基于遗传算法的多媒体网络编码资源优化

Zhijian Qu, Xiaohong Liu, Jia Fu
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引用次数: 1

摘要

本文研究了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最小化问题。网络编码资源优化问题已被证明是np困难问题,延迟约束的引入使其求解变得更加复杂,因为本质上构造这种延迟约束树而不结合编码资源优化的单一问题是np完全的。在解决这一问题的过程中,将多选题背包问题(MCKP)的基本模型作为优化实体,提出了基于路由编码的遗传算法(REGA)。在三种网络场景下的数值结果验证了该算法的有效性,对实际多媒体网络中具有更高QoS水平的拓扑设计具有一定的潜力和帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic algorithm-based network coding resources optimization in multimedia network
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.
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