Load-Aware Spectrum Distribution in Wireless LANs

1. Load-Aware Spectrum Distributionin Wireless LANs Thomas Moscibroda, Ranveer Chandra, Yunnan Wu, SudiptaSengupta, ParamvirBahl, Yuan Yuan Microsoft Research ICNP 2008

2. Outline • Introduction • Motivation • Design Approach • Problem Formulation • Algorithms • Evaluation • Conclusions

3. Introduction • In IEEE 802.11, the entire available spectrum is divided into smaller channels of equal channel-width (bandwidth)

4. Introduction

5. Previous Approaches - 1 • Change associations between clients and access points (APs)

6. Previous Approaches - 1 • Change associations between clients and access points (APs)

7. Previous Approaches – 1I • Use transmission powers for load balancing

8. Previous Approaches – 1I • Use transmission powers for load balancing

9. Previous Approaches – III • Coloring: Assign best (least-congested) channel to most-loaded Aps, Reuse some of the channels, weighted coloring

10. Previous Approaches – III • Coloring: Assign best (least-congested) channel to most-loaded Aps, Reuse some of the channels, weighted coloring

11. Spectrum assignment • The problem with existing approaches is fundamental • - Demand at APs very different • - But, every AP assigned the same amount of spectrum! (one 20 MHz channel) • Our approach:

12. Introduction • In this paper, we argue that by moving beyond this fixed channelization structure, the network capacity, spectrum utilization and fairness can be greatly increased • Wider channels for heavily-loaded APs • Narrower channels for lightly-loaded APs

13. Load-Aware Spectrum Allocation • Problem definition: 1) Assignment with optimal spectrum utilization: All spectrum to leafs!

14. Load-Aware Spectrum Allocation • Problem definition: 2) Assignment with Optimal per-load fairness: Every AP gets half the spectrum

15. Problem Definition • AP1, … , APn • Conflict graph G=(V,E) describes which APs interfere • Every APi has a load Li (e.g. #assigned clients) • Spectrum Assignment Problem: Input: 1) AP1,…,APn 2) L1,…,Ln 3) Conflict graph G Output: Assign a channel Ii=[Si, Si+Bi] to every AP

16. Problem Definition

17. Non-Overlapping Channel • Non-interfering assignment: An assignment is non-interfering if the channels of no two neighboring APs overlap. • Why Non-Overlapping? • Lesser contention overhead, no rate anomaly

18. Why is this problem interesting • Traditional channel assignment / frequency assignment problems map to graph coloring problems • We must assign contiguous bands to each node

19. Solution 1: ILP • Problem is clearly NP-hard in general conflict graphs • The problem can be formulated as an ILP

20. Solution 2: Heuristics • 1) Determine an ordering O = (AP1,…,APn) over all APs • 2) For a given R, … a) … assign each node a channel width b) … check whether these (B1,…,Bn) can be feasibly allocated when greedily packed in the order of O • 3) Find largest R, for which greedy packing is feasible (binary search). • We looked at several possible orderings O (most-congested first, smallest-last )

21. Evaluations • Extensive trace-driven simulations using two-data sets: • 1) Small WLAN, monitoring information of 6 APs on floor at MSR • 2) Large WLAN, 177 APs in 3 buildings [Balazinska, Castro, Mobisys 2003]

22. Evaluations

23. Conclusions • Adaptive Channel Width • Simple technology (deployable today!) • Provides new knob for optimization • Huge potential for performance improvement!