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Packet Dispersion in IEEE 802.11 Wireless Networks Mingzhe Li, Mark Claypool and Bob Kinicki WPI Computer Science Department Worcester, MA 01609

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Presentation on theme: "Packet Dispersion in IEEE 802.11 Wireless Networks Mingzhe Li, Mark Claypool and Bob Kinicki WPI Computer Science Department Worcester, MA 01609"— Presentation transcript:

1 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) Tampa, Florida, November 14, 2006

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

3 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).

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

5 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.

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

7 P2MNet Workshop November 14, 2006 7 NS-2 Additions to 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.]

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

9 P2MNet Workshop November 14, 2006 9 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. Wireless Traffic Classification

10 P2MNet Workshop November 14, 2006 10 Wireless Traffic Classification

11 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

12 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

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

14 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.

15 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, T s, and dispersion is: E[T] = E[D] + T s

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

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

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

19 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.

20 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

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

22 P2MNet Workshop November 14, 2006 22 Models with Contention and Wireless Transmission Errors RTS/CTSBasicRTS/CTSBasic Mean Error 8.05%4.90%9.40%7.67% Standard Deviation 6.72%4.28%5.30%3.82% Errors in the Bandwidth Estimation Model Compared with Simulations Error Free BER = 10 -5

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

24 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, C e. With considerable contending traffic and/or BER, the dispersion metric is referred to as the achievable throughput, A t, for the current level of contending traffic.

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

26 P2MNet Workshop November 14, 2006 26 Achievable Throughput

27 P2MNet Workshop November 14, 2006 27 Impact of Channel Rate on Effective Capacity

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

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

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

31 P2MNet Workshop November 14, 2006 31 Packet Size Effect on Standard Deviation of Bandwidth Estimations Five node, BAS wireless network with 1500-byte packets

32 P2MNet Workshop November 14, 2006 32 Impact of Channel Rate on Standard Deviation of Bandwidth Estimations

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

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

35 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.

36 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 http://web.cs.wpi.edu/~rek/ Second International Workshop on Performance and Management of Wireless Local Area Networks (P2MNet) Tampa, Florida, November 14, 2006 Thank You !!

37 P2MNet Workshop November 14, 2006 37


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