Distributed Channel Management in Uncoordinated Wireless Environments Arunesh Mishra, Vivek...
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Transcript of Distributed Channel Management in Uncoordinated Wireless Environments Arunesh Mishra, Vivek...
Distributed Channel Management in Uncoordinated Wireless EnvironmentsArunesh Mishra, Vivek Shrivastava, Dheeraj Agarwal, Suman Banerjee, Samrat GangulyUniversity of Wisconsin & NEC Labs
Presented by: Anuradha KadamFebruary 27, 2007
Outline
Introduction Background MAXchop Algorithm Practical Considerations Simulations Implementation Conclusion
Introduction
Wireless 802.11 hotspots: uncoordinated Unsatisfactory and unpredictable network
performance Primary focus: fairness problem Channel assignment: channel-hopping
Key Components
Channel Hopping Switching Overhead Impact on TCP Partially Overlapped channels Client-driven Assignment
Outline
Introduction Background MAXchop Algorithm Practical Considerations Simulations Implementation Conclusion
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
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
Channel Hopping
• Channel Hopping Sequence• Periodicity• Throughputs of interfering APs get averaged out to equal values
Outline
Introduction Background MAXchop Algorithm Practical Considerations Simulations Implementation Conclusion
MAXchop Algorithm
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
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
Outline
Introduction Background MAXchop Algorithm Practical Considerations Simulations Implementation Conclusion
Practical Considerations
Implementing Channel SwitchingClient-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
Practical Considerations
Interfering APs estimationClient drivenAP driven
Asynchrony in hoppingdifferent hopping periodsasynchronous time slotsover long periods performance is same
Outline
Introduction Background MAXchop Algorithm Practical Considerations Simulations Implementation Conclusion
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
Simulations
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
Simulation-Results (1)
Sample Topology 27 APs with uneven
density 8 suffer considerable
interference Remaining had
similar throughputs
Simulation-Results (1)
Simulation-Results (2)
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%.
Outline
Introduction Background MAXchop Algorithm Practical Considerations Simulations Implementation Conclusion
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
Results - TCP
Throughput gains: 15.13% by POV-MAXchop over NOV-chop & 15.05% by POV-static over NOV-LCCS
Results - UDP
Throughput gains: POV-MAXchop improves by 10%
Improvement in fairness
Outline
Introduction Background MAXchop Algorithm Practical Considerations Simulations Implementation Conclusion
Conclusion
Channel hopping:simple and efficient methodGood fairness propertiesUtilize partially overlapped channels
Provide throughput gains in dense networks.
Questions??