Heuristics-Based Clustering of Internet of Vehicle Based on Effective Approximate QoS Guideline for Message Dissemination

Internet of Things and connected world concepts are emerging foreground in all walks of life, and Internet of Vehicles (IoV) is a natural evolution of these concepts for a connected vehicular environment. Clustering is needed in the IoV network for effective management of network resources and to avoid congestion in the network. On the effective cluster base, any efficient routing protocol can be realized for message dissemination. In most of the existing work, clustering based on multiple mobility metrics is the first step, followed by routing over established clusters. This work proposes a clustering solution without the need for frequent clustering or reduced cluster maintenance effort. The proposed solution establishes a virtual QoS guideline path for message dissemination based on graph theory as a first step, and clustering of the network is done to further improve the QoS in the guideline path using a heuristic algorithm. The proposed solution demonstrates notable improvements over existing approaches. Specifically, it achieves an average cluster duration that is at least 6% higher and reduces cluster maintenance overhead by 7%. In terms of Quality of Service (QoS), the solution attains a 3.6% higher packet delivery ratio, along with a 21% reduction in end-to-end delay and a 28% decrease in routing overhead.