-Cloud computing has come to the forefront as it overcomes some of the issues in computing such as storage space and processing power. It enables ubiquitous accessing and processing of information without the need of excessive computing facilities. In this work, we plan to brief some of the issues in aggregating the cloud services, discovering futuristic cloud service requests, develop a repository of the same and propose an agent based Quality of Service (QoS) provisioning system for cloud clients.

1. Tutorial Paper
Proc. of Int. Conf. on Advances in Communication, Network, and Computing 2013
Agent based Aggregation of Cloud Services- A
Research Agenda
Dr. Nandini Sidnal1 and Sreedevi R. Nagarmunoli1
1
KLEDRMSSCET, Belgaum, Karnataka, India
sidnal.nandini@gmail.com
Abstract--Cloud computing has come to the forefront as it
overcomes some of the issues in computing such as storage
space and processing power. It enables ubiquitous accessing
and processing of information without the need of excessive
computing facilities. In this work, we plan to brief some of the
issues in aggregating the cloud services, discovering futuristic
cloud service requests, develop a repository of the same and
propose an agent based Quality of Service (QoS) provisioning
system for cloud clients.
Index Terms—Aggregation, Futuristic cloud services,
Repository.
I. INTRODUCTION
deployment of services across multiple cloud providers,
Service Level Agreement (SLA) negotiation and management
between cloud providers, additional privacy, security and
trust management layers atop providers and support of
context-aware applications. Works in [1-5, 15-27, 11-14] depict
that not much attention is paid in monitoring and developing
repository of cloud services, customized aggregation of
services and distribution of services.
The field of software agent technology is a rapidly
developing area of research which encompasses a diverse
range of topics and interests [31-37]. Cognitive agents that
mimic human thought process and represent the logical
transition of research on human information processing to
practical application are deployed to develop an autonomous
aggregating system. Section 2 presents the literature survey
and section 3 describes the objectives of the research to be
carried out. Section 4 describes the proposed methodology
and section 5 provides the possible outcome and conclusion.
With the rapid development of processing and storage
technologies and the success of the Internet, computing
resources have become cheaper, more powerful and more
ubiquitously available than ever before. This technological
trend has enabled the realization of a new computing model
called cloud computing, in which computing resources such
II. LITERATURE SURVEY
as CPU, storage etc. are provided as general utilities that can
be leased and released by users through the Internet in an
The survey is based on the research works carried out in
on-demand fashion.
the universities, by the academicians and works in research
National Institute of Standards and Technology (NIST)
laboratories such as HP, IBM etc. [13] discusses the concept
defines cloud computing as a model for enabling convenient,
of “cloud” computing, it tries to address some of the issues
on-demand network access to a shared pool of configurable
related to research topics, and the “cloud” implementation
computing resources that can be rapidly provisioned and
available today. [14] investigates the challenges of
released with minimal management effort or service provider
developing a Campus Cloud based on aggregating resources
interaction [29,30]. It enables ubiquitous accessing and
in multiple universities. [10] presents a policy-centered QoS
processing of information without the need of excessive
meta-model which can be used by service providers and
computing facilities. Compared to other distributed
consumers alike to express capabilities, requirements,
computing paradigms such as Grid computing and High
constraints, and general management characteristics relevant
Performance Computing (HPC), cloud computing provides
for SLA establishment in service aggregations. HP Lab is
broader interoperability over the world-wide web networks
focusing on delivering the secure application and computing
[6, 9].
end-state of “Everything-as-a-Service”.
Some of the issues in cloud computing environment can
IBM researchers’ adopted cloud computing for faster
be classified as Platform Management, Cloud-enabled
turnaround times in provisioning of resources for specific
Applications, challenges in Cloud Management, Cloud
research projects [14]. Google and IBM are jointly working
Enablement, Cloud Interoperability, elastic scalability, trust,
on data centers in cloud. The Cloud Computing and
security, privacy, data handling, programming models,
Distributed Systems (CLOUDS) Laboratory is actively
resource control, systems development and systems
engaged in the design and development of next-generation
management and Aggregation of Cloud Services.
computing systems and applications that aggregate or lease
Aggregation of Cloud Services - The research challenges
services of distributed resources depending on their
in the aggregation of resources from diverse cloud providers
availability, capability, performance, cost, and users’ QoS
adding additional layers of service management, novel
requirements [9].
architectural models for aggregation of cloud providers,
Some of the ongoing research projects in cloud computing
brokering algorithms for high availability, performance,
area by different universities are discussed in the following
proximity, legal domains, price, or energy efficiency, sharing
paragraphs. The Researchers at Boston University are
of resources between cloud providers, networking in the
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DOI: 03.LSCS.2013.1. 560

2. Tutorial Paper
Proc. of Int. Conf. on Advances in Communication, Network, and Computing 2013
exploring the merits of “Collocation Games” (CGs) as a novel,
earlier work done on Web and Grid computing.
economically-sound framework upon which emerging cloud
architectures could be implemented [38]. Research is going
III. OBJECTIVES
on at Duke University to explore and test Trustworthy Virtual
The objectives of the proposed research work that will be
Cloud Computing [38]. Florida International University (FIU)
carried out are discussed in this section. The following issues
researchers are leveraging cloud computing to analyze aerial
in cloud computing are studied and some of the issues in
images and objects to help support disaster mitigation and
aggregating the cloud services would be resolved. Cloud
environmental protection [38]. The researchers at Indiana
aggregator is a platform or service that combines multiple
University are working on Large-Scale Distributed Scientific
clouds with similar characteristics (geographic area, cost,
Experiments on Shared Substrate, exploring the use of cloud
technology, size, etc.) into a single point of access, format,
techniques to overcome current medical computing obstacles
and structure. Value is derived from cost savings and greater
[38]. The team at MIT is working in collaboration with Yale
efficiency found from the ability to easily leverage multiple
Universit and the University of Wisconsin at Madison on a
services providers.
comparative study of approaches to cluster-based, large-scale
As a cost-effective and time-efficient way to develop new
data analysis and cloud for education [38].
applications and services, service aggregation in cloud
The aim of the project work at University of St. Andrew is
computing empowers all service providers and consumers
to investigate how underused computing resources within
and creates tremendous opportunities in various industry
an enterprise may be harvested and harnessed to improve
sectors. However, it also poses various challenges in securing
return on IT investment [15]. [16] aims at specifying,
the information on cloud.
measuring and understanding high level cloud properties.
Some of the issues that need to be resolved in aggregating
The aim of the project [17] is to develop and evaluate
[7-8, 10] the cloud services are availability of services that
techniques to allow desired high-level properties to be
may be hired in real time without conflicts, novel architectural
specified, mapped into appropriate low-level actions, and the
models for aggregation of cloud providers, brokering
results to be measured and reported in terms of the highalgorithms for high availability, performance, proximity, legal
level properties. The goal of the research work defined in [18]
domains, price, or energy efficiency, sharing of resources
is to make experiments better by using the Cloud in a number
between cloud providers, networking in the deployment of
of ways. The project [19] would investigate a range of
services across multiple cloud providers, additional privacy,
problems in the established area of computational abstract
security and trust management layers atop providers, support
algebra in order to see whether, or how, they can be effectively
of context-aware applications and automatic management of
parallelized using this framework.
service elasticity .
The aim of the project [20] is to investigate the practical
Objectives of the research are to design an agent focused
issues which affect data migration in the cloud and to propose
on aggregation of services for cloud clients. The issues
mechanisms to specify policies on data migration and to use
considered in our research are:
these as a basis for a data management system. The work
 To design a cognitive agent based novel architecture/
defined in [21] aims to investigate how a migration of
scheme for discovering futuristic cloud services (that
applications may result in changes to the way that work is
may be in demand) and develop a repository of the same
actually done. [22] investigates the use of cloud computing
by networking multiple cloud providers.
for mobile network data archiving: there are varieties of topics
 To design a scheme to autonomously and intelligently
in distributed systems including network measurement,
monitor, negotiate and aggregate the resources from the
privacy, sanitization, data protection and computation
cloud repository based on the QoS (time, price,
caching.
availability) defined in the cloud client’s requests. The
The research work in [23] discusses security issues. The
scheme shall explore the use of virtualization in system
topics of research within the topic of Cloud Verification,
and resources in order to minimize energy usage whilst
Validation and Testing (VV&T) from formal verification
still meeting the service requirements and operational
through to empirical research and metric validation of multi
constraints of a cloud.
part or parallel analysis are discussed in [24]. The aim of the
 To design a scheme to dynamically and automatically
project in [25] is to apply constraint programming techniques
schedule and deliver the services to the requested clients
to solve issues in cloud environment efficiently.
ensuring high availability of services and to develop
The work in [26] explores the use of virtualization in
billing and pricing model for measuring cloud services
system and network resources in order to minimize energy
utility.
usage whilst still meeting the service requirements and
operational constraints of a cloud. [27] discusses the
IV. PROPOSED METHODOLOGY
consequence of dynamically provisioned resource allocation
under denial of service attacks, in order to reduce the wasting
The research work aims at aggregating and providing
of resources. [28] proposes to revise the analytical model to
customized set of services to the requesting clients in an
accommodate Cloud Computing and carry out experiments
efficient manner.
and measurements, to compare the responsiveness with
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3. Tutorial Paper
Proc. of Int. Conf. on Advances in Communication, Network, and Computing 2013
A. Discovery of cloud services
The cloud providers are networked by segmenting or
clustering them based on type of services provided,
geographical locations etc. Cognitive agents crawl blindly
through the cloud to discover the cloud services fulfilling
the futuristic requests and build the repository of services.
Further request prediction may be done using log record,
click stream record and user information or Markov model to
anticipate futuristic requests for discovering the cloud
services. Discovery process may be carried out in parallel
using the concept of agent cloning. Repository shall be
updated at regular frequency to eliminate the stale information
using aging techniques. Multidimensional data structure
shall be deployed to store the cloud services in the repository.
Efficient indexing algorithms and meta-services (service
cache) shall be adopted to retrieve the service information
from the repository to improve the performance of the
repository access. The repository shall store the services
offered, vendor details, pricing, current status, QoS etc.
B. Aggregation of requested services
Based on the service requests from cloud clients cognitive
agents monitor the status of the services, negotiate with the
vendors, and aggregate them based on the specified QoS.
Unsupervised learning mechanism may help the agents to
negotiate intelligently for better prices to aggregate and
distribute the cloud services. English auctions may be used
to maximize the profits for vending the services. Multiple
options of aggregated services are to be given to the clients
in order to increase their satisfaction level.
C. Distribution of services
After the services are aggregated they are to be
distributed in a customized way. Scheduling has to be done
in an optimal way so as to maximize the availability and utility
of services. Billing and pricing algorithms are to be developed
for the delivered services. All the above objectives will be
simulated under various scenarios to assess the performance
and effectiveness of the proposed scheme. The simulation
shall be carried out on IBM Blade Center HS22 using
compatible programming language.
V. POSSIBLE OUTCOME AND CONCLUSIONS
Services on the cloud are plenty but the clients are not
able to get the required services. There is no common
repository of availability of cloud services. The proposed
work will develop a framework to overcome the above
mentioned issues. Further the usage of cognitive agents
offers several benefits in aggregating cloud services such as
autonomy in discovering the cloud services, developing and
updating the repository, embedding intelligence, flexibility in
negotiation, adaptability to network environments,
customization of QoS requirements etc. The research work
may be enhanced in future by employing some agent based
solutions to other issues such as cloud management,
enablement, and interoperability and to develop some
applications. Further we have planned to publish our research
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findings in referred journals and present in national/
international conferences.
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