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Optimal Data Compression and Forwarding in Wireless Sensor Networks

Optimal Data Compression and Forwarding in Wireless Sensor Networks. Bulent Tavli, Mehmet Kayaalp, Ibrahim E. Bagci TOBB University of Economics and Technology Ankara, Turkey. Goals. Maintain balanced energy consumption among sensors Increase network lifetime

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Optimal Data Compression and Forwarding in Wireless Sensor Networks

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  1. Optimal Data Compression and Forwarding in Wireless Sensor Networks Bulent Tavli, Mehmet Kayaalp, Ibrahim E. Bagci TOBB University of Economics and Technology Ankara, Turkey

  2. Goals • Maintain balanced energy consumption among sensors • Increase network lifetime • Focus on whole network rather than individual nodes • Exploit data compression • Explore different strategies for mitigating sensor network hotspots

  3. Transmission Scheduling In a many-to-one (converge-cast) multi-hop wireless sensor network, how should we schedule transmissions so as to balance energy usage and maximize lifetime? …

  4. Direct Transmission … High energy drain in the furthest nodes

  5. Next Hop … High energy drain in the closest nodes

  6. Split Transmissions … Will a scheme like this help?

  7. Problem Definition • Given • Sensor locations • Power model • Traffic generation pattern • Initial energy distribution • Goal • Determine optimal flow pattern to maximize network lifetime • Solution • Linear programming

  8. Models • Power model: • Compression model:

  9. Linear Program for flow balancing

  10. Linear Program for flow balancing and data compression

  11. Strategies • NCFB (No Compression and Flow Balancing) • Only flow balancing • MCFB (Mandatory Compression and Flow Balancing) • All nodes compress all of their data • Flow balancing • OCFB (Optimal Compression and Flow Balancing) • Nodes compress their data and balance the flow on the network jointly

  12. 1 2 3 4 5 6 Example 1: All nodes compress Pcp = , node-separation = 15m

  13. 1 2 3 4 5 6 Example 2: No compression at all Pcp = 10, node-separation = 15m

  14. 1 2 3 4 5 6 Example 3: Some compression Pcp = 10, node-separation = 25m

  15. 1 2 3 4 5 6 Example 4: All nodes compress Pcp = 10, node-separation = 80m

  16. Conclusions • Data compression is becoming an integral part of in-network data processing • Allocate energy budget on compression and forwarding optimally • Linear Programming • Avoid data compression • Small network & high compression energy • Partial data compression • Large network & high compression energy • Small network & low compression energy • Compress most of the data • Large network & low compression energy • For all parameter space jointly optimizing data compression and load balancing results in maximal network lifetime

  17. Q&A

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