DCGCR: Dynamic Clustering Green Communication Routing for Intelligent Transportation Systems

For the effective green communications amongst the vehicles, the energy-efficient routing protocol for intelligent transportation system (ITS) is essential. Due to the high speed and recurring topological variations of Vehicular sensor Networks, identifying a connected route with a sufficient latency is a difficult task with many constraints and obstacles. Therefore, to overcome this, we developed the statistical approach to theoretically determine the load congestion and consumption of energy during the lifetime of the sensor network for ITS. Hence, dynamic clustering green communication routing (DCGCR) protocol is proposed for vehicular communication. To manage energy consumption and enhance the lifetime of the network deployed on the roadside units (RSU), we analyze the evolution of energy holes and apply our analytical conclusions for ITS with WSN routing. The proposed routing protocol considers various metrics: i) energy consumption of vehicular sensor nodes,ii) network stability iii) reliability and iv) amount of data exchange among vehicles. The efficiency of the proposed computational model in calculating the lifetime of the vehicular network and energy hole evolution process is demonstrated through extensive computation results. DCGCR approach is compared with the various energy-aware routing algorithms namely, Dynamic Energy Balanced Routing (DEBR), Geographic Greedy Routing (GGR), double cost function-based routing (DCFR) and found that proposed approach achieves more accuracy with 7% less failure rate.

Automated summary

For effective green communications amongst vehicles, the proposed dynamic clustering green communication routing (DCGCR) protocol considers various metrics such as energy consumption, network stability, reliability, and data exchange among vehicles. The protocol overcomes the difficulties of identifying a connected route with sufficient latency in Vehicular Sensor Networks and offers computational efficiency in determining load congestion and energy consumption. Compared to other energy-aware routing algorithms, the DCGCR approach achieves higher accuracy with a 7% reduction in failure rate.