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Packet Dispersion in IEEE 802.11 Wireless Networks

Packet Dispersion in IEEE 802.11 Wireless Networks. Mingzhe Li, Mark Claypool and Bob Kinicki WPI Computer Science Department Worcester, MA 01609 rek@cs.wpi.edu. Second International Workshop on Performance and Management of Wireless Local Area Networks (P2MNet)

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Packet Dispersion in IEEE 802.11 Wireless Networks

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  1. Packet Dispersion inIEEE 802.11Wireless Networks Mingzhe Li, Mark Claypool and Bob Kinicki WPI Computer Science Department Worcester, MA 01609 rek@cs.wpi.edu Second International Workshop on Performance and Management of Wireless Local Area Networks (P2MNet) Tampa, Florida, November 14, 2006

  2. Outline • Introduction • Packet Dispersion in WLANs • WLAN Packet Dispersion Model • Model Validation • Model Analysis • Conclusions P2MNet Workshop November 14, 2006

  3. Introduction • Bandwidth estimation techniques focus on network capacity or available bandwidth. • Most bandwidth estimation has involved only wired networks. • This paper focuses on packet dispersion in wireless LANs (WLANs). P2MNet Workshop November 14, 2006

  4. Outline • Introduction • Packet Dispersion in WLANs • WLAN Packet Dispersion Model • Model Validation • Model Analysis • Conclusions P2MNet Workshop November 14, 2006

  5. Packet Dispersion Techniques • Packet pair dispersion • two equal-sized packets are sent back-to-back through the network. • Packet train dispersion • multiple back-to-back probe packets are sent through the network. P2MNet Workshop November 14, 2006

  6. Packet Pair Dispersion narrow link P2MNet Workshop November 14, 2006

  7. NS-2 Additionsto Model WLANs • Receiver Based Auto Rate (RBAR) module was re-implemented in NS 2.27 to model 802.11 dynamic rate adaptation [ Sadeghi et al.] • An NS-2 extension to model Rayleigh fading was implemented [Ratish et al.] P2MNet Workshop November 14, 2006

  8. Wireless Rate Adaptationunder Rayleigh Fading NS-2 simulation results P2MNet Workshop November 14, 2006

  9. Wireless Traffic Classification • Probing traffic • Packet pairs or trains sent downstream through the AP to the wireless client. • Crossing traffic • Downstream traffic going through the AP to other wireless clients. • Contending traffic • Upstream traffic that accesses the shard wireless channel and competes with probe packets on the estimated path. P2MNet Workshop November 14, 2006

  10. Wireless Traffic Classification P2MNet Workshop November 14, 2006

  11. WLAN Packet Dispersion Issues • Wireless frame retries • increase the packet delay variance that produce packet dispersion inconsistencies. • Dynamic Rate Adaptation • Fading channel • Noisy wireless channel - BER • Contending Traffic P2MNet Workshop November 14, 2006

  12. Simulated Wireless Effects on Bandwidth Estimation • CDF represents 1000 • packet-pair estimates • 1000-byte probe packets • and CBR contending packets • Contending traffic = 1Mbps • upstream flow P2MNet Workshop November 14, 2006

  13. Outline • Introduction • Packet Dispersion in WLANs • WLAN Packet Dispersion Model • Model Validation • Model Analysis • Conclusions P2MNet Workshop November 14, 2006

  14. WLAN Packet Dispersion Model Assumptions Bottleneck link is the WLAN last hop. No crossing traffic. • Dispersion, T, between two packets in a packet pair is characterized in terms of E[T] and V[T] for a WLAN that includes: packet size, link data rate, BER and access methods (base or RTS/CTS). • While wireless channel conditions can be characterized by received signal strength indicator (RSSI), SNR and BER, our simplified model assumes these other factors impact BER. • The impact of channel conditions on bandwidth estimation is evaluated via V[T], the packet dispersion variance. P2MNet Workshop November 14, 2006

  15. WLAN Packet Dispersion Model • From previous 802.11 models, we build a new model for wireless packet dispersion where dispersion is defined as the delay between the arrival times of the first and second packets in the packet pair. • Thus, the model must include the delay before the transmission of the second packet, E[D], and the time to transmit it, Ts, and dispersion is: E[T] = E[D] + Ts P2MNet Workshop November 14, 2006

  16. WLAN Packet Dispersion Model • Since E[D] depends on the wireless link rate, Cl , the average packet size, L and the number of nodes in the contention domain, n, we have E[D] = d (Cl, L, n) • Similarly, for the transmission time, Ts = ts (Cl, L) P2MNet Workshop November 14, 2006

  17. Bandwidth Estimate • Defining, Cest, as the bandwidth estimate based on the wireless packet pair dispersion model, our model is defined by: P2MNet Workshop November 14, 2006

  18. Outline • Introduction • Packet Dispersion in WLANs • WLAN Packet Dispersion Model • Model Validation • Model Analysis • Conclusions P2MNet Workshop November 14, 2006

  19. Model Validation • Validation results include an ideal WLAN and a scenario with contention and BER. • Ideal validation includes NS-2 simulations, analytic model and actual measurements. P2MNet Workshop November 14, 2006

  20. Ideal WLAN Scenario The ideal scenario consists of an AP with a single wireless client for both basic (BAS) and RTS/CTS access methods. Simulations: 500 pairs Measurements: 100 pairs P2MNet Workshop November 14, 2006

  21. Model Validation Random Model Simulation Parameters Topology P2MNet Workshop November 14, 2006

  22. Models with Contention and Wireless Transmission Errors Errors in the Bandwidth Estimation Model Compared with Simulations Error Free BER = 10-5 P2MNet Workshop November 14, 2006

  23. Outline • Introduction • Packet Dispersion in WLANs • WLAN Packet Dispersion Model • Model Validation • Model Analysis • Conclusions P2MNet Workshop November 14, 2006

  24. Model Analysis • In a non-saturated WLAN with low BER, low contention, packet-pair dispersion estimates the maximal channel capacity, effective capacity, Ce . • With considerable contending traffic and/or BER, the dispersion metric is referred to as the achievable throughput, At , for the current level of contending traffic. P2MNet Workshop November 14, 2006

  25. Model Analysis • Effective Capacity • Achievable Bandwidth • Relationship with Available Bandwidth P2MNet Workshop November 14, 2006

  26. Achievable Throughput P2MNet Workshop November 14, 2006

  27. Impact of Channel Rateon Effective Capacity P2MNet Workshop November 14, 2006

  28. Impact of BER on Achievable Throughput Five node, BAS wireless network with 1500-byte packets no achievable throughput P2MNet Workshop November 14, 2006

  29. Impact of RTS/CTSon Achievable Throughput Model Results for Wireless Networks with 1500 Byte Packets P2MNet Workshop November 14, 2006

  30. Standard Deviation of Achievable Throughput P2MNet Workshop November 14, 2006

  31. Packet Size Effect onStandard Deviation ofBandwidth Estimations Five node, BAS wireless network with 1500-byte packets P2MNet Workshop November 14, 2006

  32. Impact of Channel Rateon Standard Deviation of Bandwidth Estimations P2MNet Workshop November 14, 2006

  33. Impact of BER on Standard Deviation of Bandwidth Estimations P2MNet Workshop November 14, 2006

  34. Outline • Introduction • Packet Dispersion in WLANs • WLAN Packet Dispersion Model • Model Validation • Model Analysis • Conclusions P2MNet Workshop November 14, 2006

  35. Conclusions • Packet dispersion measures the effective capacity and the achievable throughput of a wireless network instead of the capacity as in a wired network. • Wireless channel conditions, such as BER and RTS/CTS access method impact the bandwidth estimation results and the variance of the results. P2MNet Workshop November 14, 2006

  36. Thank You !! Packet Dispersion inIEEE 802.11Wireless Networks Mingzhe Li, Mark Claypool and Bob Kinicki WPI Computer Science Department Worcester, MA 01609 rek@cs.wpi.edu http://web.cs.wpi.edu/~rek/ Second International Workshop on Performance and Management of Wireless Local Area Networks (P2MNet) Tampa, Florida, November 14, 2006

  37. P2MNet Workshop November 14, 2006

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