Client-Centric Strategies for dealing with Interference and Congestion in IEEE 802.11 Wireless Networks - PowerPoint PPT Presentation

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Client-Centric Strategies for dealing with Interference and Congestion in IEEE 802.11 Wireless Networks

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Title: Client-Centric Strategies for dealing with Interference and Congestion in IEEE 802.11 Wireless Networks By: Udayan Das Adviser: Cynthia Hood – PowerPoint PPT presentation

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Title: Client-Centric Strategies for dealing with Interference and Congestion in IEEE 802.11 Wireless Networks


1
  • Client-Centric Strategies for dealing with
    Interference and Congestion in IEEE 802.11
    Wireless Networks
  • By Udayan Das
  • Adviser Cynthia Hood

2
Overview
  • Introduction Wireless Background
  • Related Work / Motivation
  • Detecting Interference Experimental Work
  • Ongoing / Future Work
  • Mitigating Interference
  • Conclusions

3
Introduction - Wireless
  • Popularity of Wireless Devices especially ones
    based on IEEE 802.11 Suite of Protocols.
  • IEEE 802.11
  • In unlicensed 2.4-GHz ISM Band (802.11b/g) and
    unlicensed ISM/UNII Band (802.11a) therefore
    there is the problem of interference from other
    devices
  • Shared Channel BW Contention-Based mechanism
    so there is the problem of Congestion.
  • Terminology Stations/Nodes/Clients, APs, BSS...

4
Introduction - Interference
  • Problem Number of different devices use the
    unlicensed Bands
  • Ex Bluetooth devices, ZigBee devices, Cordless
    Phones, Wireless Mice Keyboards, Baby Monitors
    etc.
  • Problem Other devices release unwanted radiation
    in the Bands
  • Ex Microwave.

5
Related Work
  • Wireless Monitoring Li et al 2, Yeo et al 3,
    Henderson/Kotz 4 discuss Tools and Techniques
    HW, SW, Basic Issues.
  • Monitoring Case Studies Yeo et al 5 6,
    Kotz/Essein 7 Balachandran et al 8 discuss
    monitoring experiments in Public wireless LANs
    such as a campus LAN.

6
Related Work
  • Effect of wireless variability on Higher Layers
    Li et al 9 and Vacirca/Cuomo 10.
  • Effect on TCP Subramaniam et al 11 discuss
    using Simulation the effect of Interference on
    TCP.
  • Interference Bluetooth etc Golmie et al 12
    13 discuss interference effects theoretically.

7
Related Work / Motivation
  • The effect of Interference has not been studied
    in detail.
  • Effects on Higher Layer Performance
  • Detecting Interference
  • Gummadi et al 14 has experimental work on
    interference and also discusses Mitigation
  • Similar to our work
  • Differences in methods used Interference
    Sources etc.
  • Mitigation Methods not practical

8
Motivation
  • To show experimentally the effect of Interference
    interference can be detected
  • Once detected, we need to devise simple methods
    to counter it's negative effects.
  • Quick Easy Implementation
  • Wide-spread deployment (acceptance)
  • Limited or No Change to IEEE 802.11 Standards
  • Intuitively, moving to a different channel is the
    best approach, and we propose methods to do this
    in a simple manner looking at the problem from
    a client's perspective.

9
Interference - Detection
  • Conducted a series of experiments to demonstrate
    the effect of interference on Wireless Network
    Performance
  • Effect on Higher Layer Protocol (UDP/TCP)
    performance
  • How does degradation occur? is it linear? Etc
  • What can we use to categorically say that
    interference exists on the channel?

10
Interference Detection - UDP
  • Experimental Set-up

11
Interference Detection - UDP
  • Experimental Set-up
  • Ad-Hoc connection between two laptops using
    channel 6 2.437 GHz.
  • UDP Packet Generator which constantly sends UDP
    packets to the receiver. Collect packet traces at
    both ends (using Ethereal).
  • Introduce Interference (Sine Wave from Wave
    Generator) at
  • center of Channel 6
  • center of Channel 5 (2.432 GHz) Adjacent
    Channel
  • center of Channel 4 (2.427 GHz) Edge of Channel
    6
  • Similar experiment with TCP (Video Traffic).

12
UDP - Results
13
UDP - Results
14
UDP - Results
15
UDP Results
16
UDP - Results
17
UDP - Results
18
TCP - Results
19
Results - Analysis
  • Clearly, the performance degradation is not
    linear with increasing interference.
  • After -50-dBm we see rapid degradation in
    performance.
  • This degradation alone cannot be used to identify
    interference, as this may have been caused by
    congestion.
  • Degradation is more rapid for UDP throughput, and
    for MAC-Layer Information ACK Drop Rate.
  • BUT it doesn't matter what causes performance
    degradation Interference / Congestion.

20
Results Analysis Conclusion
  • We have observed that beyond -50dBm
  • connection shows a susceptibility to break-down.
  • In fact, at -45dBm connection does not remain
    alive for entire trace period.
  • We observed the same behavior for TCP.
  • Break-down of connection is the best indicator
    of interference!
  • Comparison with Gummadi et al 14
  • Similar performance degradation (at different
    power levels)
  • No effect of Adjacent Channel PRISM Interferer
  • Do not mention connection breakdown

21
Mitigation
  • Basic Philosophy Moving to a different
  • Channel is best.
  • Re-association decision Find a new channel/AP to
    associate to-
  • Without cooperation from AP
  • With cooperation from AP
  • Packet Tracing will be used again to estimate
    channel conditions
  • Then a selection is made based on maximum
    available bandwidth
  • Usually choices are available

22
Mitigation Typical Scenario
  • Choices are available!
  • About 60 APs

23
Ongoing WorkMitigation - Un-cooperated
  • Method
  • Collect channel state information by doing a
    passive scan for 5 seconds, less (1-second as
    above) when running time-sensitive applications
    such as audio.
  • Calculate per channel usage by adding the DATA
    column for all APs on a particular channel.
  • Select an AP on the least utilized channel after
    yielding to AP selection (preferred network)
    policy.
  • Select an AP with the highest available signal
    strength among the possible candidates.

24
Ongoing WorkMitigation - Un-cooperated
  • Packet Tracing example using Kismet.

25
Ongoing WorkMitigation - Un-cooperated
  • Example
  • Channel 1 Clients 0 BW Usage 0.
  • Channel 6 Clients 4 BW Usage 29.5 Kbps.
  • Channel 11 Clients 0 BW Usage 0.
  • Channel 1 or 11 is a better option than Channel
    6.
  • However, channel 6 has most APs, and considering
    an AP policy (ex IIT) channel 6 will still be
    selected channel 6 usage is still low.

26
Future WorkMitigation Cooperation from AP
  • AP records information on Network state
  • Channel Utilization
  • Percentage Traffic Audio, Video and Data
  • This information is broadcast in BEACON frame
  • Method
  • Same as before, but calculations are based on AP
    advertised information

27
Future WorkMitigation Cooperation from AP
  • Benefit
  • Beacons are used, upto 5 Beacons can be used, the
    period is less than 1 second.
  • On the other hand, it gives a more long term view
    of network state because AP information is time
    averaged.
  • Therefore recent changes in Network State will
    have less effect.
  • Better to have Pessimistic Averaging scheme

28
Conclusions
  • Demonstrated effect of Interference
    experimentally
  • Switching to a different channel is the best way
    to Mitigate interference and congestion
  • Packet Tracing can be used to make association
    decisions after interference/congestion has been
    detected

29
Contributions
  • Experimental study of the effect of
    interference on higher layer performance
  • Demonstrating how Packet-Tracing can be used to
    estimate Network/Channel State
  • This can be used in making association decisions
  • Publication DySpan 2007 Client Channel
    Selection for Optimal Capacity in IEEE 802.11
    Wireless Networks. with J.T. MacDonald D.
    Roberson
  • Follow-Up Paper to be submitted to DySpan '08

30
  • Questions?

31
References
  1. J. T. MacDonald, U. Das, and D. A. Roberson,
    Client Channel Selection for Optimal Capacity in
    IEEE 802.11 Wireless Networks. In proceedings of
    the IEEE International Symposium on Dynamic
    Spectrum Access Networks (DySpan 2007), Dublin,
    Ireland, April 2007.
  2. F. Li, M. Li, R. Lu, H. Wu, M. Claypool, and R.
    Kinicki, Tools and Techniques for Measurement of
    IEEE 802.11 Wireless Networks. In Proceedings of
    the Second International Workshop On Wireless
    Network Measurement (WiNMee), Boston, MA, USA,
    April 2006
  3. J. Yeo, S. Banerjee and A. Agrawala. Measuring
    Traffic on the Wireless Medium Experience and
    Pitfalls. CS-TR 4421. Department of Computer
    Science, University of Maryland, Wise04.
  4. T. Henderson and D. Kotz. Measuring Wireless
    LANs. In R. Shorey, A. L. Ananda, M. C. Chan,
    and W. T. Ooi, editors, Mobile, Wireless and
    Sensor Networks Technology Applications and
    Future Directions, pages 527. New York, NY,
    2006.
  5. J. Yeo, M. Youssef, and A. Agrawala, A Framework
    for Wireless LAN Monitoring and its
    Applications.'' in ACM Workshop on Wireless
    Security (WiSe 2004) in conjunction with ACM
    MobiCom 2004, Philadelphia, PA, USA, Oct. 2004.

32
References
  1. J. Yeo , M. Youssef , T. Henderson , A. Agrawala,
    An Accurate Technique for Measuring the Wireless
    Side of Wireless Networks. Papers presented at
    the 2005 workshop on Wireless traffic
    measurements and modeling, p.13-18, June 05-05,
    2005, Seattle, Washington.
  2. D. Kotz , K. Essien, Analysis of a Campus-wide
    Wireless Network. Proceedings of the 8th annual
    international conference on Mobile computing and
    networking, September 23-28, 2002, Atlanta,
    Georgia, USA.
  3. A. Balachandran , G. M. Voelker , P. Bahl , P. V.
    Rangan, Characterizing User Behavior and Network
    Performance in a Public Wireless LAN.
    Proceedings of the 2002 ACM SIGMETRICS
    international conference on Measurement and
    modeling of computer systems, June 15-19, 2002,
    Marina Del Rey, California
  4. F. Li, J. Chung, M. Li, H. Wu, M. Claypool, and
    R. Kinicki, Application, Network and Link Layer
    Measurements of Streaming Video over a Wireless
    Campus Network.''Proceedings of the 6th Passive
    and Active Measurement Workshop (PAM), Boston,
    Massachusetts, USA, Apr. 2005
  5. F. Vacirca, and F. Cuomo, Experimental Results
    on the Support of TCP over 802.11b An Insight
    into Fairness Issues. WONS 2006.

33
References
  1. V. Subramaniam, K. K. Ramakrishnan, S.
    Kalyanaram, and L. Ji, Impact of Interference
    and Capture Effects in 802.11 Wireless Networks
    on TCP. Proceedings of the second international
    workshop on Wireless traffic measurements and
    modeling, 2006
  2. N. Golmie, R.E.V. Dyck, A. Soltanin, A.
    Tonnerrre, and O. Rebala, Interference
    Evaluation of Bluetooth and IEEE 802.11b
    Systems. Wireless Networks, 9(3)201211, 2003.
  3. N. Golmie and F. Mouveaux. Interference in the
    2.4 GHz ISM Band Impact on the Bluetooth Access
    Control Performance. In ICC, Helsinki, June
    2001.
  4. R. Gummadi, D. Wetherall, B. Greenstein, S.
    Seshan, Understanding and Mitigating the Impact
    of RF Interference on 802.11 Networks. In
    Proceedings of the ACM SIGCOMM 2007, Kyoto,
    Japan, Aug 2007.
  5. A. P. Jardosh, K. N. Ramachandran, K. C.
    Almeroth, and E. M. Belding-Royer,
    Understanding Congestion in IEEE 802.11b
    Wireless Networks.'' In Proceedings of the
    Internet Measurement Conference (IMC), Berkeley,
    CA, USA, Oct 2005.

34
Further Work
  • Focus on Bit-Errors Develop Interference Models
  • Case Studies on Implemented Mitigation Schemes
  • Move to beyond Client-Centric Philosophy
  • When Interference is detected, AP can make
    switching decision and inform Clients through the
    BEACON

35
  • The End
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