Open Access

ARTICLE

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Youseef Alotaibi¹, B. Rajasekar², R. Jayalakshmi³, Surendran Rajendran^4,*

1 Department of Software Engineering, College of Computing, Umm Al-Qura University, Makkah, 21955, Saudi Arabia
2 Department of Electronics and Communication Engineering, Sathyabama Institute of Science and Technology, Chennai, 600119, India
3 Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, 600123, India
4 Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Science, Chennai, 602105, India

* Corresponding Author: Surendran Rajendran. Email:

(This article belongs to the Special Issue: Secure Blockchain Clustering for 6G Wireless Technology with Advanced Artificial Intelligence Techniques)

Computers, Materials & Continua 2024, 78(3), 4243-4262. https://doi.org/10.32604/cmc.2024.047608

Received 10 November 2023; Accepted 08 February 2024; Issue published 26 March 2024

Abstract

Rapid development in Information Technology (IT) has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle (V2V) transmission. Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data. The communication occurs directly between V2V and Base Station (BS) units such as the Road Side Unit (RSU), named as a Vehicle to Infrastructure (V2I). However, the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time. Therefore, the scheme of an effectual routing protocol for reliable and stable communications is significant. Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment. Therefore, this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing (FOA-EECPCR) technique in VANETS. The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET. To accomplish this, the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy, distance, and trust level. For the routing process, the Sparrow Search Algorithm (SSA) is derived with a fitness function that encompasses two variables, namely, energy and distance. A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method. The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

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Keywords

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