{"title":"A Routing Scheme Using an Adaptive K-Harmonic Means Clustering for VANETs","authors":"Khalid Kandali, H. Bennis","doi":"10.1109/ISCV49265.2020.9204257","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a routing protocol using an adaptive K-Harmonic Means (RPKHM) in order to improve the lifetime of links between vehicles and to increase the stability of the vehicular network. First, the number and initial positions of the centroids are determined using a mathematical model that takes into account the total number of vehicles and the network topology. Whereas, the clustering is done using a similarity value based on the Euclidean distance, the difference in speed and direction of the vehicles. Finally, the maintenance of the clusters and the selection of new cluster heads are based on a cost function, which takes into account the total size of the free buffer and expected transmission count (ETX). The simulation results show the efficiency of the proposed scheme in terms of Packet Delivery Ratio, average End-to-End Delay, and Throughput.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCV49265.2020.9204257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, we propose a routing protocol using an adaptive K-Harmonic Means (RPKHM) in order to improve the lifetime of links between vehicles and to increase the stability of the vehicular network. First, the number and initial positions of the centroids are determined using a mathematical model that takes into account the total number of vehicles and the network topology. Whereas, the clustering is done using a similarity value based on the Euclidean distance, the difference in speed and direction of the vehicles. Finally, the maintenance of the clusters and the selection of new cluster heads are based on a cost function, which takes into account the total size of the free buffer and expected transmission count (ETX). The simulation results show the efficiency of the proposed scheme in terms of Packet Delivery Ratio, average End-to-End Delay, and Throughput.