Content Distribution Network for Streaming Using Multiple Galois Fields

Abstract

In this paper, the architecture of random linear network coding based on the hybrid coding in multiple Galois field sizes is proposed. Random linear network coding is an efficient network coding approach that enables network to generate independently and randomly linear mapping between input and output symbols over finite field. With the proposed reduction method, coded symbols and coefficients in higher degree of Galois field can be converted to symbols and coefficients in GF(2) so that hybrid coding in multiple Galois field sizes can be made possible. Therefore, peers in the heterogeneous environments can all benefit from the proposed content distribution network for streaming to better utilize the network resource.