Brief Announcement: Distributed Algorithms for Maximum Link Scheduling in the Physical Interference Model

  • Guanhong Pei
  • Anil Kumar S. Vullikanti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7611)


We develop distributed algorithms for the maximum independent link set problem in wireless networks in a distributed computing model based on the physical interference model with SINR constraints — this is more realistic and more challenging than the traditional graph-based models. Our results give the first distributed algorithm for this problem with polylogarithmic running time with a constant factor approximation guarantee, matching the sequential bound.


Wireless Network Virginia Tech Interference Model IEEE INFOCOM Link Diversity 
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  1. 1.
    Goussevskaia, O., Oswald, Y.A., Wattenhofer, R.: Complexity in geometric sinr. In: ACM MobiHoc (2007)Google Scholar
  2. 2.
    Goussevskaia, O., Halldórsson, M., Wattenhofer, R., Welzl, E.: Capacity of arbitrary wireless networks. In: IEEE INFOCOM (2009)Google Scholar
  3. 3.
    Wan, P.-J., Jia, X., Yao, F.: Maximum Independent Set of Links under Physical Interference Model. In: Liu, B., Bestavros, A., Du, D.-Z., Wang, J. (eds.) WASA 2009. LNCS, vol. 5682, pp. 169–178. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Ásgeirsson, E., Mitra, P.: On a game theoretic approach to capacity maximization in wireless networks. In: IEEE INFOCOM (2011)Google Scholar
  5. 5.
    Pei, G., Kumar, V.S.A.: Distributed algorithms for maximum link scheduling under the physical interference model (2012),

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Guanhong Pei
    • 1
  • Anil Kumar S. Vullikanti
    • 2
  1. 1.Dept. of Electrical and Computer Engineering, and Virginia Bioinformatics InstituteVirginia TechUSA
  2. 2.Dept. of Computer Science, and Virginia Bioinformatics InstituteVirginia TechUSA

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