzzy would result
an optimised decision. Finally we illustrated that using of it has a good performance for web service based
applications.
CONTEMPORARY SEMANTIC WEB SERVICE FRAMEWORKS: AN OVERVIEW AND COMPARISONSijwscjournal
The growing proliferation of distributed information systems, allows organizations to offer their business processes to a worldwide audience through Web services. Semantic Web services have emerged as a means to achieve the vision of automatic discovery, selection, composition, and invocation of Web services by encoding the specifications of these software components in an unambiguous and machine-interpretable form. Several frameworks have been devised as enabling technologies for Semantic Web services. In this paper, we survey the prominent Semantic Web service frameworks. In addition, a set of criteria is identified and the discussed frameworks are evaluated and compared with respect to these criteria. Knowing the strengths and weaknesses of the Semantic Web service frameworks can help researchers to utilize the most appropriate one according to their needs.
CONTEMPORARY SEMANTIC WEB SERVICE FRAMEWORKS: AN OVERVIEW AND COMPARISONSijwscjournal
The growing proliferation of distributed information systems, allows organizations to offer their business processes to a worldwide audience through Web services. Semantic Web services have emerged as a means to achieve the vision of automatic discovery, selection, composition, and invocation of Web services by encoding the specifications of these software components in an unambiguous and machine-interpretable
form. Several frameworks have been devised as enabling technologies for Semantic Web services. In this paper, we survey the prominent Semantic Web service frameworks. In addition, a set of criteria is identified and the discussed frameworks are evaluated and compared with respect to these criteria. Knowing the strengths and weaknesses of the Semantic Web service frameworks can help researchers to utilize the most appropriate one according to their needs.
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHYijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to select web services and to analyze composition of the web services. Web service choreography is going to dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by web services. These services are hosted in large numbers by different service providers on different service clusters. The mapping of service and task is difficult issue in run time environment. The interoperability between services is also a great problem. The selection of services is very big issue. In this paper we have proposed a bio-inspired selection algorithm based on dominant role and proposed a discovery infrastructure. We have also used the client behavior to improve the failure of the composition of the service.
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHY ijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are
used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot
be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to
select web services and to analyze composition of the web services. Web service choreography is going to
dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by
web services. These services are hosted in large numbers by different service providers on different service
clusters. The mapping of service and task is difficult issue in run time environment. The interoperability
between services is also a great problem. The selection of services is very big issue.
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHY ijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are
used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot
be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to
select web services and to analyze composition of the web services. Web service choreography is going to
dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by
web services. These services are hosted in large numbers by different service providers on different service
clusters. The mapping of service and task is difficult issue in run time environment. The interoperability
between services is also a great problem. The selection of services is very big issue.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
A review on framework and quality of service based web services discoveryMustafa Algaet
In consequence these services are nowadays accessible to the final clients. In the last few years, more
and more Web Services providing the same functionalities are available in the environment. In order to
select the best service adapted to client’s requests, we need some method capable to evaluate and
compare different services providing the same functionalities. In this context, Quality of service can be defined as the capability to respond to the requirements (constraints) of a client and to fulfill these
needs with the best criteria (preferences) established by the client. It is calculated based on the non-
functional properties of the service. This paper provides an overview of a research progress in Quality
of Service Based Web Services Discovery; it also highlights the issues that need to be investigated in
Quality of Service Based Web Services
Location-Aware and Personalized Collaborative Filtering for Web Service Recom...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Location-Aware and Personalized Collaborative Filtering for Web Service Recom...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Evaluation of QoS based Web- Service Selection Techniques for Service Composi...Waqas Tariq
This document discusses quality of service (QoS) based techniques for selecting web services for service composition. It begins by providing background on service-oriented computing and defining service composition. The document then reviews three approaches to web service selection: functional, non-functional, and user-based. It focuses on non-functional (QoS-based) service selection, describing the specifications of QoS-based service selection techniques, including QoS modeling, categorization, user preferences, evaluation criteria, and aggregating evaluation results. The document aims to evaluate various QoS-based service selection techniques and identify criteria for comparing them.
WEB SERVICE COMPOSITION IN DYNAMIC ENVIRONMENT: A COMPARATIVE STUDYcscpconf
This document provides a comparative study of 16 recent research papers on web service composition in dynamic environments. It evaluates the papers based on their approach to adapting to environmental changes, the composition phase they consider for detecting changes, whether they account for quality of service attributes, their main contributions, and whether they include experiments. The study finds that most approaches handle dynamism during the execution phase, treating earlier phases as static, and that more work is needed to detect and handle changes across all composition phases to build more reliable plans. Accounting for quality of service attributes and including experiments are also areas for improvement.
WEB SERVICES DISCOVERY AND RECOMMENDATION BASED ON INFORMATION EXTRACTION AND...ijwscjournal
This paper shows that the problem of web services representation is crucial and analyzes the various factors that influence on it. It presents the traditional representation of web services considering traditional textual descriptions based on the information contained in WSDL files. Unfortunately, textual web services descriptions are dirty and need significant cleaning to keep only useful information. To deal with this problem, we introduce rules based text tagging method, which allows filtering web service description to keep only significant information. A new representation based on such filtered data is then introduced. Many web services have empty descriptions. Also, we consider web services representations based on the
WSDL file structure (types, attributes, etc.). Alternatively, we introduce a new representation called symbolic reputation, which is computed from relationships between web services. The impact of the use of these representations on web service discovery and recommendation is studied and discussed in the
experimentation using real world web services.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
This document summarizes a research paper that proposes a user-centric approach for evaluating and optimizing constraint-based web service compositions using fuzzy logic and genetic algorithms. The approach uses fuzzy logic to model user preferences through quality criteria rankings. It then uses a genetic algorithm to optimize the composition process to maximize user satisfaction based on those fuzzy preferences. The results showed that the fuzzy-genetic algorithm system enables users to more easily and efficiently participate in and guide the web service composition process according to their needs and preferences.
USER-CENTRIC OPTIMIZATION FOR CONSTRAINT WEB SERVICE COMPOSITION USING A FUZZ...ijwscjournal
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed environments. In such systems, however each service responds the user request independently, it is essential to compose them for delivering a compound value-added service. Since, there may be a number of compositions to create the requested service, it is important to find one which its properties are close to user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem. Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of web service composition easier and more efficient.
User-Centric Optimization for Constraint Web Service Composition using a Fuzz...ijwscjournal
ABSTRACT
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed
environments. In such systems, however each service responds the user request independently, it is
essential to compose them for delivering a compound value-added service. Since, there may be a number of
compositions to create the requested service, it is important to find one which its properties are close to
user’s desires and meet some non-functional constraints and optimize criteria such as overall cost or
response time. In this paper, a user-centric approach is presented for evaluating the service compositions
which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on
quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem.
Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of
web service composition easier and more efficient.
International Journal of Computer Science, Engineering and Information Techno...ijcseit
Web Services are independent software systems which offer machine-to-machine interactions over the
Internet to achieve well-described operations. With the advent of Service-Oriented Architecture (SOA),
Web Services have gained tremendous popularity. As the number of Web Services is increased, finding the
best service according to users requirements becomes a challenge. The Semantic Web Service discovery is
the process of finding the most suitable service that satisfies the user request. A number of approaches to
Web Service discovery have been proposed. In this paper, we classify them and determine the advantages
and disadvantages of each group, to help researchers to implement a new or to select the most appropriate
existing approach for Semantic Web Service discovery. We, also, provide a taxonomy which categorizes
Web Service discovery systems from different points of view. There are three different views, namely,
architectural view, automation view and matchmaking view. We focus on the matchmaking view which is
further divided into semantic-based, syntax-based and context-aware. We explain each sub-group of it in
detail, and then subsequently compare the sub-groups in terms of their merits and drawbacks.
WEB SERVICE DISCOVERY METHODS AND TECHNIQUES: A REVIEWijcseit
Web Services are independent software systems which offer machine-to-machine interactions over the
Internet to achieve well-described operations. With the advent of Service-Oriented Architecture (SOA),
Web Services have gained tremendous popularity. As the number of Web Services is increased, finding the
best service according to users requirements becomes a challenge. The Semantic Web Service discovery is
the process of finding the most suitable service that satisfies the user request. A number of approaches to
Web Service discovery have been proposed. In this paper, we classify them and determine the advantages
and disadvantages of each group, to help researchers to implement a new or to select the most appropriate
existing approach for Semantic Web Service discovery. We, also, provide a taxonomy which categorizes
Web Service discovery systems from different points of view. There are three different views, namely,
architectural view, automation view and matchmaking view. We focus on the matchmaking view which is
further divided into semantic-based, syntax-based and context-aware. We explain each sub-group of it in
detail, and then subsequently compare the sub-groups in terms of their merits and drawbacks.
Web service discovery methods and techniques a reviewijcseit
Web Services are independent software systems which offer machine-to-machine interactions over the
Internet to achieve well-described operations. With the advent of Service-Oriented Architecture (SOA),
Web Services have gained tremendous popularity. As the number of Web Services is increased, finding the
best service according to users requirements becomes a challenge. The Semantic Web Service discovery is
the process of finding the most suitable service that satisfies the user request. A number of approaches to
Web Service discovery have been proposed. In this paper, we classify them and determine the advantages
and disadvantages of each group, to help researchers to implement a new or to select the most appropriate
existing approach for Semantic Web Service discovery. We, also, provide a taxonomy which categorizes
Web Service discovery systems from different points of view. There are three different views, namely,
architectural view, automation view and matchmaking view. We focus on the matchmaking view which is
further divided into semantic-based, syntax-based and context-aware. We explain each sub-group of it in
detail, and then subsequently compare the sub-groups in terms of their merits and drawbacks.
CLUSTERING-BASED SERVICE SELECTION FOR DYNAMIC SERVICE COMPOSITIONIJwest
The increase in the number of available web services led to the increase in the similarity of services functionality offered by different providers each with different QoS parameters. Therefore, in web service composition, the selection of the optimal service to satisfy the QoS values required by user is one of the significant requirements. Moreover, the dynamic nature of web services adds more challenges to obtain the accuracy of the selection process. Most of the existing service composition approaches deal with services changes during composition execution, causing a re-planning or re-selection that affecst the service composition performance. In this paper, we introduce the clustering-based service selection model that outperforms the existing ones. The proposed model has the ability to detect and recover the changes in service repository by monitoring the composition process from a global point of view. The approach is a two-levels-based web service clustering. The proposed model encompasses a clustering process, a planning process, a selection process and a recovery process.
A Privacy-Preserving QoS Prediction Framework for Web Service RecommendationIRJET Journal
This document discusses a privacy-preserving QoS prediction framework for web service recommendation. It begins with an introduction to web services and the importance of quality of service (QoS) metrics in selecting web services. It then discusses existing recommender system techniques like collaborative filtering for web service recommendation. The document proposes a new technique for predicting QoS values based on known QoS data while preserving privacy. It reviews related work on QoS-aware and location-aware web service recommendation techniques. Finally, it outlines the framework of a proposed location-aware and privacy-preserving QoS prediction approach for web service recommendation.
FUZZY-BASED ARCHITECTURE TO IMPLEMENT SERVICE SELECTION ADAPTATION STRATEGYijwscjournal
One of the main requirements in service based applications is runtime adaptation to changes that occur in
business, user, environment, and computational contexts. Changes in contexts lead to QOS degrade.
Continues adaptation mechanism and strategies are required to stay service based applications(SBA) in
safe state. In this paper a framework for runtime adaptation in service based application isintroduced. It
checks user requirements change continuously and dynamically adopts architecture model. Also it checks
providers QOS attributes continuously and if adaptation requirement is triggered, runs service selection
adaptation strategy to satisfy user preferences. Thusit is a context aware and automatically adaptable
framework for SBA applications. Wehave implemented a fuzzy based system for web service selection unit.
Due to ambiguity of context’s data and cross-cutting effects of quality of services, using fuzzy would result
an optimised decision. Finally we illustrated that using of it has a good performance for web service based
applications.
CONTEMPORARY SEMANTIC WEB SERVICE FRAMEWORKS: AN OVERVIEW AND COMPARISONSijwscjournal
The growing proliferation of distributed information systems, allows organizations to offer their business processes to a worldwide audience through Web services. Semantic Web services have emerged as a means to achieve the vision of automatic discovery, selection, composition, and invocation of Web services by encoding the specifications of these software components in an unambiguous and machine-interpretable form. Several frameworks have been devised as enabling technologies for Semantic Web services. In this paper, we survey the prominent Semantic Web service frameworks. In addition, a set of criteria is identified and the discussed frameworks are evaluated and compared with respect to these criteria. Knowing the strengths and weaknesses of the Semantic Web service frameworks can help researchers to utilize the most appropriate one according to their needs.
CONTEMPORARY SEMANTIC WEB SERVICE FRAMEWORKS: AN OVERVIEW AND COMPARISONSijwscjournal
The growing proliferation of distributed information systems, allows organizations to offer their business processes to a worldwide audience through Web services. Semantic Web services have emerged as a means to achieve the vision of automatic discovery, selection, composition, and invocation of Web services by encoding the specifications of these software components in an unambiguous and machine-interpretable
form. Several frameworks have been devised as enabling technologies for Semantic Web services. In this paper, we survey the prominent Semantic Web service frameworks. In addition, a set of criteria is identified and the discussed frameworks are evaluated and compared with respect to these criteria. Knowing the strengths and weaknesses of the Semantic Web service frameworks can help researchers to utilize the most appropriate one according to their needs.
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHYijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to select web services and to analyze composition of the web services. Web service choreography is going to dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by web services. These services are hosted in large numbers by different service providers on different service clusters. The mapping of service and task is difficult issue in run time environment. The interoperability between services is also a great problem. The selection of services is very big issue. In this paper we have proposed a bio-inspired selection algorithm based on dominant role and proposed a discovery infrastructure. We have also used the client behavior to improve the failure of the composition of the service.
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHY ijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are
used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot
be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to
select web services and to analyze composition of the web services. Web service choreography is going to
dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by
web services. These services are hosted in large numbers by different service providers on different service
clusters. The mapping of service and task is difficult issue in run time environment. The interoperability
between services is also a great problem. The selection of services is very big issue.
SERVICE SELECTION BASED ON DOMINANT ROLE OF THE CHOREOGRAPHY ijwscjournal
Web services are playing dominant role on Internet for e-business. The compositions of these services are
used to meet business objectives. The web service choreography describes the external observable behavior
of these compositions. Many compositions may available for same functionality. These compositions cannot
be distinguished on the basis of functional properties. This Quality of services (QoS) may help the user to
select web services and to analyze composition of the web services. Web service choreography is going to
dictate implementation of workflow. This workflow consists of several tasks. Each task is implemented by
web services. These services are hosted in large numbers by different service providers on different service
clusters. The mapping of service and task is difficult issue in run time environment. The interoperability
between services is also a great problem. The selection of services is very big issue.
Semelhante a AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTIONAL AND QOS ASPECTS (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY EVALUATION BASED ON THEIR FUNCTIONAL AND QOS ASPECTS
1. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
DOI : 10.5121/ijwsc.2011.2201 1
AN ARCHITECTURE FOR WEB SERVICE SIMILARITY
EVALUATION BASED ON THEIR FUNCTIONAL AND
QOS ASPECTS
Mahsa Jamal Vishkaei1
, Ahmad Baraani-Dastjerdi and Kamal Jamshidi2
1
Department of Computer Engineering, University of Sheikhbahaee, Isfahan, Iran
vishkaei@shbu.ac.ir
2
Department of Computer Engineering, University of Isfahan, Isfahan, Iran
{ahmadb, jamshidi}@eng.ui.ac.ir
ABSTRACT
By increasing popularity of SOC, using Web services in applications has increased too. SOC creates a
loosely coupled environment in which the actual execution environment might differ significantly from the
one with the presupposed conditions during application design. Therefore, although an appropriate Web
service might have been selected, by passing time, the Web service may not be efficient enough or may
not be applicable under specific conditions.
For service-oriented systems to be flexible and self-adaptive, it is necessary to automatically select and
use a similar service instead of the one which causes the above mentioned problems. Finding a similar
service means specifying the proper services which fulfill the same requirements as those fulfilled by the
problematic service.
In most of the previous works, a number of the best services (k) are selected and ordered based on
functional similarity. The user must select one of these services based on his/her preferences. One
important metric in selecting a similar service is considering QoS properties and user preferences about
QoS. Because of the importance of this issue, in the present paper, an architecture is proposed in which,
in addition to functional similarity, QoS properties and user preferences are also considered in selecting
a similar service.
KEYWORDS
Web service, Self-adaptive, Functional Similarity, QoS Similarity &User Preferences
1. INTRODUCTION
“SOC promotes the idea of assembling application components into a network of services that
can be loosely coupled [1] and Web services are currently the most promising SOC based
technology [2]. Web services act dynamically in such an environment and therefore, there could
be real-time changes in service status such as service unavailability and service quality decline.
Such problems may reduce quality or cause failure in processes and applications which use such
services. This makes the service consumer to go through the process of rediscovering a service
similar to the initial one which could also fulfill the previous requirements. Such a process is
much time-consuming. A flexible and self-adaptive Service-oriented system must be able to
automatically select the similar services and introduce them to the user so that the user does not
have to go through the difficulties of discovering similar services. The present work offers a
solution in providing similar services automatically whenever there is a problem in initial
service availability. Similar services are considered those which have a close functionality and
QoS to the initial one. In the process of finding similar services, after finding some services
which have the most functional similarity, the important metric for the user is to select the
service which has a satisfactory level of QoS. For Web services users, considering QoS issues is
2. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
2
critical since there is a direct relationship between the quality of an application consisted of
Web services and the quality of each consisting service. Thus, finding a similar service does not
only encompass considering functional features, but also QoS related properties. For this
purpose, there is a need to seek a way to know the user’s preferences about QoS. In most studies
such as [3,4,5,6], finding similar services is based on functional similarity in which a number of
the best services (k) are selected and introduced to the user. The user then has to select one of
them based on his/her preferences about QoS.
The represented method in this paper, considers QoS properties and user preferences about these
properties in addition to functional similarity. Considering QoS properties results in a different
rating of functionally similar services and, as a result, the best possible selection is done based
on functionality and quality.
Using QoS properties, results in a selection based on another important aspect of services which
optimizes service selection. In case of any changes in QoS properties of services, the system
adapts itself to environmental conditions and automatically selects the best similar service. To
gain service quality information, a four layered architecture is introduced in this article which
monitors services and stores this information for future use. When there is a request to find a
similar service, the first step is to examine services based on functional similarity. The
functionally similar services are then examined based on quality and user preferences. At last,
services are rated based on all the above similarity metrics. Accuracy is increased by using
statistical methods. In addition, each functional and QoS similarity has a weight which could be
changed based on user’s opinion and environmental conditions which makes the final decision
flexible.
User QoS preferences are derived using SLA (Service Level Agreements). SLA is a commonly
used mechanism to express Quality features [7]. In the present work, the attempt is to introduce
a new method in which: first, using SLA, user-defined parameters and their values are derived
and used automatically after discovering functionally similar services; second, the final decision
is flexible based on functionality and quality metrics. Thus, the present study attempts to find a
similar service based on two aspects.
The paper is organized as follows: Section 2 introduces related works. Section 3 explains the
QoS model that refers to QoS properties which used for quality evaluation of service. Next,
Section 4, presents our Architecture for similarity evaluation in detail. Finally we get conclusion
in section 5.
2. RELATED WORKS
Similarity search for Web services, also called Web service retrieval, occupies an important
place in SOC and several related works could be found regarding the issue. Generally, there are
three major groups of methods for finding similar services. In the first group, there exists a
group of previously chosen similar services; when a service fails to work at runtime, it is
replaced by another based on user context or QoS [8,9]. In the second group, similar services
are selected dynamically [3,4,5,6]. In the third group, the external behavior of a Web service
like execution paths or its conversations with other services is considered. In this group, because
of lack of information about external behavior of services in their description, service check is
done in composition process [10,11,12,13,14].
The second group is considered basic for this article. The reason is, the methods in this group
base their work on information existent in service description (WSDL) rather than concerning
external behavior or defining a new model for service representation or even choosing similar
services in advance. In works [3,4,5,6], calculating similarity is based on functional aspects only
3. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
3
and therefore, the user needs to do further refinement pertaining to important QoS features. In
[3], both syntactic and semantic aspects of a Web service that could be derived from WSDL are
considered. Semantic aspects are related to the purpose of a Web service which is in turn related
to the names assigned to the entire service and syntactic aspects are based on input/output
structures and data type adaptations. In [4], a search engine named Woogle is established for
Web services which uses textual similarity of methods and its parameters in order to examine
service similarity. The key element of Woogle is clustering algorithm for identifying the
relationships among the terms adopted in the all published Web services. It then compares the
concepts encompassing input/output parameters as a measure of similarity. In [5], finding
similar services is based on domain-independent and domain-specific ontology. In order to
specify domain-independent relations, after a series of pre-processes, WordNet thesaurus is
used. Deeper relations based on industry and application-specific terms are found using domain-
specific ontology and after that, related terms are found based on rule based inference. Matches
due to the two methods are combined to determine an overall similarity score. In [6], because of
inefficiency of catalogue style service discovery methods, a new method has been developed in
which similarity is sought via comparing the two WDSLs. In this article, in order to find the
similarity between two WSDL descriptions, a series of complementary methods are introduced.
These methods examine, on the one hand, data type structures, messages and operations and, on
the other hand, the meaning of identifiers and natural language descriptions. These methods
combine classical information retrieval and WordNet-based technique to increasing the
precision of the retrieval mechanism.
From the first group, work [15] could be mentioned in which, the assumption is that there is a
series of functionally similar services from which, one service is selected based on QoS. It uses
preferences networks to represent user preferences and to decide upon QoS using such
preferences. The work does not mention how to obtain user preferences but indicates that these
preferences can be defined at three levels of low, medium and high. Such a definition cannot be
accurate enough since different people may have different conceptions of these three levels.
3. THE QOS MODEL
The term “QoS” was used for the first time in the networking community by Crawley [16]. In
SOC, QoS encompasses a number of qualities or service properties like availability, security,
response time and throughput [17]. Generally speaking, QoS attributes are divided into two
groups: deterministic and non-deterministic [18]. Deterministic attributes are those that their
value is known before a service is invoked, like price or supported security protocols. Non-
deterministic attributes are those which their accurate value is unknown until the service is
invoked, like response time.
In this section, some QoS attributes are introduced which are used to evaluate the extent of
similarity among Web services from quality point of view. These features are defined under
specific conditions, for example they must be measurable, being measurable means that they
could be measured through monitoring mechanisms, to name the most important. Stated simply,
the purpose here is to use non-deterministic features. This results in a real evaluation of services
in operational environment and thus has an important role in finding similar services. To create
a general open model for evaluating QoS, there is also a need to consider features with a high
percentage of generality among QoS features of Web services which their desired value is
mentioned in SLA so that user preferences are discovered automatically. In this article, those
features used to measure QoS similarity are called “metrics”. These metrics include Availability
(A) and Response time (R). It is also possible to add other features later.
4. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
4
4. THE ARCHITECTURE
The architecture proposed in this section finds similar services to the initial service (Sq) based
on functional and QoS similarity. This architecture is composed of four layers (Figure 1).
QoS
Similarity Analyzer
Functional
Similarity
Monitoring
Figure 1: Architecture
The monitoring layer monitors Web services in the service repository (∑ = {Sp}) and stores
obtained data in a Database. In functional similarity and QoS similarity layers, functional and
QoS similarity of the Web services in the repository are evaluated compared to Sq. The analyzer
layer coordinates all the layers and makes the final decision. This layer communicates with the
external user and receives requests to find similar services and sends the final answer to the
user.
In this architecture, functional similarity is examined through WSDL. Services are examined for
QoS through monitoring QoS metrics of all services in repository and storing obtained data.
This is followed by evaluating QoS similarity of monitored services with user specified QoS
metrics related to Sq through the specification of user preferences about QoS metrics. An
examination of the stored information is done through monitoring operation and the degree of
similarity between QoS metrics of services with user preferences is identified. Not all services
need to be checked at this stage. Only those services whose functional similarity is greater than
a defined threshold are examined. Finally, services are rated based on the degree of similarity
obtained from two different aspects. Furthermore, this rating is done in a flexible manner and
thus, the best possible similar services are found and offered to the user. The component
diagram of the architecture is presented in Figure 2.
Figure 2: Component Diagram
5. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
5
Details about each layer are presented in the following sections.
4.1. The monitoring layer
The monitoring layer identifies and stores the QoS information of Web services. One of the
problems of the current Web services is their QoS information not being mentioned in their
description [17,19]. As a result, there is a need to find a way to monitor services and get such
information dynamically so that it could be used in future.
To get the required QoS information, the method for monitoring services in the repository ∑ =
{Sp}, must:
1. Have the ability to get the required information using Web service description (WSDL),
since, the code and implementation of the service is generally invisible to users;
2. Not need to do any change to the Web service;
3. Be independent form Web service provider and be applicable to all Web services.
In most works about QoS in Web services, the way to get and evaluate these features is not
mentioned; for example, in [20], the UDDI repository for associate QoS to specific Web service
is extend without any mentioning of how such values were obtained. In [21], analyzing and
estimating the performance of Web services is based on simulation i,e, invoking a Web service
under low load conditions and transforms these testing results into simulation model and uses
the model to estimate service excepted performance in heavy load. Because Web services act
dynamically, it does not seem that methods based on estimation be much accurate. [22] also
proposes a framework for QoS monitoring and analysis. This work considers communication
level monitoring via SOAP messages interception but has not detail about it and is mostly
concerned with analyzing the information. In [23] selecting services is based on QoS and it tries
to integrate QoS into Web service technology. But again in this work nothing is mentioned
about the way to get and evaluate QoS attributes.
After studding the existing methods and the above mentioned requirements, the method in [24]
was found suitable. This method is Non-intrusive, it measures QoS properties dynamically and
in a bootstrapping way and, in addition, completely service independent and does not have
access to Web service implementation. The measurement technique in this method is client-side
which is independent from the service itself and the service provider. In client-side technique it
is enough to have access to Web service description to get the QoS features of the service while
server-side technique need to access the Web service’ source code. Based on what mentioned
before, the latter is not a suitable technique here. [24] uses aspect-oriented programming (AOP)
which allows weaving performance measurement aspects. Thus, this approach could be used as
an independent package for monitoring services and recording the required information.
Availability (A) and response time (R) metrics of services could also be measured using this
method. It is noticeable that using this method should be so that extra loads are not imposed on
services. If all services are monitored all the time, a huge amount of information must be stored;
in addition, extra loads may be forced on services. To prevent this, it is necessary to reduce the
amount of data without distorting its integrity. This is achieved by sampling in monitoring and
data storage. Services are monitored randomly or in static time intervals. A scheduler
component, in which scheduling policies are defined, is in charge of sampling. This process is
continued by collecting the measured features for each service and storing the data in a Data
base and using this data when necessary. When QoS data are collected, it needs to be processed
to fulfill its particular purpose. The processing of data could be online or offline or a
combination of both [25]. In online processing, the data are processed immediately and in
offline processing the data are processed after being stored. Offline processing has the
advantage that the data could be studied from various viewpoints. In the present work, based on
the objectives of the study and the defined usage for the data, offline processing was preferred.
6. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
6
4.2. The functional similarity layer
The functional similarity layer checks the degree of functional similarity between services in
repository (∑ = {Sp}) and Sq. Checking functional similarity means finding those services that
do the similar task to service Sq. The main source to be used here is WSDL description. The
required information can be obtained from main parts of the WSDL, i.e portType, operation and
message. After receiving the WSDL of Sq, its similarity to the services in the repository (∑ =
{Sp}) is measured and each service is rated based on its functional similarity. Those services
that their degree of similarity is higher than the threshold are chosen and named as services
S1..Sk. In the next step, the vector of F = (fs1, fs2, …, fsk) is created for services S1.. Sk from their
functional similarity. Services S1..Sk and vector F are then sent to the analyzer layer.
As mentioned in section 2, in works [3,4,5,6] the similarity between two Web services is
measured from functional point of view. In this section, one of these methods is selected for
evaluating functional similarity between Web services as follows.
In [4], terms are considered as a package of words and similarity is measured based on TF/IDF
measure, the concepts are inferred from terms and the similarity among these concepts is
noticed. The weakness of this work is that it is possible to send only one method to the Web
service. In [5] the focus is only on words and the structure of the WSDL is not considered which
is the weakness of this method. [6], like [3], uses a recursive method in measuring similarity
between service description elements but its weakness is not considering the number of
operations and parameters of Web services. Work [3] does not have the above mentioned
problems and is accurate enough; therefore it is used in the present work to measure functional
similarity. The latter method considers both syntactic and semantic aspects of Web services that
could be derived from WSDL. Semantic aspects are related to the purpose of the Web service
which is itself related to the names assigned to the entire service like the names of operations,
parameters, port types, parts and inputs and outputs of its methods. Syntactic aspects are related
to the conformance between input and output structures and the consistency among data types.
4.3. The QoS similarity layer
The QoS similarity layer measures the degree of QoS similarity of services in repository ∑ =
{Sp} to Sq. Achieving this goal requires calculating the vector of user preferences (Puq = (auq,ruq))
about service QoS features for Sq in which auq indicates availability and ruq indicates response
time. The next step is to evaluate the quality status of services using the information calculated
and stored by the monitoring layer. It is noticeable that only those services which are
functionally similar to Sq are examined here. In section 4.3.1. how to calculate Puq and in section
4.3.2. how to measure QoS similarity are discussed.
4.3.1. User preferences about QoS
For Web service users, considering quality issues are very important because the quality of
applications consisting of Web services has a direct relationship with the quality of each service.
Therefore, there is a need to calculate Puq. One method is using SLA. By using SLA, one can
automatically become aware of user preferences when choosing Sq and use them in finding
similar services. SLA is actually a kind of contract in which different metrics for quality is
defined [17]; for example, the average response time should be less than 0.5 second or the
availability of a service must be more than 99.0 %.
In order to use SLA, it is necessary to use one of its defined standards. One standard is WSLA
(Web Service Level Agreement) [7] that is a formal language for expressing SLA in which the
agreement is made at service level.
The basic parts of a WSLA are as follows [7]:
7. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
7
1. Parties and their roles: provider, consumer and third parties;
2. SLA parameters: service object specifications like response time, throughput, etc. ;
3. Service Level Objectives (SLO): promises made about SLA parameters, obligations of
each party and actions taken if these promises and obligations are not observed.
It is obvious that in order to realize user preferences and to make the Puq vector about service
specifications, one must use the third part of WSLA i.e. SLO. In WSLA, it is possible to define
arbitrary parameters. It is also possible to have different definitions for the same parameter like
availability. In order for this article to be comprehensive, for each parameter, only one
definition is used and in all WSLAs for different services it is interpreted the same. In order to
understand better, notice a sample SLO in Figure 3.
<ServiceLevelObjective name="Conditional SLO For AvgThroughput">
<Obliged>ACMEProvider</Obliged>
</Validity>
<Expression>
<Implies>
<Expression>
<Predicate xsi:type="Less">
<SLAParameter> Response Time</SLAParameter>
<Value>10</Value>
</Predicate>
</Expression> part 1
<Expression>
<Predicate xsi:type="Greater">
<SLAParameter>AvgThroughput</SLAParameter>
<Value>1000</Value>
</Predicate>
</Expression>
</Implies>
</Expression>
<EvaluationEvent>NewValue</EvaluationEvent>
</ServiceLevelObjective>
Figure 3. A sample SLO
As is seen in Figure 3, part 1 shows the extent considered for QoS parameters that could be used
to find the most similar service in QoS to the initial one. For each attribute, it is specified that
the desired value must be greater or lower than the mentioned number. For example, for the
average throughput, a number greater than 1000 and for response time, a number less than 10 is
specified. This is how the vector of Puq for WSLA concerning Sq is created.
In WSLA, it is possible to define parameters at both method-level and service-level. In this
work, the assumption is that parameters are defined at service-level and in addition the WSLA
between service provider and service consumer for each Web service is stored in Database.
4.3.2. Evaluating QoS similarity
In this section, examining services from QoS point of view is discussed. In order to evaluate
QoS similarity of services with user preferences about Sq, it is necessary to communicate with
the analyzer layer. Through this communication, services S1..Sk and the WSLA of Sq (WSLAsq)
are received and the QoS similarity of services that are functionally similar to Sq are evaluated.
The vector of Puq is filled with the average availability and the average response time values
from WSLAsq. To evaluate the degree of QoS similarity, it is also necessary to use the data
stored for services S1..Sk by the monitoring layer. The average availability (asj) and the average
response time (rsj) for services S1..Sk are calculated using the stored data and put into matrix M
(Figure 4). In recovering the monitored data and calculating the average availability and the
average response time a number of recently stored data (w) are used. The purpose is considering
the most recent service behavior so that if the service has been acting well previously but not
recently, such a fact makes a difference in decision making and at the end the best possible
selection is done.
8. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
8
( )
k
j
r
w
r
a
w
a
where
r
a
r
a
M
n
w
n
x
sjx
sj
n
w
n
x
sjx
sj
sk
sk
s
s
...
1
,
1
,
1
1
1
1
=
∀
=
=
=
∑
∑ −
=
−
=
M
M
sjx
a : Xth
stored data for servicej
, n : total stored data , w : number of recently stored data
sj
a : average availability for servicej
, sj
r : average response time for servicej
Figure 4
Calculating the similarity of vector Puq and matrix M is actually a calculation in Euclidean space
in which Puq and each element of M are like points in space with two dimensions of A and R. It
is noticeable that data in Puq specifies the two desirable thresholds for availability and response
time from user’s point of view; this means that the user prefers service availability be greater
than auq and service response time be less than ruq; the more difference between these two, the
more satisfied the user. Therefore, Euclidean distance could be used to calculate similarity
between Puq and M.
In using Euclidean space, if there is great difference among data values or there is a difference
in measurement units of specifications, it is necessary to normalize the data; this assures
assigning the same weight to all specifications [26]. Here, because of the difference between the
measurement scales of availability and response time, Puq and M data must be normalized. The
normalization is done using the min-max relation [26], formula 2. For example, if the minimum
and the maximum values for A are minA and maxA respectively, and (a) is the old value of A,
based on formula 2, the new value of A, in the new range, (new_minA, new_maxA), is a'.
( ) ( )
2
min
_
min
_
max
_
min
max
min
` A
A
A
A
A
A
new
new
new
a
a +
−
−
−
=
For each element of Puq and M, formula 2 is used to create P'uq and M' (Figure 5). Here, the new
range is [0, 1].
=
sk
sk
s
s
r
a
r
a
M
`
`
`
`
`
1
1
M
M
( )
uq
uq
uq r
a
P `
,
` `
= ,
uq
k
j ∧
=
∀ ..
1
1
2
1
`
r
r
r
r
r
sj
sj
−
−
= ,
,
1
2
1
`
a
a
a
a
a
sj
sj
−
−
=
where
}
,
,
,
,
min{ 2
1
1 sk
s
uq r
r
r
r
r L
=
}
,
,
,
,
min{ 2
1
1 sk
s
uq a
a
a
a
a L
= ,
}
,
,
,
,
max{ 2
1
2 sk
s
uq r
r
r
r
r L
=
}
,
,
,
,
max{ 2
1
2 sk
s
uq a
a
a
a
a L
= ,
Figure 5
9. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
9
The degree of similarity can now be calculated using Euclidean distance. Calculating similarity
is done using QSim in Formula 3 and the answer is stored in Q vector (Figure 6).
( )
=
≥
−
=
=
≤
−
=
=
∀
+
=
=
0
)
`
`
(
)
`
`
(
0
)
`
`
(
)
`
`
(
)
3
(
..
1
,
]
`[
,
`
]
[ 2
2
r
else
r
r
if
r
r
r
a
else
a
a
if
a
a
a
where
k
j
r
a
j
M
P
QSim
j
Q
sj
uq
sj
uq
sj
uq
sj
uq
uq
Figure 6
4.3.3. Optimization
Calculating the similarity between P'uq and M' cannot be only based on average availability and
average response time since high data variation from these two may affect accuracy. Therefore,
in order to increase accuracy, it is necessary to consider the degree of variation from average as
well. Thus, in calculating similarity between P'uq and M', coefficient of variation (CV) is used.
Low CV shows consistency among data and high CV shows inconsistency among them [27].
Using data in (or By having a set of data objects) X = {x1,x2,…,xn}, CV is calculated through
formula 4 [27] :
( )
4
1
, 1
2
_
1
_
_
−
−
=
=
=
∑
∑ =
=
n
x
x
s
n
x
x
where
x
s
CV
n
i
i
n
i
i
Therefore, in order to increase accuracy in calculating QoS similarity, the CV value for each of
the availability metric (cva) and response time metric (cvr) is calculated for services S1.. Sk from
data stored in monitoring through the time span previously mentioned. These numbers are put
into QSim (P'uq,M'[j]) in (3) and (5) is created:
)
5
(
..
1
;
1
1
M`[j])
,
(P`
QSim
Q[j] 2
2
uq k
j
r
cv
a
cv r
a
=
∀
+
=
=
The Q vector shows the degree of similarity of each service to P'uq. To increase accuracy, the
assumption is that cva and cvr are less than one. It is possible that any element of Q be out of
[0,1] range, therefore it is necessary to put them back in the boundary using (2). The new vector
is named Q' and its elements are named as qsj; thus Q' is represented as Q'(qs1,qs2,…,qsk). Now
the final decision is made using Q' and the results of functional similarity evaluation.
4.4. The analyzer layer
The analyzer layer is responsible for coordinating all the layers and producing the final result.
This layer communicates with external user and receives requests for finding similar services
and sends the final answer to the user. When a request to find similar services to Sq is received,
the analyzer sends the WSDL of Sq to the functional similarity layer, which checks for
functional similarity. The result is a list of services S1..Sk together with their degree of similarity
to Sq which is sent back to the analyzer. Notice that this result has the form of F =
(fs1,fs2,…,fsk). The analyzer then sends the list of services (S1..Sk) to the QoS similarity layer,
which has to check for QoS similarity. It also sends the specific WSLA based on the requesting
party, the provider and Sq. the QoS similarity layer produces the result in the form of Q' in
which the extent of QoS similarity of services S1…Sk to Puq is presented. In the analyzer layer
10. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
10
the overall similarity of services S1…Sk and Sq is calculated by creating a matrix of Skx2whose
columns are filled with functional and QoS similarity values previously calculated (Figure 7).
=
k
k qs
qs
qs
fs
fs
fs
S
M
M
2
1
2
1
Figure 7
Finally, the overall similarity of services S1…Sk to Sq is calculated in the analyzer layer as
follows and services are ranked and ordered. The overall similarity means both functional and
QoS similarity at the same time.
4.4.1. Calculating the overall similarity
In order to calculate the overall similarity and ranking services, it is necessary to consider
functional and QoS similarities and their degree of importance. Therefore, in analyzer, a weight
is assigned to functional and QoS similarities. This weight is applied through W = [w1,w2]
where w1 stands for functional similarity and w2 stands for QoS similarity and w1+w2=1. w1 is
always greater than w2 because the purpose is to find a service which does the same work with
good quality. Of course these weights could be changed based on the type of work and user’s
opinion. Total similarity ranking of services S1…Sk to Sq is done using (6).
)
6
(
]
,
[ 2
1
2
1
2
1
w
w
qs
qs
qs
fs
fs
fs
A
k
k
score
×
=
M
M
Each element of Ascore
is calculated based on (7).
)
7
(
..
,
2
1 k
i
j
qs
w
fs
w
A j
j
score
j =
∀
×
+
×
=
Based on total similarity rank, score
j
A , services are ranked and ordered. The service with the
highest value of score
j
A is the most similar and its rank is ‘first’; similarly, a list of ranked
services based on score
j
A is created and sent to the user.
5. CONCLUSION
There could be real-time changes in service status such as service unavailability and service
quality decline in SOC environment. For service-oriented systems to be flexible and self-
adaptive, it is necessary to automatically select and use a similar service instead of the one which
causes problems and introduce them to the user so that the user does not have to go through the
difficulties of discovering similar services. The present work offers a solution in providing
similar services automatically whenever there is a problem in initial service availability.
One important metric in selecting a similar service is considering QoS properties and user
preferences about QoS. Because of the importance of this issue, in this work, an architecture is
proposed in which, additional to functional similarity, QoS properties and user preferences are
also considered in selecting a similar service.
11. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
11
In our architecture to check functional similarity, WSDL of services is used. Checking
functional similarity means finding those services that do the similar task. To check QoS
similarity, all services in the repository are monitored and the results are stored in a Database.
After automatically obtaining user preferences about QoS, QoS similarity of services to user
preferences is checked. In order to increase accuracy in QoS similarity check, statistical methods
are used. Total similarity is calculated based on functional and QoS similarity in a flexible way.
Considering QoS properties results in a different rating of functionally similar services and, as a
result, the best possible selection is done based on functionality and quality.
In future works, the objective is to extend QoS model with deterministic parameters like cost,
security, etc.
REFERENCES
[1] Michael P. Papazoglou,Paolo Traverso,Schahram Dustdar,Frank Leymann, (2007) "Service-Oriented
Computing: State of the Art and Research Challenges ," IEEE , vol. 40, no. 11, pp. 38-45.
[2] S. Weerawarana, Ed., (2005) Web Services Platform Architecture:SOAP, WSDL, WS-Policy, WS-
Addressing, WS-BPEL, WS-Reliable. Prentice Hall.
[3] P.Plebani,B.Pernici, (2009) "URBE: Web Service Retrieval Based on Similarity Evaluation," IEEE
Transactions on Knowledge and data engineering, vol. 21, no. 11, pp .1629-1642.
[4] X.Dong,A.Y. Halevy,J.Madhavan,E.Nemes,J.Zhang, (2004) "Simlarity Search for Web Services," in
Thirtieth international conference on Very large data bases, vol. 30, pp. 372-383.
[5] T.S.Mahmood,G.Shah,R.Akkiraju,A.A.Ivan,R.Goodwin, (2005) "Searching Service Repositories by
Combining Semantic and Ontological Matching," in IEEE International Conference on Web
Services (ICWS ’05), pp. 13-20.
[6] E.Stroulia,Y.Wang, (2005)"Structural and Semantic Matching for Assessing Web-Service
Similarity," International Journal of Cooperative Information Systems, vol. 14, no. 4, pp. 407-438.
[7] "Web Service Level Agreement (WSLA) Language Specification," IBM, 2003.
[8] Y.Taher, D.Benslimane, M.C. Fauvet, Z. Maamar, (2006) "Towards an Approach for Web services
Substitution," in in 10th International Database Engineering and Applications Symposium IEEE, pp.
166-173.
[9] Y.Yamato, H.Sunaga, (2007) "Context-Aware Service Composition and Component Change-over
using Semantic Web Techniques," in IEEE International Conference on Web Services, pp. 687-694.
[10] M. Mecella,B. Pernici,P. Craca, (2001) "Compatibility of E-Services in a Cooperative Multi-
Platform Environment," in Int’l Workshop Technologies for E-Services (TES ’01), pp. 44-57.
[11] g.spanoudakis,A. Zisman, A. Kozlenkov, (2005) "A Service Discovery Framework for Service
Centric Systems," in IEEE Int’l Conf. Services Computing (SCC ’05), pp. 251-259.
[12] L.Kuang, (2008) "A Formal Analysis of Behavioral Equivalence for Web Services," in IEEE
Congress on Services, pp. 265-268.
[13] P.Cyrille H´eam, O. Kouchnarenko , J.o.Voinot, (2007)"How to Handle QoS Aspects in Web
Services Substitutivity Verification," in 16th IEEE International Workshops on Enabling
Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp. 333-338.
[14] A. Martens, (2005) "Process Oriented Discovery of Business Partners," in Enterprise Information
12. International Journal on Web Service Computing (IJWSC), Vol.2, No.2, June 2011
12
Systems (ICEIS ’05), pp. 57-64.
[15] G.Ram, Santhanam,S.Basu,V.Honavar, (2009) "Web Service Substitution Based on Preferences
Over Non-functional Attributes," in International Conference on Services Computing (SCC 2009),
Bangalore, pp. 21-25.
[16] E. Crawley, R. Nair, B. Rajagopalan, and H. Sandick, "A Framework for QoS based Routing in the
Internet".
[17] A.Menasce, Danial, (2002) "QoS issues in Web services," in IEEE Internet computing, pp. 72-75.
[18] Y. Liu, A. H. Ngu, and L. Zeng, (2004) "QoS Computation and Policing in DynamicWeb Service,"
in Proceedings of the 13th International Conference onWorldWideWeb (WWW’04)ACM Press,
New York, NY, USA, pp. 66-73.
[19] A.Mani, A.Nagarajan, (2002) "Understanding quality of service for Web services," IBM http://www-
128.ibm.com/developerworks/library/ws-quality.html.
[20] S. RAN, (2003) "A Model for Web Services Discovery With QoS," ACM SIGecom Exchanges, vol.
4, no. 1, pp. 1-10, Nov.
[21] H.G. Song, K.Lee, (2005)"sPAC (Web Services Performance Analysis Center):," in Business
Process Management3rd International Conference, vol. 3649, France, BPM, pp. 109-119.
[22] R.B.Halima, K.Guennoun , K.Drira , M.Jmaiel, (2008) "Non-intrusive QoS Monitoring and Analysis
for Self-Healing Web Services," in 1st IEEE International Conference on the Applications of Digital
Information and Web Technologies (ICADIWT 2008), pp. 549-554.
[23] M. Tian, A. Gramm, H. Ritter, J. Schiller, (2004) "Efficient Selection and Monitoring of QoS-aware
Web services with the WS-QoS Framework," in WI '04 Proceedings of the 2004 IEEE/WIC/ACM
International Conference on Web Intelligence, pp. 152-158.
[24] F.Rosenberg, C. Platzer, S. Dustdar, (2006) "Bootstrapping Performance and Dependability
Attributes ofWeb Services," in ICWS '06 Proceedings of the IEEE International Conference on Web
Services, Chicago, pp. 205-212.
[25] W.John,S.Tafvelin, T.Olovsson, (2010) "Passive internet measurement: Overview and guidelines
based on experiences," Computer Communications, vol. 33, no. 5, p. 533–550.
[26] J.Han,M.Kamber, (2006) Data mining :Concept and Techniques, 2nd ed. San Francisco, CA: Diane
Cerra.
[27] J.K.Sharma, (2010) Fundamentals of Business Statistics. India: Dorling Kindersley.