Minimizing Energy Consumption in Vehicular Sensor Networks Using Relentless Particle Swarm Optimization Routing

Abstract

– Increasing traffic issues, particularly in highly populated nations, have prompted recent interest in Vehicular Sensor Networks (VSNETs) from academics in several fields. Accident rates continue to rise, highlighting the need for a highly functional Smart Transport System (STS). Improvements to the STS should not be spread thin across the board but should concentrate on improving traffic flow, maintaining system reliability, and decreasing vehicle carbon dioxide and methane emissions. Current routing protocols for VSNETs consider various scenarios and approaches to provide safe and effective vehicle-to-infrastructure communication. The reliability of vehicle connections during data transmission has not been well explored. This paper proposes a Relentless Particle Swarm Optimization based Routing Protocol (RPSORP) for VSNET to use vehicle kinematics and mobility to identify vehicle location, send routing information packets to road-side devices, and choose the most reliable path for travel. RPSORP optimizes local and global search to minimize energy consumption in VSNET. The RPSORP is evaluated in the GNS3 simulator using Throughput, Packet Delivery, Delay, and Energy Consumption metrics. RPSORP has superior performance than state-of-the-art routing protocols.