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Distributed Channel Management in Uncoordinated Wireless Environments Arunesh Mishra, Vivek Shrivastava, Dheeraj Agarwal, Suman Banerjee, Samrat Ganguly.

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Presentation on theme: "Distributed Channel Management in Uncoordinated Wireless Environments Arunesh Mishra, Vivek Shrivastava, Dheeraj Agarwal, Suman Banerjee, Samrat Ganguly."— Presentation transcript:

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 Initialize  Bootup or periodically (a week)  Initialize channel assignment with pseudo-random hopping sequence Hop  End of hopping period (N s t s )  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 P x (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) = P x (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 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 Channel hopping:  simple and efficient method  Good fairness properties  Utilize partially overlapped channels Provide throughput gains in dense networks.

30 Questions??


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