Optimal Load Distribution in Large Scale WLANs Utilizing a Power Management Algorithm

5/2/20075/2/2007 IEEE Sarnoff Symposium 2007IEEE Sarnoff Symposium 2007 11

Optimal Load Distribution in Large Optimal Load Distribution in Large Scale WLANs Utilizing a Power Scale WLANs Utilizing a Power

Management AlgorithmManagement Algorithm

Presented by Mohamad Haidar, Ph.D. Presented by Mohamad Haidar, Ph.D. CandidateCandidate

University of Arkansas at Little University of Arkansas at Little RockRock


Presentation OutlinePresentation Outline

IntroductionIntroduction• Wireless Local Area Networks (WLANs)Wireless Local Area Networks (WLANs)• Access Points (APs) congestionAccess Points (APs) congestion

Problem StatementProblem Statement Related WorkRelated Work Proposed SolutionProposed Solution

• Minimizing the load at the Most Congested AP (MCAP)Minimizing the load at the Most Congested AP (MCAP)• Power Management AlgorithmPower Management Algorithm

Problem FormulationProblem Formulation AlgorithmAlgorithm Numerical AnalysisNumerical Analysis ResultsResults ConclusionConclusion Future workFuture work


IntroductionIntroduction

Wireless Local Area Wireless Local Area Networks.Networks.• AirportsAirports• HotelsHotels• CollegesColleges

What is AP congestion?What is AP congestion?CCAPAP= (R= (R11+ R+ R2+..+ 2+..+ RRNN)/BW)/BW

CCAPAP: Congestion at AP: Congestion at APR : Data rate of a user connected to the R : Data rate of a user connected to the

APAPBW: Bandwidth (i.e. BW=11 Mbps for IEEE BW: Bandwidth (i.e. BW=11 Mbps for IEEE

802.11b)802.11b)

1 2 ... jN

j

U U U

BW

+ + +


Problem StatementProblem Statement

Congestion at hot spots Congestion at hot spots

• Degrades network throughput Degrades network throughput Slowest station will make other stations wait Slowest station will make other stations wait

longerlonger

• Unfair load distribution over the network Unfair load distribution over the network causes bottlenecks at hot spots.causes bottlenecks at hot spots.

• Inefficient bandwidth utilization of the Inefficient bandwidth utilization of the networknetwork


Related WorkRelated Work

Y. Lee, K. Kim, and Y. Choi. “Optimization of AP placement and Channel Assignment in Y. Lee, K. Kim, and Y. Choi. “Optimization of AP placement and Channel Assignment in Wireless LANs.”Wireless LANs.” LCN 2002. 27th Annual IEEE Conference on Local Computer Networks, LCN 2002. 27th Annual IEEE Conference on Local Computer Networks, pages 831-836, November 2002. pages 831-836, November 2002.

ILPILP

R. Akl and S. Park. “Optimal Access Point selection and Traffic Allocation in IEEE R. Akl and S. Park. “Optimal Access Point selection and Traffic Allocation in IEEE 802.11 Networks,”802.11 Networks,” Proceedings of 9th World Multiconference on Systemics, Cybernetics Proceedings of 9th World Multiconference on Systemics, Cybernetics and Informatics (WMSCI 2005): Communication and Network Systems, Technologies and and Informatics (WMSCI 2005): Communication and Network Systems, Technologies and ApplicationsApplications, paper no. S464ID, July 2005., paper no. S464ID, July 2005.

ILP ILP

I. Papanikos, M. Logothetis, "A Study on Dynamic Load Balance for IEEE 802.11b I. Papanikos, M. Logothetis, "A Study on Dynamic Load Balance for IEEE 802.11b Wireless LAN," Wireless LAN," Proc. 8th International Conference on Advances in Communication & Proc. 8th International Conference on Advances in Communication & Control,Control, COMCON 8COMCON 8, Rethymna, Crete/Greece, June 2001., Rethymna, Crete/Greece, June 2001.

Number of users associated rather than traffic load.Number of users associated rather than traffic load.

H. Velayos, V. Aleo, and Karlsson, “Load Balancing in Overlapping Wireless LAN H. Velayos, V. Aleo, and Karlsson, “Load Balancing in Overlapping Wireless LAN Cells”, Cells”, Proceedings of IEEE ICC 2004Proceedings of IEEE ICC 2004, Paris, France, June 2004. , Paris, France, June 2004.

Balance index.Balance index.


Proposed SolutionProposed Solution

We propose solving the congestion at the hot spots We propose solving the congestion at the hot spots by decrementing the power transmitted by the by decrementing the power transmitted by the MCAP in discrete steps until one or more users can MCAP in discrete steps until one or more users can no longer associate with any AP or their data rate no longer associate with any AP or their data rate can no longer be accommodated.can no longer be accommodated.

Advantages:Advantages:• Load is fairly distributedLoad is fairly distributed• Increase in data rate throughput per userIncrease in data rate throughput per user• Less adjacent and co-channel interference.Less adjacent and co-channel interference.


Problem FormulationProblem Formulation

MCAP ILP formulation:MCAP ILP formulation:

Subject to

minijx

1 2max{ , ,..., }MC C C1 i M≤ ≤ 1 j N≤ ≤

1

1N

ij

i

x=

=∑

1

M

i ij

j

j

U x

CjBW

=

•=

∑

for j= 1,…, M

for i= 1,…,N


AlgorithmAlgorithm

Compute Received Signal Strength Indicator (RSSI) at Compute Received Signal Strength Indicator (RSSI) at each usereach user

Generate a binary matrix that assigns “1” if a user’s Generate a binary matrix that assigns “1” if a user’s RSSI exceeds the threshold value or “0” otherwise.RSSI exceeds the threshold value or “0” otherwise.

Invoke LINGO to solve the ILPInvoke LINGO to solve the ILP Identify the MCAPIdentify the MCAP Decrement its transmitted power by 1 dbmDecrement its transmitted power by 1 dbm Repeat previous steps until one or more user can no Repeat previous steps until one or more user can no

longer associate with an AP.longer associate with an AP. Observe the power levels at each AP and the best Observe the power levels at each AP and the best

user’s association and best loads at APs.user’s association and best loads at APs.


Numerical AnalysisNumerical Analysis

Receiver Sensitivity at the Receiver Sensitivity at the user is -90 dBmuser is -90 dBm

Transmitted Power at each Transmitted Power at each AP is 20 dbmAP is 20 dbm

11008

01009

101010

00107

00116

11115

10004

10003

01002

01111

AP4AP3AP2AP1User Number

4

1

2


Numerical Analysis ContinuedNumerical Analysis Continued

Traffic is randomly generated Traffic is randomly generated between 100Kbps and 1Mbps for between 100Kbps and 1Mbps for each usereach user

9368

6839

80510

7387

3496

5765

4674

6673

5662

7411

Traffic (Kbps)

User Number

Service Area Map


ResultsResults

10008

01009

001010

00107

00016

00105

10004

10003

01002

00101

AP4AP3AP2AP1User Number

Each user is associated to Each user is associated to one and one and ONLYONLY one AP. one AP.

1

1

1


Results ContinuedResults Continued

Load is distributed fairly among APs.Load is distributed fairly among APs. Final transmitted power levels at each AP is: 11 Final transmitted power levels at each AP is: 11

dBm, 9 dBm, 4 dBm and 3 dBm, respectively.dBm, 9 dBm, 4 dBm and 3 dBm, respectively.

0.3615 0.2393 0.2393AP4

0.4559 0.3547 0.2283AP3

0.4155 0.5378 0.4735AP2

0.4404 0.5416 0.7323AP1

Congestion factor with Power Mgmt

Congestion factor solution according to [2]

Initial Congestion factor:

(No Power Mgmt)

Congestion Factor comparison



Different radii sizes Different radii sizes after power after power adjustmentadjustment

Users do NOT Users do NOT always associate to always associate to the closest AP.the closest AP.

Service area map after Power Mgmt



Congestion Factor Comparison

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

AP1 AP2 AP3 AP4

A P n u m b e r

Init ial Congest ionFact or: No PowerManagement

Congest ion Fact oraccording t o [ 2]

Congest ion Fact orwit h PowerManagement

4 APs

Comparison between Congestion Factors

0.00000.10000.20000.30000.40000.50000.6000

A P n u m b e r

Init ial Congest ionFact or, NPM

Congest ion Fact orbased on [ 2]

Congest ion Fact orbased on PowerManagement

9 APs

Congestion Factor Comparison (16 APs)

0.00000.05000.10000.15000.20000.25000.30000.35000.40000.4500

A P n u m b e r

Init ial congest ion f act or: NPM

Congest ion Fact or based on [ 2]

Congest ion f act or wit h power Management

16 APs


ConclusionConclusion

We proposed an algorithm to reduce We proposed an algorithm to reduce congestion and distribute the load congestion and distribute the load fairly among APs while adjusting the fairly among APs while adjusting the transmitted power level at APs.transmitted power level at APs.

The model has shown to perform The model has shown to perform well for networks of different well for networks of different topologies.topologies.


Future WorkFuture Work

Work is undergoing to Work is undergoing to • extend the model to include inter- and extend the model to include inter- and

intra-cell interferences and channel intra-cell interferences and channel assignments.assignments.

• Apply the model to a dynamic user Apply the model to a dynamic user distribution that changes over time.distribution that changes over time.

Optimal Load Distribution in Large Scale WLANs Utilizing a Power Management Algorithm

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