认知无线电中车载传感器网络的OLSR协议

Q4 Business, Management and Accounting

International Journal of Mobile Network Design and Innovation Pub Date : 2018-08-02 DOI:10.1504/IJMNDI.2018.10014840

A. Priyadharshini, M. Sundarambal

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引用次数: 1

摘要

在我们所提出的系统中，车辆传感器网络(VSN)是基于认知无线电，并借助于最优链路状态路由(OLSR)协议来构建的。本文展望了与认知无线电相关的车载传感器网络的数据通信。利用混合组搜索和遗传算法(HGSO-GA)对最优链路状态路由协议进行了改进。采用OLSR协议选取传播功率包的相邻节点，减少网络中的控制透明度。数据包在多点中继(MPR)车辆的帮助下从源传输到目的，MPR车辆是每个源选择的邻居车辆的子集，以访问所有作为转发器的两跳邻居。OLSR路由协议，有效管理频谱分配，减少路由延迟。该技术已在NS2工作平台上实现。

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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OLSR protocol for vehicular sensor network in cognitive radio

In our proposed system, the vehicular sensor network (VSN) is formulated based on the cognitive radio with the aid of optimal link state routing (OLSR) protocol. Here the cognitive radio related vehicular sensor networks are anticipated for the data communication. The optimal link state routing protocol is modified by utilising the hybrid group search and genetic algorithm (HGSO-GA) algorithm. The OLSR protocol is used to pick the adjacent nodes which disseminate the power package to diminish the quantity of control transparency in the network. The data packages are conveyed from source to destination with the help of multi point relay (MPR) vehicles, which is the subset of the chosen neighbour vehicles by each source to access all the two-hop neighbours act as forwarders. OLSR routing protocol to efficiently manage spectrum allocation that helps reduce the routing delay. The proposed technique is implemented in the working platform of NS2.

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来源期刊

International Journal of Mobile Network Design and Innovation Business, Management and Accounting-Management Information Systems

CiteScore

0.30

自引率

0.00%

发文量

期刊介绍： The IJMNDI addresses the state-of-the-art in computerisation for the deployment and operation of current and future wireless networks. Following the trend in many other engineering disciplines, intelligent and automatic computer software has become the critical factor for obtaining high performance network solutions that meet the objectives of both the network subscriber and operator. Characteristically, high performance and innovative techniques are required to address computationally intensive radio engineering planning problems while providing optimised solutions and knowledge which will enhance the deployment and operation of expensive wireless resources.