adaptive and context aware service discovery for the internet of things - rusmart 2013 conference
DESCRIPTION
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.TRANSCRIPT
Adaptive and Context-aware Service Discovery
for the Internet of Things
Talal Ashraf Butt, Iain Phillips, Lin Guan, George Oikonomou
Loughborough University, UK
1
Agenda
2
Service Discovery role
IoT vision
TRENDY SD protocol
Experiments and Results
TRENDY techniques
Conclusion and Future work
IoT vision
IoT
vision
Any* Integration
WoT
Standardisation
for Interoperability
Web level
integration
Anywhere
Anytime
Anything
Anyone
3
Role of Service Discovery
4
Router User 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
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
Our Vision
6
6LoWPAN Internet of Things
Service discovery
Web Services
Discoverability
Interoperability
Web of Things
WoT: SD Requirements
7
6LoWPAN General
Compact
Size
Sleep
Cycles
Heterogeneity
Scalability
Efficiency
Service
Selection
Requirements
Interoperability
Compact
packets
Service
Composition
Requirements
Solution: TRENDY SD Protocol
Trend-based
Serivce Discovery
Protocol
Interoperable Compact Context
Aware Adaptive
8
Service Discovery
9
Architecture
10
CoAP
Service
Invocation
IETF’s standard
Existing Web
Constrained
domains
Restful Web Service Paradigm
Compact
Interoperable Low
overhead
IoT requirement
11
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
Service Description
Diverse
Requirements
Compactness Semantic
Detail
Use Simple format
Also allow other formats Solution
13
TRENDY Timer
14
TRENDY Timer
15
TRENDY Timer
16
Localised
traffic
Resource
Awareness
In-network
data
processing
Increases
Scalability
Base for
Service
Composition
Benefits of
Grouping
Location-based Grouping
17
APPUB (Adaptive Piggybacked Publishing)
18
TRENDY Protocol
19
Alternatives
• Multicast
• Directory-less
• Complex application
gateway
• Control overhead
• In progress
• Can use TRENDY
techniques
uBonjour SSLP based IETF RD
20
Experiments and Results
21
DA
UA
Edge-Router
RPL routing protocol
ContikiMAC as RDC
6LowPAN
Of 35 Nodes
Linux
processes
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
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
