WBest: a Bandwidth Estimation Tool for IEEE 802.11 Wireless Networks

1. WBest: a Bandwidth Estimation Tool for IEEE 802.11 Wireless Networks Mingzhe Li, Mark Claypool, and Robert Kinicki {lmz, claypool, rek}@cs.wpi.edu Department of Computer Science, Worcester Polytechnic Institute, Worcester MA, 01609 USA Presented by Feng Li (lif@cs.wpi.edu) 33rd IEEE Conference on Local Computer Networks (LCN), Montreal, Quebec, Canada, October 16th,2008

2. Motivation • Bandwidth estimation techniques focus on network capacity or available bandwidth. • Most bandwidth estimation involved only wired networks. • This paper presents a new Wireless Bandwidth estimation tool, WBest, designed for fast, non-intrusive, accurate estimation of available bandwidth over wireless LANs. LCN08 – October 16th, Montreal, Quebec, Canada

3. Challenges on Bandwidth Estimation • Traditional approaches. (e.g. pathChirp v2.4.1 [Ribeiro 2003], pathload v1.3.2 [Jain 2003] etc.) • Designed for precisely estimate the bandwidth in wired networks. • Converge based on searching algorithms. • Provide limited bandwidth information. • Impacted by wireless networks. (e.g. shared media, retransmission, interference etc), • Inaccurate results. • Long estimation time. • High intrusiveness. LCN08 – October 16th, Montreal, Quebec, Canada

4. Capacity Estimation with Packet Dispersion Bottleneck router L : Packet size Ci: Bottleneck capacity ∆in: Initial gap ∆out: Dispersed gap LCN08 – October 16th, Montreal, Quebec, Canada

5. Example: Packet Dispersion with Wireless Contention Probing traffic Contending traffic / Co-channel interference LCN08 – October 16th, Montreal, Quebec, Canada

6. Outline • Motivation and Backgrounds • WBest Algorithm • Evaluation Experiments • Result Analysis • Conclusions LCN08 – October 16th, Montreal, Quebec, Canada

7. Terminology • Effective Capacity (Ce) • Maximum possible bandwidth that a link or end-to-end path can deliver. • Available Bandwidth (A ) • Maximum unused bandwidth at a link or end-to-end path in a network. • Typically, it is a time-varying metric. LCN08 – October 16th, Montreal, Quebec, Canada

8. Wireless Bandwidth EstimationTool(WBest) • Objective • Fast, low intrusiveness, adequately accurate estimation of available bandwidth and variance of bandwidth in wireless networks. • Two-step algorithm • Packet pair technique to estimate effective capacity (Ce) of wireless network. • Packet train technique to estimate mean and standard deviation of available bandwidth (A). LCN08 – October 16th, Montreal, Quebec, Canada

9. WBest Assumptions • Assume last hop wireless network (hth hop) is bottleneck link with a single FCFS queue and: • Assume no significant changes in network conditions between two steps (estimating Ceand A). LCN08 – October 16th, Montreal, Quebec, Canada

10. Estimating Effective Capacity (Ce) • Send n packet pairs to estimate Ce: • Ti : dispersion time of ith packet pair (seconds), • L : packet size (bytes). • Use median of n estimations to minimize impacts of crossing and contending traffic. LCN08 – October 16th, Montreal, Quebec, Canada

11. Estimating Available Bandwidth (A) • A packet train of m packets is sent at effective capacity (Ce) to estimate available bandwidth (A). • FCFS queuing at AP. • R : dispersion rate S : crossing/contending traffic • S’ : reduced crossing/contending traffic • Estimate contending and crossing traffic (S) using dispersion rate (R) LCN08 – October 16th, Montreal, Quebec, Canada

12. Estimating Available Bandwidth (A) (cont’d) • Mean available bandwidth (A). Fig 3 Estimating Available Bandwidth using Average Dispersion Rate (R). LCN08 – October 16th, Montreal, Quebec, Canada

13. WBest Algorithm 1st Phase Calculating Ce n = 30 m = 30 2nd Phase Calculating A ErrorCorrection LCN08 – October 16th, Montreal, Quebec, Canada

14. Outline • Motivation and Background • WBest Algorithm • Evaluation Experiments • Result Analysis • Conclusions LCN08 – October 16th, Montreal, Quebec, Canada

15. Evaluation Setup Client C • Build testbed • Open source drivers • Wireless sniffer • Various wireless conditions • Traffic load • Power saving mode • Rate adaptation • Implementation of WBest • Compare with: • IGI/PTR v2.0 [Hu 2003] (PGM/PRM) • pathChirp v2.4.1 [Ribeiro 2003] (PRM) • pathload v1.3.2 [Jain 2003] (PRM) LCN08 – October 16th, Montreal, Quebec, Canada

16. Experiment Design • 14 cases were designed to evaluate four bandwidth estimation tools under different network conditions. • Each of 14 cases were repeated 30 times. • All clients were placed with pre-selected locations with RSSI range between -38 and -42 dBm. • All experiments were run during summer break to eliminate effects from occasional wireless activities. LCN08 – October 16th, Montreal, Quebec, Canada

17. Result-Convergence Time vs. Error LCN08 – October 16th, Montreal, Quebec, Canada

18. Result-Intrusiveness vs. Error LCN08 – October 16th, Montreal, Quebec, Canada

19. Future Work • Apply WBest to multimedia streaming applications to improve media performance and playout buffer optimization on wireless networks. • Evaluate WBest performance under more complex wireless environments. • Enhance WBest robustness during AP queue overflow. • Develop new metric to replace Available Bandwidth (A) when TCP flows involved. LCN08 – October 16th, Montreal, Quebec, Canada

20. Conclusions • Current bandwidth estimation tools are significantly impacted by wireless network conditions, such as contention or rate adaptations. • Current tools are generally impractical for applications such as streaming multimedia that require fast, accurate and low intrusive bandwidth estimation. • WBest consistently provides fast available bandwidth estimation, with generally more accurate estimates and lower intrusiveness under all conditions evaluated. LCN08 – October 16th, Montreal, Quebec, Canada

21. Question ? • WBest with source code is available at: http://perform.wpi.edu/downloads/#wbest LCN08 – October 16th, Montreal, Quebec, Canada

22. Thank You! WBest: a Bandwidth Estimation Tool for IEEE 802.11 Wireless Networks Mingzhe Li, Mark Claypool, and Robert Kinicki {lmz, claypool, rek}@cs.wpi.edu Department of Computer Science, Worcester Polytechnic Institute, Worcester MA, 01609 USA Presented by Feng Li (lif@cs.wpi.edu) LCN08 – October 16th, Montreal, Quebec, Canada

23. Reference • [Hu 2003] Ningning Hu and Peter Steenkiste, “Evaluation and characterization of available bandwidth probing techniques,” IEEE Journal on Selected Areas in Communications, vol. 21, no. 6, Aug. 2003. • [Ribeiro 2003] V. Ribeiro, R. Riedi, R. Baraniuk, J. Navratil, and L. Cottrell, “pathchirp: Efficient available bandwidth estimation for network paths,” in PAM ’03, La Jolla, CA, USA, Apr. 2003. • [Jain 2003] Manish Jain and Constantinos Dovrolis, “End-to-end available bandwidth: Measurement methodology, dynamics, and relation with tcp throughput,” IEEE/ACM Transactions in Networking, , no. 295-308, Aug. 2003. LCN08 – October 16th, Montreal, Quebec, Canada

24. Analysis of Number of Packet Pairs LCN08 – October 16th, Montreal, Quebec, Canada

25. Analysis of Length of Packet Train LCN08 – October 16th, Montreal, Quebec, Canada