2. 1 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL The X – Matrix Team Adaptive Protocols for Information Dissemination in Wireless Sensor Networks http://www.cs.ucl.ac.uk/students/fshariff/projects/spin

3. 2 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Who, What and How The X-Matrix Team - Wasif, Fahd, Philip, Muhammad and Kumardev The paper - Negotiation-based Protocols for Disseminating Information in Wireless Sensor Networks by Joanna Kulik,Wendi Rabiner Heinzelman,and Hari Balakrishnan, Massachusetts Institute of Technology, Cambridge, MA, USA The broad concepts outlined in the paper Our Approach  De-construction and Analysis of work  Presentation Structure and Flow

4. 3 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Fundamental Concepts Wireless Sensor Networks  Sensors – typical size, weight, power characteristics  Sensor Networks are a subset of Ad Hoc Networks  Fixed / Mobile Routing in Ad Hoc / Sensor Networks  Traditional protocols – Classic flooding, Gossiping  Adaptive protocols – SPIN, Others What are these so-called ‘adaptive protocols’?

5. 4 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Classic Flooding BC D A Sink Node

6. 5 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Problems with Classic Flooding Implosion A B C D (a) A B C (r,s) (q,r) qs r Data overlap Energy Conservation

7. 6 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Gossiping Alternative to Classic Flooding Randomisation to conserve energy Avoids implosion B C D A

8. 7 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL The Ideal Protocol “Ideal” Shortest-path routes No wasted energy No redundant data B D E F G C A

9. 8 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN: Negotiation and Dissemination Overview of SPIN Application-Level Control Meta-Data Negotiation Spin Messages ADV – New data advertisement REQ – Request for data DATA – The actual data message SPIN Resource Management A B A B A B ADV REQ DATA

10. 9 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN family of protocols Point-to-Point SPIN-PP: a 3-stage handshake protocol for point-to- point media SPIN-EC: SPIN-PP with a low-energy threshold Broadcast SPIN-BC: a 3-stage handshake protocol for broadcast media SPIN-RL: SPIN-BC for lossy networks

11. 10 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN-PP A B C E D DATA message ADV message REQ message

12. 11 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN-EC SPIN-PP with simple energy conservation heuristic When the low-energy threshold is observed, the node reduces its participation in the protocol Node can still receive Data messages cannot be transmitted

13. 12 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Questioning SPIN for Point-to-Point Why use PP when we already have BC? Do we need energy conservation or is it application dependent?

14. 13 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Point-to-Point Media Simulations Compare SPIN-PP and SPIN-EC with classic flooding, gossiping and the ideal protocol Parameters of interest include: Data throughput Energy usage Enhanced ns simulator

15. 14 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Simulation Testbed 25 nodes, 59 edges 25 data items 3 items/node  overlap Antenna reach: 10 m No network losses or queuing delays Data Meta-data 500 bytes16 bytes

16. 15 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Unlimited Energy Simulations Flooding fastest -- SPIN-PP -- Ideal -- Flooding SPIN-PP uses 3.5x less energy than flooding

17. 16 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Limited Energy Simulations SPIN-EC distributes nearly the same amount as the ideal SPIN uses energy at a much slower rate -- SPIN-PP -- SPIN-EC -- Ideal -- Flooding

18. 17 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Simulation Issues Does not take into account for any delay caused by meta-data negotiation ns constraints: Memory CPU time A simulator model of a real-world system is necessarily a simplification of the real- world system itself

19. 18 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN-BC Motivations One-to-many communication is: 1/n times cheaper in a broadcast network than in a point-to-point network where n is the number of neighbours for each node Saves energy Lets each node overhear all transactions that occur  coordinate better

20. 19 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN-BC For lossless broadcast network Uses a shared channel Like SPIN-PP, uses ADV, REQ and DATA messages Three differences: Messages sent to a broadcast address When received ADV, sets random timer, sends REQ upon timeout. Other nodes hearing REQ will cancel their timer Nodes will send data to the broadcast address only once, assuming lossless network

21. 20 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL ADV E D REQ D E SPIN-BC Example DATA E D C ADV E D C B A A Nodes with data A Nodes without data A Nodes waiting to transmit REQ

22. 21 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN-RL For lossy broadcast network Two modifications Firstly, if a node does not receive data within a period of time, it sends REQ again Secondly, when a data item is repeatedly requested, the node will wait for a predetermined amount of time before responding to any requests.

23. 22 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN - BC and RL : best option? Open questions: Bandwidth-saving, how about utilising IP Multicast? Reliable multicast?  Need further research Our opinion: if yes, a trimmed-down version of multicasting is needed.

24. 23 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Broadcast Media Simulations Simulation Testbed same as the one used in SPIN-PP with following variations:  Single shared-media channel  Nodes use 802.11 MAC layer protocol  Delay and packet losses taken into account Simulation Setup monarch – extension of ns

25. 24 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Simulations with No Packet Losses --- SPIN-BC --- Ideal --- Flooding SPIN-BC Converges quicker than flooding Dissipates 50% less energy as compared to flooding

26. 25 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Simulations with Packet Losses --- SPIN-BC --- SPIN-RL --- Ideal -- Flooding- SPIN-RL Only ideal and SPIN-RL converge because of their ability to recover from packet loss, rest do not converge This is closer to reality scenario. Expends more energy as compared to BC and the ideal

27. 26 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Data Distributed Per Unit Energy SPIN-RL delivers twice as much data per unit energy than flooding (100% more) --- SPIN-BC --- SPIN-RL --- Ideal --- Flooding

28. 27 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Validity/Relevance of results Simulation environment selected in SPIN-RL is a better representation of real world scenario Channel interference and collision which were ignored in SPIN-BC, PP and EC have been taken into account SPIN-RL: Theoretical integrity consistent

29. 28 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Major Short-comings Simulation Environment does not closely model Wireless Sensor Networks environment False assumption: the infinite supply of energy in SPIN-RL Results fall short of supporting a convincing argument in favour of SPIN protocols

30. 29 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Summary of relevant/similar work What is similar and/or relevant? SPIN and NNTP – comparable? SPIN and Energy-Conservation based routing SPIN and other Flat Multi-hop routing protocols Spin and Others – AIDA, LEACH

31. 30 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN vs Directed Diffusion What is directed diffusion? Similarities:  Optimized for disseminating application-specific information in a sensor network, specifically between source and sink nodes  Use of data naming allows negotiation between nodes prior to data forwarding to eliminate redundancy  Interest (REQ) and data (DATA) caches maintained at each node  Node-local decision making

32. 31 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL SPIN vs Directed Diffusion - 2 Dissimilarities:  SPIN uses a push model for disseminating information to all nodes, while DD uses a pull model for obtaining information  Data is sent to all nodes in SPIN while data is NOT sent to all nodes in Directed diffusion.

33. 32 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Sensor Network Applications and SPIN Applications make the Networks SPIN around Typical Sensor Network Applications Application/Network type – Time Critical Application/Network type – Reliable & Re-Usable What kind of Protocols are optimal ?

34. 33 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Applications and SPIN Application/Network type – Time Critical  Characteristics  Typical example – Seismic Activity Detection  SPIN – is it optimal for this type of apps? Application/Network type – Reliable & Re-usable  Characteristics  Typical example – MARS Habitat Monitoring  SPIN – is it optimal for this type of apps?

35. 34 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Summary and Crystal Ball The Potential of Wireless Sensor Networks The Future of Wireless Sensor Networks The Potential of SPIN The Limitations of SPIN The Future of SPIN

36. 35 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL Ask us! We asked Joanna Kulik, one of the SPIN authors.. X-Matrix: “ Could you address any SPIN protocol weaknesses (if any?)” Joanna: “I haven't thought about SPIN in many years. I'm sure that there are many weaknesses, and that they would be easy to find. With SPIN we were just trying to lay some initial groundwork in the field. With any initial work, there are hundreds of ways that the work could be improved.”

37. 36 X-Matrix Team MSc Data Communications, Networks and Distributed Systems; Computer Science Department, UCL References 1. D. Estrin, R. Govindan, J. Heidemann, S. Kumar, Next century challenges: Scalable coordination in sensor networks, Proc. MOBICOM, 1999, Seattle, 263-270. 2. C. Intanagonwiwat, R. Govindan,, and D. Estrin. Directed diffusion: A scalable and robust communication paradigm for sensor networks. In MobiCOM, Boston, MA, August 2000. 3. Wireless Networks of Devices (WIND) [http://wind.lcs.mit.edu] 4. Praveen Rentala, Ravi Musunnuri, Shashidhar Gandham, Udit Saxena, Survey on Sensor Networks 5. LEACH [http://nms.lcs.mit.edu/projects/leach]