SOFCluster: Safety-oriented, fuzzy logic-based clustering scheme for vehicular ad hoc networks (2020)
Belghith, Abdelfettah . 2020
Vehicular ad hoc network (VANET) nodes are characterized by their high mobility and by exhibiting different mobility patterns. Therefore, VANET clustering schemes are required to account for the mobility parameters among neighboring nodes to produce relatively stable clustering schemes. In this article, we propose a novel cluster‐head (CH) selection scheme for VANETs. This scheme is based on a fuzzy logic‐powered, k‐hop distributed clustering algorithm. It deals efficiently with scalability and stability issues of VANETs and is able to achieve highly stable clustering topologies as compared with other schemes. Our proposed clustering scheme strives to maintain a safe intervehicle distance as a one prime metric for CH selection. Moreover, a major contribution of our work is the proposal of a novel strategy for constructing fuzzy logic‐based clustering algorithms useful for VANETs. This proposed solution is useful in an Internet of things‐based setting that involves controlled vehicle‐to‐vehicle communication. We first derive mathematically, a new average distance estimation formula that is used as a metric for selecting CHs, leading to safer clusters that avoid collisions with front and rear vehicles. Furthermore, the new proposed scheme creates stable clusters by reducing reclustering overhead and prolonging clusters' lifetimes.
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