QMM-VANET: An efficient clustering algorithm based on QoS and monitoring of malicious vehicles in vehicular ad hoc networks

被引:0
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作者
Fatemidokht, Hamideh [1 ]
Kuchaki Rafsanjani, Marjan [1 ]
机构
[1] Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran
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基金
美国国家科学基金会;
关键词
Mobile telecommunication systems - Clustering algorithms - Routing protocols - Quality of service - Vehicles - Cluster computing - Gateways (computer networks);
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学科分类号
摘要
Vehicular ad hoc networks (VANETs) are considered as a subset of mobile ad hoc networks (MANETs) that can be used in the transportation field. These networks considerably improve the traffic safety and accident prevention. Because of the characteristics of VANETs such as self-organization, frequent link disconnections and rapid topology changes, developing efficient routing protocols is a challenging task. To address this issue, clustering is an appropriate approach in a mobile environment. Clustering aims to partition the vehicles into a number of clusters based on some predefined metrics such as velocity, distance and location. In this paper, a clustering routing protocol, named QMM-VANET, which considers Quality of Service (QoS) requirements, the distrust value parameters and mobility constraints, is proposed. This protocol specifies a reliable and stable cluster and increases the stability and connectivity during communications. This protocol is composed of three parts: (1) computing the QoS of vehicles and electing a trustier vehicle as a cluster-head, (2) selecting a set of proper neighboring nodes as gateways for retransmitting the packets and (3) using gateway recovery algorithm to choose another gateway in case of failure of the link. NS-2 simulator is utilized to illustrate the performance of our proposed protocol in a highway scenario. The performance analyses display that the QMM-VANET protocol can achieve low end-to-end delay and high packet delivery ratio and maintain the network stability. © 2020 Elsevier Inc.
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