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Adaptive and context aware service discovery for the internet of things - Rusmart 2013 conference

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The Internet of Things (IoT) vision foresees a future Internet encompassing the realm of smart physical objects, which …

The Internet of Things (IoT) vision foresees a future Internet encompassing the realm of smart physical objects, which

offer
hosted functionality as services. The role of service discovery is crucial
when providing application-level, end-to-end integration. In this paper,
we propose trendy: a RESTful web services based Service Discovery
protocol to tackle the challenges posed by constrained domains while
offering the required interoperability. It provides a service selection technique to offer the appropriate service to the

user application depending
on the available context information of user and services. Furthermore,
it employs a demand-based adaptive timer and caching mechanism to
reduce the communication overhead and to decrease the service invocation delay. trendy’s grouping technique creates

location-based teams of
nodes to offer service composition. Our simulation results show that the
employed techniques reduce the control packet overhead, service invocation delay and energy consumption. In addition, the

grouping technique
provides the foundation for group-based service mash-ups and localises
control traffic to improve scalability.

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  • 1. Adaptive and Context-aware Service Discovery for the Internet of Things Talal Ashraf Butt, Iain Phillips, Lin Guan, George Oikonomou Loughborough University, UK 1
  • 2. Agenda 2 Service Discovery role IoT vision TRENDY SD protocol Experiments and Results TRENDY techniques Conclusion and Future work
  • 3. IoT vision IoT vision Any* Integration WoT Standardisation for Interoperability Web level integration Anywhere Anytime Anything Anyone 3
  • 4. Role of Service Discovery 4 RouterUser Agent (UA) I need * service • Switch off the lights in corridor of x building • Give me the overall temperature of x building • Close all the windows when its windy • Close all the windows when no one in the room • If rooms temperature is below x and someone in the room Then Switch on the heating and close the windows
  • 5. Existing Solutions: Gaps 5 limited Packet Size limited Bandwidth Protocols Sleeping Nodes Limited ROM and RAM Bulky formats PULL-based Compact version for 6LoWPAN Translation Overhead Architecture 6LoWPAN constraints Heavy Dependencies
  • 6. Our Vision 6 6LoWPAN Internet of Things Service discovery Web Services Discoverability Interoperability Web of Things
  • 7. WoT: SD Requirements 7 6LoWPAN General Compact Size Sleep Cycles Heterogeneity Scalability Efficiency Service Selection Requirements Interoperability Compact packets Service Composition Requirements
  • 8. Solution: TRENDY SD Protocol Trend-based Serivce Discovery Protocol Interoperable Compact Context Aware Adaptive 8
  • 9. Service Discovery 9
  • 10. Architecture 10
  • 11. CoAP Service Invocation IETF’s standard Existing Web Constrained domains Restful Web Service Paradigm Compact Interoperable Low overhead IoT requirement 11
  • 12. User assistance Push Based Extensible Centralised Decision making Query Sophistication Energy And delay Provided If maintained New Context attributes Service Selection Network-wide view Discovery Efficiency Context Aware Context-Awareness 12
  • 13. Service Description Diverse Requirements Compactness Semantic Detail Use Simple format Also allow other formatsSolution 13
  • 14. TRENDY Timer 14
  • 15. TRENDY Timer 15
  • 16. TRENDY Timer 16
  • 17. Localised traffic Resource Awareness In-network data processing Increases Scalability Base for Service Composition Benefits of Grouping Location-based Grouping 17
  • 18. APPUB (Adaptive Piggybacked Publishing) 18
  • 19. TRENDY Protocol 19
  • 20. Alternatives • Multicast • Directory-less • Complex application gateway • Control overhead • In progress • Can use TRENDY techniques uBonjour SSLP based IETF RD 20
  • 21. Experiments and Results 21 DA UA Edge-Router RPL routing protocol ContikiMAC as RDC 6LowPAN Of 35 Nodes Linux processes
  • 22. Results Timer APPUB • Low overhead • Scalability • Energy efficiency • Better user response • Low overhead • Energy efficiency Grouping • Scalability • Energy efficiency Adaptive Control Traffic Distributed Behaviour Adaptive Caching 22
  • 23. Conclusion and Future work • New feature – Dynamic Service Composition • New techniques – Multicasting for Group-based communication • Experiments – Large scale networks – Multiple networks via DNS 23
  • 24. Any Questions? 24 Email: talalbutt@gmail.com