Multi-objective Network Coding Optimization Based on NSGA-II Algorithm

Kun Hao, Beibei Wang, Yongmei Luo
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引用次数: 2

Abstract

Network coding could effectively improve transmission performance of multicast network, but encoding of node brings the additional calculation cost of node. In order to overcome the overhead brought by network coding, a network coding optimization model under the framework of algebraic network coding is designed in this paper, and the joint optimization for both the link cost and coding cost of network coding are carried out based on this model. In addition, the paper proposes MOONC (Multi-Objective Optimization Problem of Network Coding) based on improved NSGA-II algorithm. Adopting non-dominated sorting mechanism, virtual fitness and elitist strategy, this algorithm could not only improve algorithm efficiency and convergence speed, but also guarantee the population diversity. The simulation for typical network topology shows that this algorithm is effective and feasible.
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基于NSGA-II算法的多目标网络编码优化
网络编码可以有效地提高组播网络的传输性能,但对节点进行编码会增加节点的计算成本。为了克服网络编码带来的开销,本文设计了代数网络编码框架下的网络编码优化模型,并在此模型基础上对网络编码的链路成本和编码成本进行联合优化。此外,本文提出了基于改进NSGA-II算法的网络编码多目标优化问题(MOONC)。该算法采用非支配排序机制、虚拟适应度和精英策略,既提高了算法效率和收敛速度,又保证了种群的多样性。对典型网络拓扑结构的仿真表明了该算法的有效性和可行性。
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