Remora optimization algorithm-based optimized node clustering technique for reliable data delivery in VANETs

Swathi Konduru , M. Sathya
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引用次数: 2

Abstract

Vehicular ad hoc Network (VANET) is one of the recently growing trends which motivate the provision of several service providers in the urban areas. In VANETs, the vehicles represent the nodes in the network topology that needs to guarantee better cooperation when there is a higher node density. Moreover, the problem of determining an optimal route and achieving network scalability is a herculean task. In this context, the incorporation of a potential clustering algorithm has the possibility of improving the road safety and facilitating a reliable option of promoting message routing. The clustering protocols are determined to be the ideal candidate for solving the problems of network scalability to guarantee reliable data dissemination. In this paper, Remora optimization algorithm-based Optimized Node Clustering (ROAONC) Technique is proposed for node clustering in VANETs to achieved optimal CH selection process. This ROAONC scheme was proposed for minimizing network overhead in the scenarios of unpredictable node density. The simulation results of this ROAONC scheme confirmed better performance in terms of transmission range, node density, network area and number of clusters compared to the competitive ant colony, grey wolf, grasshopper, and dragonfly optimization algorithm-based clustering protocols.

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基于Remora优化算法的优化节点聚类技术在VANETs中实现可靠的数据传输
车辆自组织网络(VANET)是最近发展的趋势之一,它促使城市地区的几个服务提供商提供服务。在VANETs中,车辆代表网络拓扑中的节点,当节点密度较高时,需要保证更好的协作。此外,确定最优路由和实现网络可扩展性是一项艰巨的任务。在这种情况下,结合潜在的聚类算法有可能提高道路安全性并促进消息路由的可靠选择。集群协议是解决网络可扩展性问题以保证数据可靠传播的理想选择。本文提出了一种基于Remora优化算法的优化节点聚类(ROAONC)技术,用于VANETs的节点聚类,以实现最优的CH选择过程。该方案是为了在节点密度不可预测的情况下最小化网络开销而提出的。仿真结果表明,该方案在传输范围、节点密度、网络面积和集群数量等方面均优于竞争对手的基于蚁群、灰狼、蚱蜢和蜻蜓优化算法的聚类协议。
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