LT Network Codes

Mary-Luc Champel, Kévin Huguenin, Anne-Marie Kermarrec, Nicolas Le Scouarnec
2010 2010 IEEE 30th International Conference on Distributed Computing Systems  
Network coding has been successfully applied in large-scale content dissemination systems. While network codes provide optimal throughput, its current forms suffer from a high decoding complexity. This is an issue when applied to systems composed of nodes with low processing capabilities, such as sensor networks. In this paper, we propose a novel network coding approach based on LT codes, initially introduced in the context of erasure coding. Our coding scheme, called LTNC, fully benefits from
more » ... he low complexity of belief propagation decoding. Yet, such decoding schemes are extremely sensitive to statistical properties of the code. Maintaining such properties in a fully decentralized way with only a subset of encoded data is challenging. This is precisely what the recoding algorithms of LTNC achieve. We evaluate LTNC against random linear network codes in an epidemic content-dissemination application. Results show that LTNC increases communication overhead (20%) and convergence time (30%) but greatly reduces the decoding complexity (99%) when compared to random linear network codes. In addition, LTNC consistently outperforms dissemination protocols without codes, thus preserving the benefit of coding.
doi:10.1109/icdcs.2010.14 dblp:conf/icdcs/ChampelHKS10 fatcat:hzbw3grlhvb6xdyz42c657sxbm