Genetic algorithm-based network coding resources optimization in multimedia network
Zhijian Qu, Xiaohong Liu, Jia Fu · 2012
This paper concentrates on the problem of minimizing network coding resources with end-to-end delay and delay variation constraints in multimedia network. Network coding resources optimization problem has proved to be NP-hard, and the introduction of delay constraints makes it more complicated to be solved, since essentially the single problem of constructing such delay constrained tree without combining coding resources optimization, is NP-complete. In the process of tackling this problem, the basic model of the multiple-choice knapsack problem (MCKP) is used as an optimized entity for the proposed genetic algorithm (GA) called routing-based encoding GA (REGA). Then numeric results over three network scenarios demonstrate the effectiveness of the presented algorithm, which shows some potential and helpful capacity on topology designing with higher QoS level in practical multimedia network.