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A Bio-Inspired Cluster Optimization Schema for Efficient Routing in Vehicular Ad Hoc Networks (VANETs)

Husnain, Ghassan ; Anwar, Shahzad ; Sikander, Gulbadan ; Ali, Armughan ; Lim, Sangsoon

Energies (Basel), 2023-02, Vol.16 (3), p.1456 [Periódico revisado por pares]

Basel: MDPI AG

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Título:
A Bio-Inspired Cluster Optimization Schema for Efficient Routing in Vehicular Ad Hoc Networks (VANETs)
Autor: Husnain, Ghassan ; Anwar, Shahzad ; Sikander, Gulbadan ; Ali, Armughan ; Lim, Sangsoon
Assuntos: Algorithms ; Bandwidths ; bio-inspired algorithms ; Clustering ; Communication ; Decision making ; Highways ; Intelligent transportation systems ; Latency ; Mathematical optimization ; Mobile ad hoc networks ; Network latency ; Network security ; Network topologies ; Optimization ; Optimization algorithms ; Optimization techniques ; Roads & highways ; Service stations ; Topology ; Traffic ; Traffic control ; Traffic regulations ; Transportation networks ; Vehicles ; vehicular networks ; whale optimization algorithm ; Wireless access points
É parte de: Energies (Basel), 2023-02, Vol.16 (3), p.1456
Descrição: Vehicular ad hoc networks (VANETs) are vital to many Intelligent Transportation System (ITS)-enabled technologies, including efficient traffic control, media applications, and encrypted financial transactions. Due to an increase in traffic, vehicular network topology is constantly changing, and sparse vehicle distribution (on highways) hinders network scalability. Thus, there is a challenge for all vehicles (in the network) to maintain a stable route, which would increase network instability. Concerning IoT-based network transportation, this study proposes a bio-inspired, cluster-based algorithm for routing, i.e., the intelligent, probability-based, and nature-inspired whale optimization algorithm (p-WOA), which produces cluster formation in vehicular communication. Various parameters, such as communication range, number of nodes, velocity, and route along the highway were considered, and their probaabilities were incorporated into the fitness function, hence resulting in randomness reduction. Results were compared to existing methods such as Ant Lion Optimizer (ALO) and Grey Wolf Optimization (GWO), demonstrating that the developed p-WOA technique produces an optimal number of cluster heads (CH). The results achieved by calculating the Packet Delivery Ratio (PDR), average throughput, and latency demonstrate the superiority of the proposed method over other well-established methodologies (ALO and GWO). This study confirms statistically that VANETs employing ITS applications optimize their clusters by a factor of 75, which has the twin benefits of decreasing communication costs and routing overhead and extending the life of the cluster as a whole.
Editor: Basel: MDPI AG
Idioma: Inglês

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A Bio-Inspired Cluster Optimization Schema for Efficient Routing in Vehicular Ad Hoc Networks (VANETs)

Husnain, Ghassan ; Anwar, Shahzad ; Sikander, Gulbadan ; Ali, Armughan ; Lim, Sangsoon

Basel: MDPI AG

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