{"title":"A new routing method based on ant colony optimization in vehicular ad-hoc network","authors":"Oussama Sbayti, Khalid Housni","doi":"10.19139/soic-2310-5070-1766","DOIUrl":null,"url":null,"abstract":"Vehicular Ad hoc Networks (VANETs) face significant challenges in providing high-quality service. These networks enable vehicles to exchange critical information, such as road obstacles and accidents, and support various communication modes known as Vehicle-to-Everything (V2X). This research paper proposes an intelligent method to improve the quality of service by optimizing path selection between vehicles, aiming to minimize network overhead and enhance routing efficiency. The proposed approach integrates Ant Colony Optimization (ACO) into the Optimized Link State Routing (OLSR) protocol. The effectiveness of this method is validated through implementation and simulation experiments conducted using the Simulation of Urban Mobility (SUMO) and the network simulator (NS3). Simulation results demonstrate that the proposed method outperforms the traditional OLSR algorithm in terms of throughput, average packet delivery rate (PDR), end-to-end delay (E2ED), and average routing overhead.","PeriodicalId":131002,"journal":{"name":"Statistics, Optimization & Information Computing","volume":"32 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics, Optimization & Information Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19139/soic-2310-5070-1766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Vehicular Ad hoc Networks (VANETs) face significant challenges in providing high-quality service. These networks enable vehicles to exchange critical information, such as road obstacles and accidents, and support various communication modes known as Vehicle-to-Everything (V2X). This research paper proposes an intelligent method to improve the quality of service by optimizing path selection between vehicles, aiming to minimize network overhead and enhance routing efficiency. The proposed approach integrates Ant Colony Optimization (ACO) into the Optimized Link State Routing (OLSR) protocol. The effectiveness of this method is validated through implementation and simulation experiments conducted using the Simulation of Urban Mobility (SUMO) and the network simulator (NS3). Simulation results demonstrate that the proposed method outperforms the traditional OLSR algorithm in terms of throughput, average packet delivery rate (PDR), end-to-end delay (E2ED), and average routing overhead.
车载 Ad hoc 网络(VANET)在提供高质量服务方面面临巨大挑战。这些网络使车辆能够交换道路障碍和事故等重要信息,并支持各种通信模式,即车对物(V2X)。本研究论文提出了一种通过优化车辆间路径选择来提高服务质量的智能方法,旨在最大限度地减少网络开销并提高路由效率。所提出的方法将蚁群优化(ACO)集成到优化链路状态路由(OLSR)协议中。通过使用城市移动性仿真(SUMO)和网络仿真器(NS3)进行实施和仿真实验,验证了该方法的有效性。仿真结果表明,所提出的方法在吞吐量、平均数据包交付率(PDR)、端到端延迟(E2ED)和平均路由开销方面都优于传统的 OLSR 算法。