1. 1 Min Power Routing in Wireless Networks Hai Jiang and Zhijun Huang March 22, 2001 CS215 Project Report:

2. 2 Outline Introduction Previous Work Problem Formulation Modified Bellman-Ford Algorithm Simulation Results Conclusion

3. 3 Introduction Why Min Power in Wireless Network? 1. Limited Energy : Battery Operated Network 2. Interference Reduction and Spectrum Reuse How to minimize power consumption? 1. Physical Level: Low-power CPU/Display High-capacity Battery => Little Room for further reduction 2. Higher Level: Power-aware protocols MAC Layer Network Layer * …

4. 4 Previous Work Singh and Raghavendra (98) 1/E remain : reflect node’s reluctance to forward packets Non-localized Dijkstra’s Algorithm: Shortest Weighted Path Rodoplu and Meng (98) Power consumption: u(d)= d 4  2  10 8 Non-localized Bellman-Ford Algorithm: Shortest Path Gomez etc (99) Power cost function: Pi * f(Bi) Heizelman and Chandrakasan (00) Radio Model: E tx (k, d) = E elec * k + E amp * k * d 2 Hierarchical Clustering

5. 5 Existing Problem Network with minhop algorithm Critical Node, N6, expends power faster => die first Problem: how to balance power consumption? How to consider hop-count constraint? 1 0 2 34 5 6 0

6. 6 Radio Model Transceiver/Receiver Circuity E elec = 50nJ/bit Transmit Amplifier E amp = 100pJ/bit/m 2 Transmit E tx (k, d) = E elec * k + E amp * k * d 2 Receive E rx (k) = E elec * k

7. 7 Problem Formulation Each Node : Remaining Energy Ei Each Edge : Transmission Energy Pi Object: For each path, Min such that, Ei > Emin and Hop-count < M => Min, such that Hop-count < M

8. 8 Modified Bellman-Ford Algorithm

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11. 11 Simulation Settings Method Simulator : written in C; Algorithms: Min-hop Min-power w/ Hop Constraint Min-power w/o Hop Constraint Parameters RadioRange : 100 m Network Size : 600 m x 600 m Node Number : 100 - 200 Max Hop : 5, 10, 20, No Constraint Time Steps : 2000 rounds

12. 12 Min-power prolongs network lifetime!

13. 13 Network Density increase => Min-power is more effective

14. 14 Critical nodes in Minhop die fast => Minhop is the worst !

15. 15 Network Density increase => Min-power is more effective

16. 16 Original Network

17. 17 Minhop v.s. Minpower at Time = 1000

18. 18 Minhop v.s. Minpower at Time = 2000

19. 19 Minhop and Minpower w/o constraint : Consume Similar Energy

20. 20 More node died in Minhop => Minhop Consume Less Energy at later time

21. 21 Conclusion Develop min power routing algorithm with hop constraint Network lifetime prolongs in this algorithm Energy savings are greater in Densor networks Next improvement: try to do simulation in GlomoSim