manet中路由的建立采用束状虫群算法和跨层交互进行改进

Sadanand Inamdar, Jayashree I. Kallibaddi
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引用次数: 0

摘要

本文提出了移动自组织网络(MANETs)中的定向路由方法,该方法探索了一种更新的生物启发的增强方法,称为被膜群算法(TSA),以识别最优路径。对重复喷流脉冲和被囊动物群体行为的TSA进行了改进,以克服其早期陷入局部最优的缺陷。使用跨层交互(CLI)跨层交换网络密度参数。提出了在定向天线无线网络的介质接入协议中通过改变方向监控时间、可选握手和改变数据片段长度来减轻路由协议负担的方法。仿真结果表明,在manet中,基于TSA和CLI的路由方法相对于其他竞争方案提供了更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Route establishment in MANETs; Ameliorated with Tunicate Swarm Algorithm and Cross layer Interaction
This paper proposes directional routing approach in Mobile Ad-hoc NETworks (MANETs) that explores updated biologically inspired intensification method called Tunicate Swarm Algorithm (TSA) to identify optimal path. TSA that duplicates jet impulse and swarm actions of tunicates is modified to overcome its earlier deficiency of trapping into local optima. Network density parameter is exchanged across layers using Cross Layer Interaction (CLI). It is proposed to reduce routing protocol’s burden by having changing directional monitoring time, optional handshake and changing data fragment length in medium access protocol of directional antenna enabled MANETs. The results obtained in simulation show that TSA and CLI based routing approaches in MANETs provide improved result in relation to other competing proposals.
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