Self-organized Wireless Access Networks (SWAN)

Project Description

The increased popularity of IEEE 802.11 WLANs has led to dense deployments in urban areas. Such high density leads to sub-optimal performance unless the interfering networks learn how to optimally share the spectrum. In this project we look into distributed algorithms that allow (i) multiple interfering 802.11 WLANs to select their operating frequency in a way that minimizes global interference, (ii) clients to choose their Access Point so that the bandwidth of all interfering networks is shared optimally, (iii) APs and clients to select their transmission power and Clear Channel Assessment (CCA) threshold so as to maximize the overall network capacity. The proposed algorithms optimize global network performance based on local information. They do not require explicit coordination among the wireless devices, and can thus operate in diverse environments with no single administrative authority. We study implementation requirements and show that significant benefits can be gained even within incremental deployments and in the presence of non-cooperating wireless clients.

Future steps involve the migration of our self-organization algorithms from the infrastructure wireless LAN space to address self-organization of mesh networks.

Implementation - The SWANnet testbed

Throughout the course of the project we evaluate the performance of the proposed algorithms using two different approaches: (i) Simulations (in Opnet and Qualnet) addressing the performance of the proposed schemes in large scale environments, and (ii) real implementations on the Intel 2915ABG wireless cards.

The proposed functionality has so far been tested in a 80-node testbed deployed across the 3 stories of the William Gates building at University of Cambridge, in a 40 node testbed deployed in the computer science department of University California Riverside (UCR), and in a 60 node testbed deployed in the computer science department of University of Wisconsin in Madison. All testbeds consist of Soekris 4825 nodes with two mini-PCI interfaces hosting the Intel 2915 ABG cards. The wireless NICs implement a proprietary version of the firmware and microcode facilitating the measurement of PHY and MAC layer parameters that cannot be accessed in commercial cards.

Publications

Publications produced by SWAN are the following:

• J. Zhu, X. Guo, S. Roy, and K. Papagiannaki
  CSMA Self-Adaptation based on Interference Differentiation
  To appear in IEEE Globecom, Wireless Networking Symposium, Washington D.C., November, 2007.
  Download: (pdf)
• S. Das, H. Pucha, K. Papagiannaki, and Y. Hu
  Understanding Wireless Routing Link Metric Dynamics
  To appear in ACM Internet Measurement Conference, San Diego, CA, October 2007.
  Download: (pdf)
• N. Ahmed, V. Shrivastava, A. Mishra, S. Banerjee, S. Keshav, and K. Papagiannaki
  Interference Mitigation in Wireless LANs using Speculative Scheduling
  To appear as an extended abstract in ACM Mobicom, Montreal, Canada , September 2007.
  Download: (pdf)
• I. Broustis, K. Papagiannaki, S. Krishnamurthy, M. Faloutsos, and V. Mhatre
  MDG: Measurement-Driven Guidelines for 802.11 WLAN Design
  To appear in ACM Mobicom, Montreal, Canada, September 2007.
  Download: (pdf)
• V. Mhatre, K. Papagiannaki and F. Baccelli
  Interference Mitigation through Power Control in High Density 802.11 WLANs
  To appear in IEEE Infocom, Anchorage, Alaska, May, 2007.
  Download: (pdf)
• B. Kauffmann, F. Baccelli, A. Chaintreau, V. Mhatre, K. Papagiannaki and C. Diot
  Measurement-Based Self Organization of Interfering 802.11 Wireless Access Networks
  To appear in IEEE Infocom, Anchorage, Alaska, May, 2007.
  Download: (pdf)
• V. Mhatre and K. Papagiannaki.
  Optimal Design of High-Density 802.11 WLANs
  In ACM CoNEXT, Lisbon, Portugal, December, 2006.
  Download: (pdf)
• K. Sundaresan and K. Papagiannaki.
  The Need for Cross-Layer Information in Access Point Selection Algorithms
  In ACM Internet Measurement Conference, Rio de Janeiro, Brasil, October, 2006.
  Download: (pdf)

Collaborators

Current collaborators are:

• Nabeel Ahmed, University of Waterloo, Canada
• S. Das, Purdue University
• Suman Banerjee, University of Winsconsin in Madison
• Yannis Broustis, UC Riverside
• M. Faloutsos, UC Riverside
• S. Keshav, University of Wateloo, Canada
• S. Krishnamurthy, UC Riverside
• Y.C. Tay, University of Singapore

Past collaborators are:

• Francois Baccelli, INRIA, ENS, Paris, France
• Augustin Chaintreau, Thomson Research in Paris
• Christophe Diot, Thomson Research in Paris
• Bruno Kauffman, ENS, France
• Vivek Mhatre, Thomson Research in Paris
• Karthikeyan Sundarean, Georgia Tech