An enhanced whale optimization algorithm for vehicular communication networks. (26th April 2019)

• Record Type: Journal Article
• Authors: Valayapalayam Kittusamy, Senthil Ragavan; Elhoseny, Mohamed; Kathiresan, Shankar
• Other Names: Kumari Saru guestEditor.; Kumar Sangaiah Arun guestEditor.; Chaudhary Ankit guestEditor.; Wang Jin guestEditor.; Mercaldo Francesco guestEditor.
• Is Part Of: International journal of communication systems. Volume 35:Number 12(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-26
• Subjects: clustering -- mobility analysis -- sensors -- VANET -- vehicular communication networks -- whale optimization; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.3953
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: In the field of vehicle communication networks, vehicular ad hoc network (VANET) is established with the help of road side unit (RSU). Each vehicle in the traffic system is managed by RSU with certain mobility factor, but still, there are some issues in the mobility management. In order to avoid such expensive RSUs and to enhance the mobility management of VANET system, the paper proposes a novel algorithm for the process of organizing a cluster structure and cluster head (CH) election suitable for VANETs. The proposed adaptive weighted clustering protocol (AWCP) groups the random nodes, and then the optimal CH is attained by the optimization of network parameters. For the purpose of optimization, an innovative algorithm called the enhanced whale optimization algorithm (EWOA) is introduced. For each vehicle in a trusted clustering model, its movement is analyzed by vehicle network mobility routing protocol with identified speed and position. The distance between the trusted vehicle node and RSU is analyzed by the proposed AWCP‐EWOA model. The results demonstrate the proposed AWCP‐EWOA model outperforms compared with AWCP and AWCP‐Whale Algorithm (WA) protocols in terms of clustering efficiency and its mobility enhancement. Abstract : The proposed adaptive weighted clustering protocol groups the random nodes, and then the optimal cluster head is attained by the optimization of network parameters. For the purpose of optimization, an innovative algorithm called the enhanced whale optimization algorithm (EWOA) is introduced. For each vehicle in a trusted clustering model, its movement is analyzed by vehicle network mobility routing protocol with identified speed and position. The distance between the trusted vehicle node and road side unit (RSU) is analyzed by the proposed adaptive weighted clustering protocol (AWCP)–EWOA model.