1. 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

2. 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
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IEEE Sarnoff Symposium 2007

3. 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 b)
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IEEE Sarnoff Symposium 2007

4. 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
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IEEE Sarnoff Symposium 2007

5. IEEE Sarnoff Symposium 2007
Related Work
Y. Lee, K. Kim, and Y. Choi. “Optimization of AP placement and Channel Assignment in Wireless LANs.” LCN th Annual IEEE Conference on Local Computer Networks, pages , November 2002.
R. Akl and S. Park. “Optimal Access Point selection and Traffic Allocation in IEEE 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 b 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.
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6. 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.
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IEEE Sarnoff Symposium 2007

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

9. 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
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IEEE Sarnoff Symposium 2007

10. 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
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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
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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.
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IEEE Sarnoff Symposium 2007

13. 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.
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Results Continued
4 APs
9 APs
16 APs
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IEEE Sarnoff Symposium 2007

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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.
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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