A Joint Resource Allocation and Task Offloading Scheme for Energy-aware and Latency Constrained Vehicular Edge Computing Network
WenXuan Gao, Xinjie Yang · 2024
In the Internet of Vehicles, computation-intensive and latency-sensitive applications challenge vehicles’ computational capabilities and processing time. Vehicular Edge Computing(VEC), leveraging idle resource of nearby vehicles and Roadside Units (RSUs), addresses this by enabling collaborative task computing via Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communications. This paper tackles the VEC system’s resource management for performance optimization, focusing on joint resource allocation and task offloading to minimize energy consumption while ensuring task completion. The formulated mixed-integer nonlinear programming problem is decomposed into sub-problems, and an Ant Colony System (ACS), Lagrange multipliers, and gradient methods-based scheme is proposed. Simulations show our scheme outperforms others in reducing task incomplete rate and energy consumption.