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Mobility Aware Energy Efficient Clustering for MANET: A Bio-Inspired Approach with Particle Swarm Optimization

机译:MANET的移动感知能效集群:一种具有粒子群优化的生物启发方法

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Mobility awareness and energy efficiency are two indispensable optimization problems in mobile ad hoc networks (MANETs) where nodes move unpredictably in any direction with restricted battery life, resulting in frequent change in topology. These constraints are widely studied to increase the lifetime of such networks. This paper focuses on the problems of mobility as well as energy efficiency to develop a clustering algorithm inspired by multiagent stochastic parallel search technique of particle swarm optimization. The election of cluster heads takes care of mobility and remaining energy as well as the degree of connectivity for selecting nodes to serve as cluster heads for longer duration of time. The cluster formation is presented by taking multiobjective fitness function using particle swarm optimization. The proposed work is experimented extensively in the NS-2 network simulator and compared with the other existing algorithms. The results show the effectiveness of our proposed algorithm in terms of network lifetime, average number of clusters formed, average number of reclustering required, energy consumption, and packet delivery ratio.
机译:移动意识和能效是移动自组织网络(MANET)中两个必不可少的优化问题,其中节点在电池寿命有限的情况下无法沿任意方向移动,从而导致拓扑结构频繁变化。对这些约束条件进行了广泛研究,以延长此类网络的寿命。本文针对流动性和能效问题,开发了一种基于粒子群优化的多智能体随机并行搜索技术的聚类算法。簇头的选择要考虑移动性和剩余能量,以及用于选择要用作较长时间簇头的节点的连接程度。通过采用粒子群优化的多目标适应度函数来表示聚类的形成。这项工作在NS-2网络模拟器中进行了广泛的实验,并与其他现有算法进行了比较。结果表明,在网络寿命,形成的平均簇数,所需的平均重新群集数,能耗和数据包传输率方面,我们提出的算法是有效的。

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