An evolutionary approach to inter-session network coding

• Main Authors: O'Reilly, Una-May (Contributor), Medard, Muriel (Contributor), Traskov, Danail (Author), Kim, Minkyu (Contributor)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
• Format: Article
• Language: English
• Published: 2010-05-04T15:22:23Z.
• Subjects: Article
• Online Access: Get fulltext

 Whereas the theory and application of optimal network coding are well studied for the single-session multicast scenario, there is no known optimal network coding strategy for a more general connection problem where there are more than one session and receivers may demand different sets of information. Though there have been a number of recent studies that demonstrate various utilities of network coding in the multi- session scenario, they rely on very restricted classes of codes in terms of the coding operations allowed and/or the location of decoding. In this paper, we propose a novel inter-session network coding strategy for a general connection problem. Our coding strategy allows fairly general random linear coding over a large finite field, in which decoding is done at receivers and the mixture of information at interior nodes is controlled by evolutionary mechanisms. We demonstrate how our coding strategy may surpass existing end-to-end pairwise XOR coding schemes in terms of effectiveness and practicality.