1. Convergecasting In Wireless Sensor Networks Master’s Thesis by Valliappan Annamalai Committee members Dr. Sandeep Gupta Dr. Arunabha Sen Dr. Hasan Cam

2. Outline Problem Statement Preliminary information System model Proposed Algorithms Results Conclusion and Future Work

3. Problem Statement Network construction in a sensor network for Convergecasting Must minimize time consumed for data collection

4. Group Communication Patterns Broadcast Multicast Convergecast

5. 0 12 5 3 4 6 Broadcast & Convergecast Broadcast Convergecast Multicasting 0 12 5 3 4 6 * * * * * Indicates Multicast Group Members

6. Group Communication in Wired Networks Done at the network layer Each pair of nodes can have a separate connection between them Nodes usually share a bus Sharing leads to collision Collision and retransmission leads to power wastage.

7. Group Communication in Wireless Networks Common medium for communication Need a contention based reliable MAC layer in wireless networks Contention increases power consumption For real time data collection, allocating a separate channel for each pair of nodes Channel can be divided based on TDMA, FDMA and CDMA

8. Sensor Network Set of sensors that collectively form a network. Communication medium Frequency used part of ISM band Constraint Power Computation Memory

9. Applications of Sensor Networks Military Surveillance reconnaissance Environment monitoring Fire and flood detection Health monitoring Applications make use of broadcasting and convergecasting Latency must be kept to a minimum

10. Related Work Pegasis: Chain construction for data aggregation Energy consumption high Delay is high Wave Expansion approach Less reliable Broadcast tree construction algorithm proposed by I. Chlamtac

11. Contribution of this Research Work Channel allocation is NP-Complete Two network construction and channel allocation algorithms (CTCCAA) for convergecasting. Currently these allocate time slots and codes Same network can also be used for broadcasting

12. System Model Set of nodes placed in the area of interest Nodes are static Controlling node (root node or base station) Amount of data sensed at each node is constant Controlling node responsible for network construction

13. Convergecast Tree Construction and Channel Allocation Algorithm(CTCCAA) Two algorithms Pipelined CTCCAA Non-pipelined CTCCAA Centralized algorithms capable of allocating codes and slots Node position given as input

14. Pipelined CTCCAA Data collection starts at the leaf nodes. Propagates towards the root node. Generates a parent child relationship between nodes

15. Constraints No two nodes that have parent(s) in the transmission range of each other share the same channel Slot assigned to parent is less than the one assigned to its children

16. Example that illustrates the working of Pipelined CTCCAA 0 1 2 345 12 2 3 41 2 3 34 Maximum Slot Size = 3 * x Where, x is the number of bits sensed by each node

17. Non-pipelined CTCCAA Data collection at independent and non-interfering parts of the network Each node has buffering capability Used for non-real time data collection Algorithm is similar to pipelined version but the reversal of slots is not done

18. Constraints Slot assigned to a child need not be less than the slot assigned to the parent If a child has two possible parent it is assigned to the closest parent

19. Example: Slot assignment for non-pipelined CTCCAA

20. Comparison Metric Latency Convergecasting Graphs with random node placement was generated Calculated time taken for convergecasting on a broadcast tree (Tb,c) Calculated time taken for convergecasting on the network constructed by pipelined CTCCAA (Tc,c)

21. Comparison … Broadcasting Calculated time taken for broadcasting on a broadcast tree (Tb,b) Calculated time taken for broadcasting on the network constructed by pipelined CTCCAA (Tb,c)

22. Results for pipelined convergecasting Ratio on time taken for pipelined convergecasting on graphs with node density 0.3 nodes / unit ^ 2

23. Ratio on time taken for pipelined convergecasting on graphs with node density 0.5 nodes / unit ^ 2

24. Results for non-pipelined Convergecasting Ratio on time taken for non-pipelined convergecasting on graphs with node density 0.3 nodes / unit ^ 2

25. Ratio on time taken for non-pipelined convergecasting on graphs with node density 0.5 nodes / unit ^ 2

26. Results for Broadcasting Ratio on time taken for broadcasting on graphs with node density 0.3 nodes / unit ^ 2

27. Ratio on time taken for broadcasting on graphs with node density 0.5 nodes / unit ^ 2

28. Conclusion & Future work The algorithms proposed successfully construct networks for convergecasting that reduces latency Got accepted for WCNC 2003 Better slot allocation algorithm that completely eliminates idle time wastage

29. References “Tree-based Broadcasting in Multihop Radio Networks” by I. Chlamtac and S. Kutten “The Wave Expansion Approach to Broadcasting in Multihop Radio Networks” by I. Chlamtac and O.Weinstein “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks” by C. Intanagonwiwat, R. Govindan and D. Estrin “Frequency Assignment: Theory and Application” by W.K. Hale “Pegasis: Power-Efficient Gathering in Sensor Information Systems” by S. Lindsey and C. S. Raghavendra