Optimization of layered multicast with network coding and genetic algorithm

This article studies the problem of constructing optimal layered multicast with network coding for heterogeneous networks. Based on the flexibility of layered source coding, a global-favorable optimization scheme is proposed, which maximizes the aggregate throughput of heterogeneous sink nodes for layered multicast with network coding by determining the optimal bit rates of the layers. To solve this global-favorable optimization scheme, especially in the large-scale heterogeneous networks, a new problem-specific genetic algorithm （GA） is further proposed. It not only searches efficiently for the optimal allocation of layer bit rates, but also guarantees the validity of candidate solutions that this new GA-based optimization scheme could obtain layered multicast with network coding, even in the large-scale in the whole evolutionary process. Simulation results demonstrate efficiently the optimal or satisfactorily near-optimal bit rates for heterogeneous networks.

Scalable broadcast with network coding in heterogeneous networks

This article studies the scalable broadcast scheme realized with the joint application of layered source coding,unequal error protection （UEP） and random network coding from the theoretical point of view.The success probability for any non-source node in a heterogeneous network to recover the most important layers of the source data is deduced.This probability proves that in this broadcast scheme every non-source node with enough capacity can always recover the source data partially or entirely as long as the finite field size is sufficiently large.Furthermore,a special construction for the local encoding kernel at the source node is proposed.With this special construction,an increased success probability for partial decoding at any non-source node is achieved,i.e.,the partial decodability offered by the scalable broadcast scheme is improved.