An Energy Optimized Clustering approach for Communication in Vehicular Cloud Systems

Vehicular cloud networks are considered to possess faster transitional topology and mobility thereby adhering to its features as an ad hoc network. Many times, it is difficult to monitor vehicular nodes that results in internetworking concerns as a result of power inadequacy during real computation. This leads to lots of energy wastage issues encountered during routing which degrades lifetime of nodes. Thus in this study a new clustering based energy optimization method is proposed to enhance the efficiency of vehicular communication. K-medoid cluster analysis along with dragonfly approach is applied to the system model to optimize energy. On the basis of simulation undertaken, it is recorded that the network lifetime, packets delivered, processing delay and throughput are increased using the proposed model.