Dynamic Load Balancing and Channel Allocation in Indoor

WLAN

Mohamad Haidar

Committee : Dr. Hussain Al-RizzoDr. Robert AklDr. Haydar Al-ShukriDr. Yupo ChanDr. Hassan ElsalloukhDr. Seshadri Mohan

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Proposal Outline• Background• Problem Statement• Review of Literature• Research Objectives• Project Plan• Conclusion• References• Questions

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Background

• What is WLAN?– Flexible data communications

system– Consists of one or more wireless

devices– WLAN uses IEEE 802.11 standard

• Two types of WLAN:– Ad-Hoc: Two or more PCs

equipped with wireless adapter cards, NO connection to a wired network.

– Client/Server: Multiple wireless devices linked to a central hub (AP) which act as a bridge to the network resources.

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Background(continued)• Family of WLAN:

– 802.11: 1-2 Mbps in the 2.4 GHz band (FHSS or DSSS)

– 802.11a: Extension to 802.11 provides up to 54 Mbps in the 5 GHz band (OFDM)

– 802.11b (Wi-Fi): extension of 802.11 provides 11 Mbps with a fall back to 5.5, 2, and 1 Mbps in the 2.4 GHz. (DSSS)

– 802.11g: offers transmission of 20-54 Mbps over relatively short distances in the 2.4 GHz.(OFDM)

– 802.11n: build on MIMO offers high throughput of 100-200 Mbps

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Problem Statement

• Dynamically balance traffic load on APs and minimize channel interferences by assigning optimal channels (non-overlapping) to the APs on an indoor WLAN.

• Interferences: Co-channel

Adjacent

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Literature Review• Cellular networks review:

– ILP optimization was used on selecting optimal position of BSs in a cellular network [1].

– Divide and conquer is another optimization technique was used to position BSs [2].

– Dynamic load balancing (channels) was applied in cellular networks to reduce call blocking probability [3].

• WLAN review:– Static

• AP placement and channel assignment was proposed in [4] and [5] using an optimal ILP.

• Provides best set of AP locations for load balancing• Constant BW is provided by a channel at an AP regardless of the

number of users

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Literature Review (continued)

• WLAN review:– Dynamic

• Dynamic load balancing was ONLY considered by [8]. But did NOT provide reconfiguration of channels.

• Only proposed an approach to minimize traffic disruption caused by association or dissociation of new nodes to and from their respective APs.

• Other related work:– Moving objects, such as people affect the performance of the

system by introducing large variations in the received signal strength [9].

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Literature Review (continued)

• Other Related work:– Without proper

consideration of cell locations and cell sizes, deployment of high-density WLANS might carry significant risk of poor performance.

WHY?

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Research Objectives• Optimize AP selection and traffic allocation

– Formulate AP placement according to initial traffic

• Optimize dynamic channel allocation– Formulate a dynamic optimal channel

assignment by min. interference between adjacent and co-channel APs.

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Research Objectives (continued)

• Interference by adjacent and co-channel cells should be minimized.

• A node is considered to be covered by an AP if power received from its corresponding AP exceeds a certain threshold value.

• User distribution traffic load will be treated as a statistical Poisson distribution (varying traffic with time).

• Propagation mechanisms will be taken into consideration:• For optimal performance of the whole network, a

centralized decision-making algorithm will be implemented.

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Research Objective (continued)• Formulation

– Objective: • Minimize congestion at bottleneck APs:

max{C1, C2, …, CM}, (1)

Where i is the number of APs, j is the number of candidate APs and Ci is the congestion factor at AP i.

– The objective function is subject to the following constraints(2)

Where xij is a binary variable takes the value of 1 when demand cluster i is assigned to AP j and 0 otherwise.

for j=1,…,M (3)

Where Bj is the maximum bandwidth of AP j, Ti is the average traffic load at demand cluster i.

• Dynamic feature will add the time constraint on these equations!

1 ,1mini L j M

1

1L

iji

x

1

1,

L

i ijjj i

C T xB

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Project Plan

• Phase I:– Has been started and in progress

– Some simulations have been conducted using available software packages

– Optimization and Network flow class with Dr. Yupo Chan

– Realistic indoor environments will aid in formulating optimization problem

Indoor floor plan using different wall materials, door way and Tx.

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Project Plan (continued)

• Phase II:– Formulating the optimization problem– Apply the formulated problem to realistic environments

• Phase III:– Dynamic optimization feature will be added.– Mobility model will be presented in terms of Poisson

distribution– Several simulations will be carried out under different

scenarios and constraints.– Results will be presented and compared to models

reported in [4] and [5].

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Conclusion

• It is expected that the proposed dynamic traffic load-balancing scheme will lead to an effective utilization of the channel and an improvement in capacity and coverage area of WLAN.

• Unlike other schemes this dynamic feature will strive to give the optimal performance as time progresses.

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References1. C. Glaber, S. Reith, and H. Vollmer. “The Complexity of Base Station positioning in Cellular

Networks.” Workshop on Approximation and Randomized Algorithm in Communications Networks, March 2000.

2. E. Yammaz and O. K. Tonguz. “Dynamic Load Balancing Performance in Cellular Networks with Multiple Traffic Types.” IEEE Vehicular Technology Conference, pages 3491-3495, September 2004

3. S. Gordon and A. Dadej. “Design of High Capacity Wireless LANs based on 802.11b Technology.” 6th International Symposium on Communications Interworking, pages 133-144, October 13-16, 2002.

4. 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

5. 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.

6. M. Klepal, R. Mathur, A. McGibney, and D. Pesch. “Influence of People Shadowing on Optimal Deployment of WLAN Access Points.” IEEE Vehicular Technology Conference, pages 4516-4520, 2004.

7. S. Gordon and A. Dadej. “Design of High Capacity Wireless LANs based on 802.11b Technology.” 6th International Symposium on Communications Interworking, pages 133-144, October 13-16, 2002.

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Questions?