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1. TRENDY: Adaptive
and Context-Aware
Service Discovery
Protocol for 6LoWPANs
Talal Ashraf Butt, Dr. Iain Phillips,
Dr. Lin Guan, Dr. George Oikomonou
Loughborough University
1
2. Overview
• WoT vision and Role of Service Discovery (SD)
• WoT SD Requirements
• Our proposed solution: TRENDY
• Experiments and results
• Future Work
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3. Web of Things (WoT)
How to make application-specific WSNs to be
active part of the web?
6LoWPAN Internet of Things
Service discovery Discoverability
Web Services Interoperability
Web of Things 3
4. Role of Service Discovery
User Agent I need * service
Router
(UA)
• 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
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5. Existing Solutions: Gaps
6LoWPAN constraints Heavy Dependencies
limited Sleeping Protocols
Packet Nodes
Size
Bulky
limited Limited formats
Bandwidth ROM and RAM
Compact version for 6LoWPAN Architecture
Translation PULL-based
Overhead
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6. WoT: SD Requirements
Compact Compact
Scalability
packets Size
Sleep Efficiency
6LoWPAN General Requirements
Cycles Requirements
Service
Heterogeneity Service
Interoperability Selection
Composition
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7. TRENDY SD Protocol
CoAP
Based Service Context
Grouping Adaptivity
Restful Composition Awareness
Web services
TRENDY: An Adaptive and Context-Aware Service
Discovery Protocol for 6LoWPANs
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8. Service Description
• Very simple at registration time (Comma
separated URLs)
• Optional: Detailed IETF CoRE well-
known descriptions
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9. Context awareness
Location based tags
User Agent I need * service in * place Directory Agent
(UA) (DA)
• 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
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10. Context awareness
Service Selection
I need temperature service
in H room
User Agent of x building
DA
(UA)
Two Options:
Select the one with
1. Hit count (Popularity)
2. Less battery consumed H room
3. More reliable
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11. Discovery Query Options
I need temperature service
in H room
of x building
User Agent
(UA) DA
URL(s) and IP address(es)
of matched service(s)
Using URI-query with: H room
1. Keyword
2. Keyword and location
3. 1 or 2 with select the optimal option
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12. Status maintenance
Every node randomly selects
a interval between 50 and 90% of time window for status updates
o Static interval Basic Time window = 600
o Multihop effect DA GL1 = Active
GM1 = Active
GM2 = Active
GM3 = Active
Interval = 412
GM1
GM6 Interval = 501
Interval = 431 GM2 GM4
Interval = 521
GM5
GM3
Interval = 476
Interval = 511 12
15. Grouping
Basic Time window = 600
GL1 = Active
DA GM1 = Active
Implements GL GM2 = Active
CoAP resource GM3 = Active
GL1
GM3
Interval = 412
Interval = 501
GM1 GM2
Interval = 431 Interval = 521
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16. Grouping
Basic Time window = 600
GL1 = Active
GM1 = GM of GL1
DA
GM2 = GM of GL1
GM3 = Active
Interval = 412 GL1
GM3
Interval = 501
GM1 GM2
Interval = 431 Interval = 521
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17. Multiple available GLs
Basic Time window = 600
GL1 = Active
DA GM1 = Active
GM2 = Active
GM3 = Active
GL1
GM3
Interval = 412
GL2
Interval = 501
Interval = 476
GM2
GM1
Interval = 521
Interval = 431
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18. Optimal GL Selection
• If multiple GLs available
• Select one with high rank
Rank = st + nGM - f - (b/1000)
st b
(serving time) (battery consumption)
nGM f
(number of (number of failures)
registered GMs)
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25. T h a n k y o u
Questions?
Loughborough University
25
Editor's Notes
WoT vision6LowPAN enables IoTSD allows discoverability of available services in networkWeb Services enables InteroperabilityThe combination can enables the interoperability requires for WoT paradigm applications(1 min) Total 1 min
Existing solutions + Requirements (1 min)6LowPAN requirementsGeneral requirementsTotal 4 mins
TRENDY SDP (1 min)CoAP based Restful web servicesGrouping Service compositionContext AwarenessAdaptivity1 minTotal 5 mins
Grouping -1 + Grouping -2 +Multiple GLs + Optimal GL selection (3 mins)All nodes send status updates to DA Creates the bottleneck problem Multihop effect also increases the problemWe propose grouping to deal with thisWhere some nodes implement the GL CoAP resourceTo let the DA know that it can play the role of GL
Grouping -1 + Grouping -2 +Multiple GLs + Optimal GL selection (3 mins)DA then allocates the GL other nodes in its groupThis way made group members now report to GL instead of DA
Grouping -1 + Grouping -2 +Multiple GLs + Optimal GL selection (3 mins)If DA find out that multiple potential GLs are available in a groupDA uses a rank equation to select the optimal one
Architecture + Adaptive timer: Grouping + Benefits (2 mins)Group members in a group follow the counter value of their GL
Experiment Setup + results (2 mins)Two CoAP ImplementationUses border router between DA and 6LoWPANExperiments done with 25 nodes
Experiment Setup + results (2 mins)Results shows that TRENDY timer decreases the control overheadAnd grouping increases the control overhead and hints to decrease the energy consumptionTotal 19 mins
Future work (1 min)More intelligent timer with pub/subMore responsible GLs to enable service compositionDA as Proxy to get potential benefits of caching and HTTP interoperabilityLarge scale experiments1 min Total 20 minutes