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IoT Naming, Discovery and Semantic Search
1. Naming, Search and Discovery in IoT
Issues and proposed solutions
in the FP7 EU IoT.est Project
2. IoT.est – a quick snapshot
• IoT.est will develop a test-driven service creation environment (SCE)
for Internet of Things enabled business services.
– The SCE will enable the acquisition of data and control/actuation of sensors,
objects and actuators.
• The project will provide the means and tools to define and
instantiate IoT services that exploit data across domain boundaries;
• IoT.est will facilitate run-time monitoring and will enable autonomous
service adaptation to environment/context and network parameter
(e.g. QoS) changes.
3. IoT.est: The Key issues
• IoT enabled Business Services: Semantic Description
• Service Composition: A Knowledge based Approach
• Service Components: Re-usable, Interoperable and Adaptive
• Abstraction: Mapping to Heterogeneous Platforms and Large Scale
Deployment
• Testing (Design Time): Automated Generation of Tests
• Monitoring (Run-Time): Context-aware Service Adaptation
4. Consortium
• 8 partners, 7 countries
• Project Lead:
CCSR, University of Surrey
• Started in:
October 2011
Industry PTIN, ATOS, SIE
SME TT, AI
Research Centre NICT
Higher Education UNIS, UASO
5. IoT.est
• IoT + SOA + Test
– Our focus is on IoT-enabled SOA + Test
• IoT.est will not implement another IoT platform
– We assume low-level connectivity, information communication and
device-level services are provided by other IoT platforms.
– We work on IoT-enabled service life-cycle support and brining “Test” to
IoT service and system design, implementation and deployment.
• However, naming and discovery is also an issue for IoT.est.
6. Naming and Discovery issues
• How to name, find and access the IoT resources,
services and test/service modules.
– Service designers need to know:
• What resources are available
• Where they come from
• How to access them
– We consider using reusable test components to evaluate and/or
validate:
• Availability
• Reliability
• Adaptability
• …
7. Using semantic data
• Semantic data for modelling and describing
– Resources
• Gateway, sensors, processing resources
– Entities
• Physical world objects
– Features of interest for each entity
– Services
• IoT services and interfaces
– Test functions and test modules
• (semantic) TTCN3?
9. Linked data approach
• IoT resources will be addressed by a URI.
• By referring to a URI, we will be able to receive meaningful
information about a resource (semantic annotation).
• A URI will define the service interface to interact with IoT
resources.
• The low-level name resolution could be handled by other existing
framework or component or an abstraction layer in the case of
6LowPAN and CoAp.
– directly (with some intermediaries)
– or on other non-IP platforms we need an overlay layer or a
middleware (gateway) to represent the IoT resources (virtualisation).
10. Discovery
• IoT.est will provide an integrated semantic annotation framework to
describe IoT resources, entities, services and test functionalities.
• The search and discovery will be based on the attributes of the
resources/entities and services described in the semantic
annotations.
• So this will be more a semantic search and reasoning issue.
11. What are the practical steps?
• Linked data approach is a promising way of integrating data from
different sources and interlinking semantic descriptions.
• Alignment between different description models for IoT
Services/Resources/Entities;
• Proposing reference and abstract models for semantic descriptions
in IoT (e.g. similar to W3C SSN approach).
• However, semantic data processing is not often easy in resource
constrained environments (such as IoT)
– Binary RDF or N3 could be potential solutions.
• Distribution of resources and scalability of solutions are also other
key challenges.