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MDG: Measurement-Driven Guidelines for 802.11 WLAN Design

MDG: Measurement-Driven Guidelines for 802.11 WLAN Design. Ioannis Broustis, Konstantina Papagiannaki, Srikanth V. Krishnamurthy, Michalis Faloutsos, Vivek Mhatre ACM MOBICOM 2007. Goal: Improve WLAN network performance. Three functions to improve network performance in dense WLANs

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MDG: Measurement-Driven Guidelines for 802.11 WLAN Design

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  1. MDG: Measurement-Driven Guidelines for802.11 WLAN Design Ioannis Broustis, Konstantina Papagiannaki, Srikanth V. Krishnamurthy, Michalis Faloutsos, Vivek Mhatre ACM MOBICOM 2007

  2. Goal: Improve WLAN network performance • Three functions to improve network performance in dense WLANs • Frequency selection • Provides spatial separation between interfering APs • User association • Provides load balancing among APs • Power control • APs shrink their cells to facilitate higher spatial reuse of spectrum

  3. AP AP Frequency Selection • Neighbor Access Points (APs) select different frequencies in order to mitigate interference from each other Cell of B Cell of A Channel 6 Channel 11 B A AP AP Channel 6 Channel 6 Inter-cell Contention: A cannot transmit because B is transmitting

  4. User Association • Users select less-loaded Access Points (APs) in order to get more throughput A B AP AP C

  5. Power Control • APs shrink their overlapping cells in order to reduce interference and improve spatial reuse A B AP AP

  6. Problem statement • Which are the functions that should be applied in a specific scenario? • In what sequence should they be applied? High level objective: to maximize a fair notion of aggregate network throughput

  7. Previous Work • Most studies have tried to optimize one of these functions • No studies on the interdependencies between allthree functions • A. Mishra, V. Shrivastava, D. Agarwal, S. Banerjee. Distributed Channel Management in Uncoordinated Wireless Environments. MOBICOM 2006. • N. Ahmed, S. Keshav. SMARTA: A Self-Managing Architecture for Thin Access Points. CoNEXT 2006. • K. Sundaresan, K. Papagiannaki. The Need for Cross-Layer Information in Access Point Selection Algorithms. IMC 2006. • A. Mishra, V. Brik, S. Banerjee, A. Srinivasan, W. Arbaugh. A Client-Driven Approach for Channel Management in Wireless LANs. INFOCOM 2006. • A. Kumar, V. Kumar. Optimal Association of Stations and APs in an IEEE 802.11 WLAN. NCC 2005. • T. Korakis, O. Ercetin, S. V. Krishnamurthy, L. Tassiulas, S. Tripathi. Link Quality Based Association Mechanism in IEEE 802.11h Compliant Wireless LANs. RAWNET 2005. • B. Leung, K. Kim. Frequency Assignment for IEEE 802.11 Wireless Networks. VTC 2003. • Y. Bejerano, S. Han, L. Li. Fairness and Load Balancing in Wireless LANs Using Association Control. • MOBICOM 2004.

  8. Contribution • We perform an extensive experimental study on Testbed-A • We quantify the interplay of the three functions • We employ 3 previously proposed algorithms for these functions • We identify the conditions which make the topology conducive to each one of these functions • We develop the MDG framework (Measurement Driven Guidelines) • We validate the effectiveness of MDG on a different Testbed-B! • Testbed-B is significantly different from Testbed-A • We observe that MDG provides the best strategy in all cases

  9. The Structure of This Talk • Background on the 3 algorithms • Part 1. Experimental Study on Testbed-A - Derivation of conditions • Part 2. Building the MDG framework • Part 3. Validating MDG on Testbed-B

  10. Our choice for the algorithms • All 3 algorithms based on Gibbs sampling • Fully-saturated downlink traffic • Frequency selection algorithm (FS) [Kauffmann et al. ‘07] • Finds the channel allocation with minimum total interference • User Association Algorithm (UA) [Kauffmann et al. ‘07] • Finds the state of minimal potential delay of clients • Depends on AP channel access time, AP-client link quality and number of clients per AP • Power Control algorithm (PC) [Mhatre et al. ‘07] • Finds the state of minimal potential delay by jointly tuning PTXand Clear Channel Assessment threshold (CCA) [1] B. Kauffmann et al. “Measurement-Based Self Organization of Interfering 802.11 Wireless Access Networks”. INFOCOM 2007 [2] V. Mhatre, K. Papagiannaki, F. Baccelli. “Interference Mitigation through Power Control in High Density 802.11 WLANs”. INFOCOM 2007

  11. Algorithmic requirements • The Access Points (APs): • Measure: channel power, load etc • Exchange: information with other APs • Advertise: information to the clients • We require minimal functionality from the client • Clients tune their Tx power, CCA threshold • Clients pick Access Point (AP) for association as per the optimization criteria

  12. Implementation and Experimental set-up • The 3 algorithms are implemented • for both APs and clients • on Intel 2915 prototype driver and firmware • Testbed A : U Cambridge, UK • 21 APs, 30 client • Technical Characteristics • Nodes: Soekris net4826, • Wireless cards: Intel 2915 a/b/g • 5-dBi omnidirectional antennae • Experiments late at night, to avoid external interference • Both in 802.11a and 802.11g

  13. Experiments at a glance • We study each function in isolation • To understand the capabilities of each • We study all pairwise combinations • To undestand how each affects the other • We study the effect of all three of them • Methodology • Activate APs and clients in random order • Apply the algorithms • Run throughput measurements to observe gain due to each combination

  14. Frequency Selection (FS) in isolation • Should we always apply FS? • FS is always beneficial • FS outperforms Random Channel Selection (RCS) by 48% in 802.11a and by 65% in 802.11g

  15. User Assoc. (UA) in isolation • We observe that the performance due to UAis largely dependent on the level of contention • If the contention among APs is high, there is notmuch for clients to gain • Less contention = more throughput due to UA, when AP load is not balanced • Contention is lower in 802.11a than in 802.11g • UA is more favorable in 802.11a than in 802.11g

  16. User Assoc. (UA) and Freq. Selection (FS) • We apply FS before UA • The combination of UA and FS is always beneficial! • The total network throughput becomes higher than the sum of throughputs in the isolated cases! • Much more in 802.11a than in 802.11g

  17. Power Control helps in some scenarios • How does topology affect the ability of PC to shrink cells? • Five topological cases • Cases where PC improves performance • Case a • AP-client link strong (RSSI>-55 dBm) • AP-AP link weaker by at least k dBm (k = 15 to 20) • Case b • Both AP-AP and AP-client links strong (RSSI>-55 dBm) • Reduction in power not feasible • Increasing CCA makes APs ignore each others’ transmissions --> parallel transmissions possible

  18. Power Control does not always help! • Cases where PC has no effect • Case c • AP-AP link stronger than AP-client link • Isolation is not possible • Case d • AP-client weak and AP-AP evenweaker • Power reduction reduces the AP-client link quality • With CCA increment, AP is disconnected from client • Case e • AP-client link stronger by k dBm than AP-AP link, k < 15 dBm • No cell isolation is possible

  19. Power control (PC) and Frequency Selection (FS) • PC usually does not provide benefits without FS • Many co-channel links under cases (c) and (e) • With FS, remaining co-channel APs have reduced AP-AP link qualities • FS + PC is more beneficial in 802.11g than in 802.11a • After FS there is still significant contention in 802.11g, due to fewer channels

  20. Power Control (PC) and User Association (UA) • PC in conjunction with UA, is usually not beneficial without FS! • UA may create long AP-client links • As long as a user discovers a lightly loaded AP that is going to provide lower delays, the client will associate to that AP • This reduces the AP-client link quality (RSSI) even more AP AP

  21. Applying all 3 functions • Blindly applying all three algorithms may hurt the performance ! 24% throughput degradation when applying all 3 algorithms!!

  22. The need for a systematic approach • We develop MDG (Measurement Driven Guidelines) • A framework for deciding when to apply each function • Based on the empirical observations • Measurement-based inputs: • Whether overlapping cells exist, so as to apply FS • Whether overloaded APs exist, so as to apply UA • Whether AP-AP and AP-client links are conducive for PC • Intuitively, MDG: • First mitigates interference • Second balances the load

  23. Building MDG • Initial steps: • 1. Check if FS is beneficial • 2. If not, check if UA is beneficial

  24. Checking for contention after FS • If FS resolves all interference, PC is not needed • If after FS there still exists contention among APs, then further steps depend upon whether the network employs 802.11a or 802.11g.

  25. 802.11a: UA or PC ? • In 802.11a, FS+UA is more beneficial than FS+PC • Applying FS almost eliminates cell overlaps • When contention is limited, it is preferable to apply UA rather than PC

  26. 802.11g: UA or PC ? • In 802.11g, FS+PC is more beneficial than FS+UA • FS does not eliminate cell overlaps, due to the limited number of channels • FS+PC boosts the network performance

  27. MDG: The Final Flow Diagram

  28. So… • The MDG diagram looks really cool, but does it really work? :-)

  29. Validating MDG on TestBed-B • We validate MDG on a second, different network • UC Riverside Wireless Testbed • Different scale and environmental factors • 8 APs, 20 clients • Validation procedure • Apply MDG • Evaluate the performance

  30. Validating MDG: 802.11a MDG discovers the path that provides the highesttotal network throughput in 802.11a

  31. Validating MDG: 802.11g MDG discovers the path that provides the highesttotal network throughput in 802.11g

  32. Further Testing of MDG Performance • Does external interference affect MDG? • MDG performs well even in the presence of other LANs (during daytime) • MDG is better than any random network configuration tested • Random channel selection • Random client affiliation • Random PTX and CCA, constant C = PTX * CCA MDG provides the best performance, compared to 40 other random configurations

  33. Conclusions • MDG maximizes the synergy between frequency selection, user association and power control • MDG is measurement driven • Relying on the fundamental understanding of the inter-dependencies between the three functions/algorithms • Grounded on conditions that make the topology conducive to each function • We validate the efficiency of MDG on a different network • MDG is useful for network management in WLANs in practice

  34. Thank you! • Questions ?

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