Dense Subgraphs on Dynamic Networks

  • Atish Das Sarma
  • Ashwin Lall
  • Danupon Nanongkai
  • Amitabh Trehan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7611)


In distributed networks, it is often useful for the nodes to be aware of dense subgraphs, e.g., such a dense subgraph could reveal dense substructures in otherwise sparse graphs (e.g. the World Wide Web or social networks); these might reveal community clusters or dense regions for possibly maintaining good communication infrastructure. In this work, we address the problem of self-awareness of nodes in a dynamic network with regards to graph density, i.e., we give distributed algorithms for maintaining dense subgraphs that the member nodes are aware of. The only knowledge that the nodes need is that of the dynamic diameter D, i.e., the maximum number of rounds it takes for a message to traverse the dynamic network. For our work, we consider a model where the number of nodes are fixed, but a powerful adversary can add or remove a limited number of edges from the network at each time step. The communication is by broadcast only and follows the CONGEST model. Our algorithms are continuously executed on the network, and at any time (after some initialization) each node will be aware if it is part (or not) of a particular dense subgraph. We give algorithms that (2 + ε)-approximate the densest subgraph and (3 + ε)-approximate the at-least-k-densest subgraph (for a given parameter k). Our algorithms work for a wide range of parameter values and run in O(Dlog1 + ε n) time. Further, a special case of our results also gives the first fully decentralized approximation algorithms for densest and at-least-k-densest subgraph problems for static distributed graphs.


Dynamic Network Dynamic Graph Approximation Guarantee Dense Subgraph Subgraph Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Atish Das Sarma
    • 1
  • Ashwin Lall
    • 2
  • Danupon Nanongkai
    • 3
    • 4
  • Amitabh Trehan
    • 5
  1. 1.eBay Research LabsSan JoseUSA
  2. 2.Department of Mathematics and Computer ScienceDenison UniversityGranvilleUSA
  3. 3.University of ViennaAustria
  4. 4.Nanyang Technological UniversitySingapore
  5. 5.Information Systems group, Faculty of Industrial Engineering and ManagementTechnion - Israel Institute of TechnologyHaifaIsrael

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