基于改进金枪鱼群算法的VANETs最优聚类最小化

Maria Christina Blessy A, S. Brindha, Bhargavi Kv, Kamali T
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引用次数: 0

摘要

车辆自组织网络(VANETs)是由车辆之间无线通信建立的即时网络。很难使这种连接成为可能和可靠的,因为车辆以更快的速度移动,它们之间的连接是不可靠的。采用多种方法建立可靠稳定的连接。其中之一是基于集群的。集群是一组车辆,它们实际上连接在一起形成一个小网络。VANET能够通过使用集群提供可靠和稳定的连接。提出了几种高效可靠的聚类算法。提出的改进金枪鱼群优化算法旨在减少集群数量的同时提高数据包的传输率和吞吐量。结果表明,该方法得到的结果接近最优,是一种有效的车辆聚类方法,可以提高网络性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Cluster Minimization for VANETs using Modified Tuna Swarm Optimization
Vehicular ad hoc networks (VANETs) are Instantaneous networks built by vehicles communicating wirelessly to one another. It is difficult to make this connection possible and reliable because the vehicles move at a faster rate and the link between them is unreliable. Multiple methods are adapted to establish a reliable and stable connection. One of which is cluster-based. Clusters are groups of vehicles that are virtually linked to form a small network. VANET is able to provide a reliable and stable connection through the use of clusters. Several algorithms are proposed for the formation of a cluster that is both efficient and reliable. The proposed modified tuna swarm optimization algorithm aims to decrease the number of clusters while simultaneously boosting the packet delivery ratio and throughput. The results indicate that the proposed method yields results that are close to optimal, making it an efficient method for performing vehicular clustering to improve network performance.
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