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Simulation Results. Pareto Frontier. Feasible region. Breakdown point. Figure 1: Win-win situation: all WLANs see an increase in throughput. Where ,. is the throughput between i th AP-client pair. is the Transmit power of the i th AP-client pair.
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Simulation Results Pareto Frontier Feasible region Breakdown point Figure 1: Win-win situation: all WLANs see an increase in throughput Where, is the throughput between ith AP-client pair is the Transmit power of the ith AP-client pair is the CCA threshold of the ith AP-client pair is the path loss between ith AP and jth client Figure 2: 10 APs with one client each was randomly spread on a square of side S (S = 50m… 900m). Aggregate throughput improvement depends on density of deployment is the thermal noise Figure 3: Throughputs of 10 APs with 2 clients each. Notice APs 6 to 10 gain less, when they use MIN as utility function. Throughput at Pareto Optimal configuration depends on choice of utility function is the CCA threshold of the ith AP-client pair Proposed solution Problem Coordinated configuration of wireless networks: A win-win approach based on bargaining • Cooperative Approach • Devices contact a central Configuration Server • Devices choose a performance function • Performance function should be flexible (802.11 devices expect high bandwidth and use high transmit power, and Bluetooth devices require low bandwidth and have lower power limitation) • Configuration Server computes optimal configuration and commands the devices • Devices set tx-power, Frequency • Plummeting costs of wireless devices resulted in dense deployments • Apartment buildings, Enterprise deployments • Possible uncoordinated configurations • Default – Poor performance • Myopic – High Interference • Heterogeneous devices using the same unlicensed spectrum • 802.11abg • Bluetooth • ZigBee • Need for alternative, informed, socially responsible configuration Configuration Server Internet Formulation Objective: To find the optimal configuration, which has the following desirable fairness properties • Symmetry – Equal gains to all participating entities • Universal Improvement – No participating entity should observe a decrease in performance • Significant throughput improvement • Universal improvement (Figure 1) • Aggregate throughput improvement for Cooperative configuration (Figure 2) • less improvements as nodes get closer • In Figure 3, the APs use two different utility functions • AVG = Average Throughput • MIN = 1 if (minimum Throughput of two clients > threshold) • 0 Otherwise • Choice of utility function is important • Utility function could be designed to meet specific needs Pratap Ramamurthy, Jittapat Bunnag, Theophilus Benson, Aditya Akella and Suman Bannerjee Almir Mutapcic and Gireesh Shrimali Can be solved using standard techniques like simulated annealing. Bargaining based optimization problem for WLANs and throughput depends on 1. Where, 2. The neighborhood set 3. Starvation conditions due to CSMA