Cluster based Data Communication in Sparse and Dense Traffic Condition for Internet of Vehicles

Abstract

Internet of Vehicle (IoV) is the parent class of vehicular ad hoc networks and has gained popularity in this decade due to various types of safety and infotainment applications. It provides comfortability and safety to passengers as well as to the drivers. Most feasible routing protocols are needed to provide in time data communication and handle high mobility of nodes, dynamic topologies and unpredictable environment of these networks. Due to this high mobility of nodes, the nodes are out from its communication range and the information becomes outdated and cause of link disconnections and packet dropping among vehicle nodes. In this thesis, we proposed SACBR (Self-Assessment Cluster Based Routing) in which the CHs are able to communicate with other CHs. Every vehicle node initiates a self-assessment approach based on more appropriate routing metrics and elects the cluster head for every cluster and then cluster head collects the data from member nodes and further forward the data to other cluster heads. The cluster head is responsible to manage its own and member nodes data forwarding process. The proposed protocol provides more stability and less overhead compared to aggregation method where every node exchanges its data with one hop neighbor. This strategy suites in sparse and dense traffic scenario where most of the time vehicle nodes are moving in platoons or in snaking structure. The experimental results show the better performance of SACBR compared to state of the art protocols.