A REVIEW ON ENERGY OPTIMIZATION FOR 5G-ENABLED VEHICULAR SENSOR NETWORKS: STRATEGIES FOR ENHANCING BATTERY LIFE

Abstract

An innovative method for boosting the capabilities of intelligent transportation systems is the incorporation of Vehicular Sensor Networks (VSNs) into fifth-generation (5G) communication infrastructures. The integration of automobiles, infrastructure, and smart gadgets in a single ecosystem made possible by 5G technologies is highlighted in this paper's thorough analysis of the Internet of Vehicles (IoV). Device-to-Device (D2D) communication, which provides low-latency, high-reliable data transmission and satisfies the scalability requirements of vehicular networks. In order to increase battery efficiency and network lifespan, the study looks into a variety of energy optimization techniques. These strategies include reinforcement learning models, clustering-based routing protocols, and hybrid metaheuristic algorithms like grey wolf and dragonfly-firefly optimization. The research highlights the trade-offs and difficulties in striking a balance between energy economy, network throughput, and communication dependability in Wireless Sensor Networks(WSN) by critically synthesizing previous works. As the industry moves toward autonomous and cooperative vehicular systems, the results highlight the need for flexible, intelligent resource management strategies in the design of energy-aware VSNs.

Keywords: Wireless Sensor Networks, Vehicular Sensor Networks, 5G, Device-to-Device Communication, Energy Efficiency, Internet of Vehicles, Clustering, Optimization Algorithms.