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Genetic algorithm-based network coding resources optimization in multimedia network

机译:基于遗传算法的多媒体网络编码资源优化

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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.
机译:本文着眼于最小化多媒体网络中具有端到端时延和时延变化约束的网络编码资源的问题。网络编码资源优化问题已被证明是NP难的,而延迟约束的引入使解决起来更加复杂,因为本质上不结合编码资源优化而构造这种延迟约束树的单个问题就是NP完全的。在解决此问题的过程中,将多项选择背包问题(MCKP)的基本模型用作所提出的称为基于路由的编码GA(REGA)的遗传算法(GA)的优化实体。然后在三个网络场景下的数值结果证明了该算法的有效性,表明了在实际多媒体网络中具有较高QoS级别的拓扑设计的潜力和有用的能力。

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