An adjusted K‐medoids clustering algorithm for effective stability in vehicular ad hoc networks. (14th June 2019)

• Record Type: Journal Article
• Authors: Hajlaoui, Rejab; Alsolami, Eesa; Moulahi, Tarek; Guyennet, Hervé
• Is Part Of: International journal of communication systems. Volume 32:Number 12(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-06-14
• Subjects: algorithm -- communication -- k‐medoids -- protocol -- stability -- vehicular ad hoc network; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.3995
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: Recently, the routing problem in vehicular ad hoc networks is one of the most vital research. Despite the variety of the proposed approaches and the development of communications technologies, the routing problem in VANET suffers from the high speed of vehicles and the repetitive failures in communications. In this paper, we adjusted the well‐known K ‐medoids clustering algorithm to improve the network stability and to increase the lifetime of all established links. First, the number of clusters and the initial cluster heads will not be selected randomly as usual, but based on mathematical formula considering the environment size and the available transmission ranges. Then the assignment of nodes to clusters in both k ‐medoids phases will be carried out according to several metrics including direction, relative speed, and proximity. To the best of our knowledge, our proposed model is the first that introduces the new metric named "node disconnection frequency." This metric prevents nodes with volatile and suspicious behavior to be elected as a new CH. This screening ensures that the new CH retains its property as long as possible and thus increases the network stability. Empirical results confirm that in addition to the convergence speed that characterizes our adjusted K ‐medoids clustering algorithm (AKCA), the proposed model achieves more stability and robustness when compared with most recent approaches designed for the same objective. Abstract : According to a large‐scale survey, the most appropriate routing protocols for VANETs are design based on the clustering approach. In this context, our idea is to adjust the " K ‐medoids" clustering algorithm for the vehicular routing problem. The goal of our adjusted K ‐medoids clustering algorithm (AKCA) is to improve the stability of the network and increase the lifespan of all established links.