{"title":"Parameters tuning of OLSR routing protocol with metaheuristic algorithm for VANET","authors":"Anusha Bandi, B. Chandrashekhar","doi":"10.1109/IADCC.2015.7154894","DOIUrl":null,"url":null,"abstract":"Vehicular Adhoc Network provides ability to wirelessly communicate between vehicles. Network fragmentations and frequent topology changes (Mobility of the nodes) and limited coverage of Wi-Fi, are issues in VANET, that arise due to absence of central manager entity. Because of these reasons, routing the packets within the network is difficult task. Hence, provisioning an adept routing strategy is vital for the deployment of VANETs. The optimized link state routing is a well-known mobile adhoc network routing protocol. In this paper, we are proposing an optimization strategy to fine-tune few parameters by configuring the OLSR protocol using metaheuristic method. We considered some of the quality parameters such as packet delivery ratio, latency, throughput and fitness value for fine tuning OSLR protocol. Then we made Comparison of genetic algorithm, particle swarm optimization algorithm by using QoS parameters. We implemented our work on Red Hat Enterprise Linux 6 platform. And results are shown by simulations using VanetMobiSim and NS2 simulators; the fine-tuned OSLR protocol behaves better than the original routing protocol with intelligence and optimization configuration.","PeriodicalId":123908,"journal":{"name":"2015 IEEE International Advance Computing Conference (IACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Advance Computing Conference (IACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IADCC.2015.7154894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Vehicular Adhoc Network provides ability to wirelessly communicate between vehicles. Network fragmentations and frequent topology changes (Mobility of the nodes) and limited coverage of Wi-Fi, are issues in VANET, that arise due to absence of central manager entity. Because of these reasons, routing the packets within the network is difficult task. Hence, provisioning an adept routing strategy is vital for the deployment of VANETs. The optimized link state routing is a well-known mobile adhoc network routing protocol. In this paper, we are proposing an optimization strategy to fine-tune few parameters by configuring the OLSR protocol using metaheuristic method. We considered some of the quality parameters such as packet delivery ratio, latency, throughput and fitness value for fine tuning OSLR protocol. Then we made Comparison of genetic algorithm, particle swarm optimization algorithm by using QoS parameters. We implemented our work on Red Hat Enterprise Linux 6 platform. And results are shown by simulations using VanetMobiSim and NS2 simulators; the fine-tuned OSLR protocol behaves better than the original routing protocol with intelligence and optimization configuration.
车辆自组织网络提供了车辆之间无线通信的能力。网络碎片化和频繁的拓扑变化(节点的移动性)以及Wi-Fi的有限覆盖是VANET中由于缺乏中央管理实体而出现的问题。由于这些原因,路由网络中的数据包是一项艰巨的任务。因此,提供一个熟练的路由策略对于vanet的部署至关重要。优化链路状态路由是一种著名的移动自组网路由协议。在本文中,我们提出了一种优化策略,通过使用元启发式方法配置OLSR协议来微调少数参数。我们考虑了一些质量参数,如数据包传送率、延迟、吞吐量和适应度值来微调OSLR协议。然后利用QoS参数对遗传算法和粒子群算法进行了比较。我们在Red Hat Enterprise Linux 6平台上实现了我们的工作。并利用VanetMobiSim和NS2仿真器进行了仿真。优化后的OSLR协议具有智能和优化配置,性能优于原有的路由协议。