Grey wolf optimization based clustering algorithm for vehicular ad-hoc networks. (August 2018)

• Record Type: Journal Article
• Authors: Fahad, Muhammad; Aadil, Farhan; Rehman, Zahoor-ur-; Khan, Salabat; Shah, Peer Azmat; Muhammad, Khan; Lloret, Jaime; Wang, Haoxiang; Lee, Jong Weon; Mehmood, Irfan
• Is Part Of: Computers & electrical engineering. Volume 70(2018)
• Page Start: 853
• Page End: 870
• Publication Date: 2018-08
• Subjects: VANETs -- Clustering -- Ad-hoc networks -- Grey wolf optimizer -- Artificial neural networks -- Intelligent transportation system; ACO Ant Colony Optimization -- ACROA Artificial Chemical Reaction Optimization Algorithm -- BBBC Big-Bang Big-Crunch -- BHA Black Hole Algorithm -- CACONET Clustering algorithm based on Ant Colony Optimization (ACO) for VANET -- CFO Central Force Optimization -- CHs Cluster heads -- CLPSO Comprehensive Learning Particle Swarm Optimization -- CN Cluster nodes -- CSO Curved Space Optimization -- CSS Charged System Search -- GA Genetic Algorithm -- GbSA Galaxy-based Search Algorithm -- GLSA Gravitational Local Search -- GWO Grey Wolf Optimization -- GWOCNETs Grey Wolf Optimization Based Clustering In Vehicular Ad-Hoc Networks. -- ITS Intelligent Transportation Systems -- MANET Mobile ad hoc networks -- MOPSO Multi-Objective Particle Swarm Optimization -- PSO Particle swarm optimization -- ROA Ray Optimization Algorithm -- SWOA Small-World Optimization Algorithm -- VANET Vehicular ad hoc networks; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.01.002
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: In vehicular ad-hoc network (VANETs), frequent topology changes occur due to fast moving nature of mobile nodes. This random topology creates instability that leads to scalability issues. To overcome this problem, clustering can be performed. Existing approaches for clustering in VANETs generate large number of cluster-heads which utilize the scarce wireless resources resulting in degraded performance. In this article, grey wolf optimization based clustering algorithm for VANETs is proposed, that replicates the social behaviour and hunting mechanism of grey wolfs for creating efficient clusters. The linearly decreasing factor of grey wolf nature enforces to converge earlier, which provides the optimized number of clusters. The proposed method is compared with well- known meta-heuristics from literature and results show that it provides optimal outcomes that lead to a robust routing protocol for clustering of VANETs, which is appropriate for highways and can accomplish quality communication, confirming reliable delivery of information to each vehicle.