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
Link To Document