• DocumentCode
    3663014
  • Title

    Symmetry in network coding

  • Author

    Jayant Apte;John MacLaren Walsh

  • Author_Institution
    Drexel University, Dept. of ECE, Philadelphia, PA 19104, USA
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    376
  • Lastpage
    380
  • Abstract
    We establish connections between graph theoretic symmetry, symmetries of network codes, and symmetries of rate regions for k-unicast network coding and multi-source network coding. We identify a group we call the network symmetry group as the common thread between these notions of symmetry and characterize it as a subgroup of the automorphism group of a directed cyclic graph appropriately constructed from the underlying network´s directed acyclic graph. Such a characterization allows one to obtain the network symmetry group using algorithms for computing automorphism groups of graphs. We discuss connections to generalizations of Chen and Yeung´s partition symmetrical entropy functions and how knowledge of the network symmetry group can be utilized to reduce the complexity of computing the LP outer bounds on network coding capacity as well as the complexity of polyhedral projection for computing rate regions.
  • Keywords
    "Network coding","Random variables","Entropy","Tin","Artificial neural networks","Complexity theory","Partitioning algorithms"
  • Publisher
    ieee
  • Conference_Titel
    Information Theory (ISIT), 2015 IEEE International Symposium on
  • Electronic_ISBN
    2157-8117
  • Type

    conf

  • DOI
    10.1109/ISIT.2015.7282480
  • Filename
    7282480