An efficient hierarchical clustering protocol for multihop Internet of vehicles communication

• Published in: Transactions on emerging telecommunications technologies Vol. 31; no. 5
• Main Authors: Dutta, Ashit Kumar, Elhoseny, Mohamed, Dahiya, Vandna, Shankar, K.
• Format: Journal Article
• Language: English
• Published: 01.05.2020
• ISSN: 2161-3915; 2161-3915
• DOI: 10.1002/ett.3690

Presently, Internet of vehicles (IoV) offers promising solutions to upgrade the traditional vehicular ad‐hoc networks (VANETs) to the next level. Since the resources are highly constrained on available resources, clustering is generally employed in VANETs. In this paper, we introduce an efficient hierarchical clustering protocol (EHCP) for multihop communication for effective resource utilization and thereby enhance the network lifetime. The proposed EHCP assumes that the vehicles are linked to the Internet using road‐side unit gateway. When the vehicles are linked to the Internet, every vehicle gathers information about its neighboring nodes and performs the clustering process to select appropriate cluster heads. The presented EHCP is simulated in NS‐2 and the VanetMobiSim integrated environment. The outcomes are analyzed in terms of different measures such as network lifetime, overhead, delay, and delivery ratio. The presented method achieved maximum packet delivery ratio of 0.94 under the high vehicle density of 180. The experimental values ensured the superior performance of the EHCP over the compared methods such as n‐hop and distributed multihop clustering using a neighborhood follow algorithm in a significant manner. This paper introduces an efficient hierarchical clustering protocol (EHCP) for multihop communication for effective resource utilization and thereby enhance the network lifetime. When the vehicles are linked to the Internet, every vehicle gathers information about its neighboring nodes and performs the clustering process to select appropriate cluster heads. The experimental values ensured the superior performance of the EHCP over the compared methods such as n‐hop and distributed multihop clustering using a neighbourhood follow algorithm in a significant manner.