Distributed Channel Management in Uncoordinated Wireless Environments

1. Distributed Channel Management in Uncoordinated Wireless Environments Arunesh Mishra, Vivek Shrivastava, Dheeraj Agarwal, Suman Banerjee, Samrat Ganguly University of Wisconsin & NEC Labs Presented by: Anuradha Kadam February 27, 2007

2. Outline • Introduction • Background • MAXchop Algorithm • Practical Considerations • Simulations • Implementation • Conclusion

3. Introduction • Wireless 802.11 hotspots: uncoordinated • Unsatisfactory and unpredictable network performance • Primary focus: fairness problem • Channel assignment: channel-hopping

4. Key Components • Channel Hopping • Switching Overhead • Impact on TCP • Partially Overlapped channels • Client-driven Assignment

5. Outline • Introduction • Background • MAXchop Algorithm • Practical Considerations • Simulations • Implementation • Conclusion

6. Background • Channel Assignment Techniques • Non-overlapping channels • Static approach – unfairness • Least Congested Channel Search (LCCS) - distributed • CFAssign using Randomized Compaction (RaC) - centralized www.cs.wisc.edu/~arunesh/chop06.ppt

7. Background • Using Partially Overlapped channels • “Partially Overlapped Channels not considered harmful” • As physical separation increased, amount of interference decreased and this led to increase in throughput • At lower separation levels, throughput can be increased by increasing channel separation. • Increase spatial re-use by careful selection

8. Channel Hopping • Channel Hopping Sequence • Periodicity • Throughputs of interfering APs get averaged out to equal • values

9. Outline • Introduction • Background • MAXchop Algorithm • Practical Considerations • Simulations • Implementation • Conclusion

10. MAXchop Algorithm

11. MAXchop Algorithm • Initialize • Bootup or periodically (a week) • Initialize channel assignment with pseudo-random hopping sequence • Hop • End of hopping period (Nsts) • Computes new hopping sequence • Based on information about hopping sequences of interfering APs. • Compute MinMax • Returns a color from C such that it distributes the interference equally among all neighbors of x. • For simplicity, assume color is chosen randomly

12. MAXchop Algorithm • Partially Overlapped channels • ρ(u,i,x,j) if AP u on channel i interferes with AP x on channel j • Return binary value or an accurate estimate of interference • Px(u) I(i,j) received power if tx and rx on channels i and j • Received power should be above a certain threshold to cause interference – binary value • ρ(u,i,x,j) = Px(u) I(i,j) – accurate estimation

13. Outline • Introduction • Background • MAXchop Algorithm • Practical Considerations • Simulations • Implementation • Conclusion

14. Practical Considerations • Implementing Channel Switching • Client-AP coordination • Beacon message • Channel Switch Overhead • 20 ms for Prism 2.5, 6 ms for Atheros • Triggered during low periods of activity • Slot duration large • Gains v/s overhead

15. Practical Considerations • Interfering APs estimation • Client driven • AP driven • Asynchrony in hopping • different hopping periods • asynchronous time slots • over long periods performance is same

16. Outline • Introduction • Background • MAXchop Algorithm • Practical Considerations • Simulations • Implementation • Conclusion

17. Simulations • Packet-level simulations • Hotspot topologies derived from Wigle • Compare against LCCS and RaC • AP locations for dense urban area • Partitioned into 12 non-interfering topologies

18. Simulations

19. Simulation Methodology • NS-2 simulator • Slot durations loosely synchronized • Switch latency of 20ms • Two metrics: • Aggregate network throughput • Fairness in per-AP throughput • Jain’s fairness index • 5 clients on average

20. Simulation-Results (1) • Sample Topology • 27 APs with uneven density • 8 suffer considerable interference • Remaining had similar throughputs

21. Simulation-Results (1)

22. Simulation-Results (2)

23. Simulation-Results (2) • 12 urban topologies • Evaluate only partially-overlapping channels. • Channel hopping improves fairness over LCCS by an average of 42%. • Ch. Hopping gives performance improvement of 30%.

24. Outline • Introduction • Background • MAXchop Algorithm • Practical Considerations • Simulations • Implementation • Conclusion

25. Implementation • Five APs • One client/AP • Typical hotspot area • Different methods of channel assignment • NOV-LCCS, NOV-MAXchop, POV-MAXchop, POV-static • TCP/UDP throughputs

26. Results - TCP • Throughput gains: 15.13% by POV-MAXchop over NOV-chop & 15.05% by POV-static over NOV-LCCS

27. Results - UDP • Throughput gains: POV-MAXchop improves by 10% • Improvement in fairness

28. Outline • Introduction • Background • MAXchop Algorithm • Practical Considerations • Simulations • Implementation • Conclusion

29. Conclusion • Channel hopping: • simple and efficient method • Good fairness properties • Utilize partially overlapped channels • Provide throughput gains in dense networks.

30. Questions??