University of Arkansas at Little Rock Optimal Load Distribution in Large Scale WLANs Utilizing a Power Management Algorithm Presented by Mohamad Haidar, Ph.D. Candidate University of Arkansas at Little Rock 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Presentation Outline Introduction Wireless Local Area Networks (WLANs) Access Points (APs) congestion Problem Statement Related Work Proposed Solution Minimizing the load at the Most Congested AP (MCAP) Power Management Algorithm Problem Formulation Algorithm Numerical Analysis Results Conclusion Future work 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Introduction Wireless Local Area Networks. Airports Hotels Colleges What is AP congestion? CAP= (R1+ R2+..+ RN)/BW CAP: Congestion at AP R : Data rate of a user connected to the AP BW: Bandwidth (i.e. BW=11 Mbps for IEEE 802.11b) 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Problem Statement Congestion at hot spots Degrades network throughput Slowest station will make other stations wait longer Unfair load distribution over the network causes bottlenecks at hot spots. Inefficient bandwidth utilization of the network 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Related Work Y. Lee, K. Kim, and Y. Choi. “Optimization of AP placement and Channel Assignment in Wireless LANs.” LCN 2002. 27th Annual IEEE Conference on Local Computer Networks, pages 831-836, November 2002. R. Akl and S. Park. “Optimal Access Point selection and Traffic Allocation in IEEE 802.11 Networks,” Proceedings of 9th World Multiconference on Systemics, Cybernetics and Informatics (WMSCI 2005): Communication and Network Systems, Technologies and Applications, paper no. S464ID, July 2005. I. Papanikos, M. Logothetis, "A Study on Dynamic Load Balance for IEEE 802.11b Wireless LAN," Proc. 8th International Conference on Advances in Communication & Control, COMCON 8, Rethymna, Crete/Greece, June 2001. H. Velayos, V. Aleo, and Karlsson, “Load Balancing in Overlapping Wireless LAN Cells”, Proceedings of IEEE ICC 2004, Paris, France, June 2004. 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Proposed Solution We propose solving the congestion at the hot spots by decrementing the power transmitted by the MCAP in discrete steps until one or more users can no longer associate with any AP or their data rate can no longer be accommodated. Advantages: Load is fairly distributed Increase in data rate throughput per user Less adjacent and co-channel interference. 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Problem Formulation MCAP ILP formulation: Subject to for j= 1,…, M 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Algorithm Compute Received Signal Strength Indicator (RSSI) at each user Generate a binary matrix that assigns “1” if a user’s RSSI exceeds the threshold value or “0” otherwise. Invoke LINGO to solve the ILP Identify the MCAP Decrement its transmitted power by 1 dbm Repeat previous steps until one or more user can no longer associate with an AP. Observe the power levels at each AP and the best user’s association and best loads at APs. 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Numerical Analysis User Number AP1 AP2 AP3 AP4 1 2 3 4 5 6 7 8 9 10 Receiver Sensitivity at the user is -90 dBm Transmitted Power at each AP is 20 dbm 4 1 2 5/2/2007 IEEE Sarnoff Symposium 2007

Numerical Analysis Continued Traffic is randomly generated between 100Kbps and 1Mbps for each user User Number Traffic (Kbps) 1 741 2 566 3 667 4 467 5 576 6 349 7 738 8 936 9 683 10 805 Service Area Map 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Results User Number AP1 AP2 AP3 AP4 1 2 3 4 5 6 7 8 9 10 Each user is associated to one and ONLY one AP. 1 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Results Continued Congestion Factor comparison Initial Congestion factor: (No Power Mgmt) Congestion factor solution according to [2] Congestion factor with Power Mgmt AP1 0.7323 0.5416 0.4404 AP2 0.4735 0.5378 0.4155 AP3 0.2283 0.3547 0.4559 AP4 0.2393 0.3615 Load is distributed fairly among APs. Final transmitted power levels at each AP is: 11 dBm, 9 dBm, 4 dBm and 3 dBm, respectively. 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Results Continued Service area map after Power Mgmt Different radii sizes after power adjustment Users do NOT always associate to the closest AP. 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Results Continued 4 APs 9 APs 16 APs 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Conclusion We proposed an algorithm to reduce congestion and distribute the load fairly among APs while adjusting the transmitted power level at APs. The model has shown to perform well for networks of different topologies. 5/2/2007 IEEE Sarnoff Symposium 2007

IEEE Sarnoff Symposium 2007 Future Work Work is undergoing to extend the model to include inter- and intra-cell interferences and channel assignments. Apply the model to a dynamic user distribution that changes over time. 5/2/2007 IEEE Sarnoff Symposium 2007