车载Ad-Hoc网络中RSU分配的混合仿生优化方案

M. H. Hassan, Ameer Mohammed Al-obaidi, Sameer Alani, F. Abbas, A. Alkhayyat, S. Mahmood, Hayder Muayad Al-Maawi, R. R. Ali
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摘要

车辆自组织网络(vehicular Ad-Hoc Network, VANETs)是在智能交通系统(Intelligent Transport Systems, ITS)的所有应用中发挥最大作用的趋势模型。一般来说,vanet基于两种通信类型,例如车辆之间和车辆与基础设施路边单元(RSU)之间的通信。本文将蚁群优化算法(Ant Colony optimization, ACO)与蚱蜢优化算法(Grasshopper optimization Algorithm, GOA)相结合,提出了一种基于非混合生物优化的HACOGO方法。HACOGO用于在VANETs中实现稳定的RSU分布。采用蚁群算法帮助车辆选择到达目的地的最优路径,并采用GOA算法选择高度宏伟的车辆作为RSU。HACOGO的性能分析是通过计算数据包传送率、端到端延迟、丢包和路由开销等常用参数来完成的。为了分析所提模型的有效性,将其结果与先前的工作进行了比较。实验结果表明,采用HACOGO方法可以降低端到端时延、丢包率和路由开销,提高网络的分组传输率。关键词:车辆自组织网络,路边单元,蚁群优化。
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A Hybrid Bio-Inspired Optimization Scheme for RSU Distribution in Vehicular Ad-Hoc Network
—Vehicular Ad-Hoc Network (VANETs) is a trending modelthat plays maximum role inall the application of Intelligent Transport Systems (ITS). In general, VANETs are based on two communication types such as among vehicles and vehicles to infrastructure Roadside Units(RSU) based communication. In this paper, HACOGO approach is developedbased on ahybrid bio inspired optimization with the combination of Ant Colony Optimization (ACO) with Grasshopper Optimization Algorithm (GOA). The HACOGO is used to perform stable RSU distribution in VANETs. The ACO algorithm is used to help the vehicle to select the optimal path toward the destination and GOA algorithm highly magnificent vehicle is chosen as RSU. The Performance analysis of HACOGO is done by calculating the common parameters such as packet delivery ratio, end-to-end delay, packet loss and routing overhead. To analysis the effectiveness of the proposed model its results are compared with the earlier works. From the outcome it is proven using the HACOGO approach the end-to-end delay, packet loss and routing overhead is reduced as well as the packet delivery ratio of the network is increased than others. Keywords—Vehicular Ad-Hoc Network,Roadside Units, Ant Colony Optimization.
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