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TRENDY: Adaptiveand Context-AwareService DiscoveryProtocol for 6LoWPANs       Talal Ashraf Butt, Dr. Iain Phillips,      D...
Overview• WoT vision and Role of Service Discovery (SD)• WoT SD Requirements• Our proposed solution: TRENDY• Experiments a...
Web of Things (WoT)How to make application-specific WSNs to be          active part of the web?       6LoWPAN             ...
Role of Service Discovery    User Agent                  I need * service                                                 ...
Existing Solutions: Gaps     6LoWPAN constraints               Heavy Dependencies   limited              Sleeping         ...
WoT: SD Requirements    Compact        Compact                                                        Scalability     pack...
TRENDY SD Protocol  CoAP  Based                      Service       Context                Grouping                        ...
Service Description• Very simple at registration time (Comma  separated URLs)• Optional: Detailed IETF CoRE well-  known d...
Context awareness                                   Location based tags    User Agent        I need * service in * place  ...
Context awareness                       Service Selection             I need temperature service                      in H...
Discovery Query Options                     I need temperature service                              in H room             ...
Status maintenance                         Every node randomly selects       a interval between 50 and 90% of time window ...
Adaptive timer                                                   Basic Time window = 600                                  ...
Benefit: Adaptive Timer      Increases        status     Decreases     maintenance    Control       interval    Overhead  ...
Grouping                                        Basic Time window = 600                                              GL1 =...
Grouping                                             Basic Time window = 600                                              ...
Multiple available GLs                                                Basic Time window = 600                             ...
Optimal GL Selection• If multiple GLs available• Select one with high rank        Rank = st + nGM - f - (b/1000)          ...
Architecture                        DA         GL                           GL                                            ...
Adaptive Timer: Grouping               Group Members report to             corresponding Group Leaders                    ...
Benefits: Grouping Group    Based on      Enable nodes      their       Service          locations   Composition          ...
Experiments Setup                              • Linux process                   DA         • Java based CoAP Implementati...
Results                Control   Method                 Energy (J)                Packets    BASIC         810        62.0...
Future Work                                      Load balancing                                More responsible GLs     ...
T   h   a   n   k   y   o    uQuestions?    Loughborough University                            25
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Trendy service discovery protocol at WoT 2012

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We propose, trendy, a new registry-based Service Discovery protocol with context awareness. It uses CoAP-based RESTful web services to provide a standard interoperable interface which can be easily translated from HTTP. In addition, trendy introduces an adaptive timer and grouping mechanism to minimise control overhead and energy consumption. Trendy ’s grouping is based on location tags to localise status maintenance traffic and to compose and offer new group based services. Our simulation results show that trendy techniques reduce the control traffic considerably and also reduce the energy consumption, while offering the optimal service selection.

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Transcript of "Trendy service discovery protocol at WoT 2012"

  1. 1. TRENDY: Adaptiveand Context-AwareService DiscoveryProtocol for 6LoWPANs Talal Ashraf Butt, Dr. Iain Phillips, Dr. Lin Guan, Dr. George Oikomonou Loughborough University 1
  2. 2. Overview• WoT vision and Role of Service Discovery (SD)• WoT SD Requirements• Our proposed solution: TRENDY• Experiments and results• Future Work 2
  3. 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. 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 4
  5. 5. Existing Solutions: Gaps 6LoWPAN constraints Heavy Dependencies limited Sleeping Protocols Packet Nodes Size Bulky limited Limited formats Bandwidth ROM and RAMCompact version for 6LoWPAN Architecture Translation PULL-based Overhead 5
  6. 6. WoT: SD Requirements Compact Compact Scalability packets SizeSleep Efficiency 6LoWPAN General RequirementsCycles Requirements Service Heterogeneity Service Interoperability Selection Composition 6
  7. 7. TRENDY SD Protocol CoAP Based Service Context Grouping Adaptivity Restful Composition AwarenessWeb services TRENDY: An Adaptive and Context-Aware Service Discovery Protocol for 6LoWPANs 7
  8. 8. Service Description• Very simple at registration time (Comma separated URLs)• Optional: Detailed IETF CoRE well- known descriptions 8
  9. 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 9
  10. 10. Context awareness Service Selection I need temperature service in H roomUser 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 10
  11. 11. Discovery Query Options I need temperature service in H room of x buildingUser 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 11
  12. 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 = ActiveInterval = 412 GM1 GM6 Interval = 501 Interval = 431 GM2 GM4 Interval = 521 GM5 GM3 Interval = 476 Interval = 511 12
  13. 13. Adaptive timer Basic Time window = 600 GM1 timer counter = 2 GM2 timer counter = 2 DA GM3 timer counter = 3 GM4 timer counter = 2 GM5 timer counter = 3 Interval = 512*2 GM6 timer counter = 2 GM1 GM6 Interval = 501*2Interval = 531*2 GM2 GM4 Interval = 521*2 GM5 GM3 Interval = 476*3 Interval = 411*3 13
  14. 14. Benefit: Adaptive Timer Increases status Decreases maintenance Control interval Overhead 14
  15. 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 15
  16. 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 16
  17. 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 17
  18. 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) 18
  19. 19. Architecture DA GL GL GMGM GM GM GMGM GM GM GM GM Area: INB01 Area: JKF01 19
  20. 20. Adaptive Timer: Grouping Group Members report to corresponding Group Leaders Basic Time window = 600 GL1 timer counter = 3 DA GM1 timer counter = GM GM2 timer counter = GM GM3 timer counter = 2Interval = 412*3 GL1 GM3 Interval = 501*2 GM1 GM2 Interval = 431*3 Interval = 521*3 20
  21. 21. Benefits: Grouping Group Based on Enable nodes their Service locations Composition Reduces Registry load 21
  22. 22. Experiments Setup • Linux process DA • Java based CoAP Implementation COOJA: Simulator • CONTIKI (OS) GL • CSMA (MAC) • CONTIKIMAC (Duty cycling) • ENERGEST (Energy estimation) • C-based CoAP Implementation GM 25 Tmote sky nodes (+1 border router) with 10 runs for 100 minutes 22
  23. 23. Results Control Method Energy (J) Packets BASIC 810 62.08 TRENDY TIMER 163 61.27 TRENDY FULL 297 60.13 23
  24. 24. Future Work  Load balancing More responsible GLs  Large-scale Grouping Scope Adaptivity Proxy Intelligent Timer (e.g. trickle)  Caching  Publish/Subscribe Interoperability Service composition 24
  25. 25. T h a n k y o uQuestions? Loughborough University 25
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