Nature inspired route optimization in vehicular adhoc network

Mayank V. Bhatt, Shabnam Sharma, A. K. Luhach, Aditya Prakash
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引用次数: 12

Abstract

Recent advancements introduced in the field of wireless technologies have led to the emergence of vehicular ad hoc networks (VANETs). VANET consists of vehicles and road-side units as its components. These components communicate with each other to share the information, mainly related to traffic conditions. In such networks, routing, secure transmission of control information and user messages, avoiding traffic collisions and frequent change of topology are the main issues that arise. Therefore, offering an efficient algorithm for avoiding traffic collision is crucial to the deployment of vehicular ad hoc networks. This work deals with finding an optimized route to reach the destination while avoiding traffic collisions, using Meta heuristic optimization approach, namely Bat Algorithm. The proposed work has three modules: prediction of destination location, formation of region (by excluding invalid nodes) and finally the selection of optimized route. This work can be implemented in those application areas, where the purpose is to track the position of objects or nodes. Finally, the results are compared with standard Bat algorithm on the basis of number of iterations, number of nodes and total travelling time to reach the destination.
基于自然启发的车辆自组网路径优化
无线技术领域的最新进展导致了车载自组织网络(vanet)的出现。VANET由车辆和路边单元组成。这些组件之间相互通信,共享信息,主要与交通状况有关。在这种网络中,路由、控制信息和用户消息的安全传输、避免流量冲突和频繁的拓扑变化是主要问题。因此,提供一种有效的避免交通冲突的算法对车辆自组织网络的部署至关重要。本研究使用元启发式优化方法,即Bat算法,在避免交通冲突的情况下,找到一条到达目的地的优化路线。提出的工作分为三个模块:目的地位置的预测、区域的形成(通过排除无效节点)和优化路线的选择。这项工作可以在这些应用领域实现,其目的是跟踪对象或节点的位置。最后,根据迭代次数、节点数和到达目的地的总旅行时间,将结果与标准Bat算法进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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