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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

MDG: Measurement-Driven Guidelines for802.11 WLAN Design

Ioannis Broustis, Konstantina Papagiannaki, Srikanth V. Krishnamurthy,

Michalis Faloutsos, Vivek Mhatre

ACM MOBICOM 2007

goal improve wlan network performance
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
frequency selection

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

user association
User Association
  • Users select less-loaded Access Points (APs) in order to get more throughput

A

B

AP

AP

C

power control
Power Control
  • APs shrink their overlapping cells in order to reduce interference and improve spatial reuse

A

B

AP

AP

problem statement
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

previous work
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.
contribution
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
the structure of this talk
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
our choice for the algorithms
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

algorithmic requirements
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
implementation and experimental set up
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
experiments at a glance
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
frequency selection fs in isolation
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
user assoc ua in isolation
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
user assoc ua and freq selection fs
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
power control helps in some scenarios
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
power control does not always help
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
power control pc and frequency selection fs
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
power control pc and user association ua
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

applying all 3 functions
Applying all 3 functions
  • Blindly applying all three algorithms may hurt the performance !

24% throughput degradation

when applying all 3 algorithms!!

the need for a systematic approach
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
building mdg
Building MDG
  • Initial steps:
  • 1. Check if FS is beneficial
  • 2. If not, check if UA is beneficial
checking for contention after fs
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.
802 11a ua or pc
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
802 11g ua or pc
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
slide28
So…
  • The MDG diagram looks really cool, but does it really work? :-)
validating mdg on testbed b
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
validating mdg 802 11a
Validating MDG: 802.11a

MDG discovers the path that provides the highesttotal network throughput in 802.11a

validating mdg 802 11g
Validating MDG: 802.11g

MDG discovers the path that provides the highesttotal network throughput in 802.11g

further testing of mdg performance
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

conclusions
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
thank you
Thank you!
  • Questions ?
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