An optimized energy management and load balancing system based on cluster head selection for the vehicular network communication.

Wireless Sensor Network (WSN) is a well-organizing network that provides efficient communication services. However, high energy usage and overloaded data sometimes become the key challenges that degrade the entire network's performance. Energy management and load balancing are critical processes for increasing the network lifespan. Therefore, in the present research, a novel Aquila-based Radial Basis Model (AbRBM) is created for vehicular network communication to reduce energy usage and balance the load with the CH selection. Initially, the required nodes are deployed in the network. Based on Aquila's optimal functions, the higher energy nodes are monitored and removed; optimal CH is selected for the data transfer. Finally, the load is balanced by sharing the data between the overhead and the rest of the nodes. The created framework was tested in the NS2 environment, and the network efficiency parameters were calculated. The model achieved a 98.3% Packet delivery rate, 1.10 mJ of average energy usage rate, 0.025-s delay, 3.8Mbps average throughput, and lifetime as 6210 rounds for the created 100 nodes in the WSN. Also, the control overhead rate is reduced to 0.42 KB. To validate the improvement, the results are related to the existing models. The higher Performance of the AbRBM satisfied the network's efficient energy management and load-balancing process. The model provided an efficient and reliable WSN for various applications. [ABSTRACT FROM AUTHOR]