Online Offloading Scheduling and Resource Allocation Algorithms for Vehicular Edge Computing System

Abstract

To accommodate the exponentially increasing computation demands of vehicle-based applications, vehicular edge computing (VEC) system was introduced. This paper considers a three-layer VEC architecture and proposes an online offloading scheduling and resource allocation (OOSRA) algorithm to improve the system performance. Specifically, this study designs a game-theoretic online algorithm to solve the problem of computation task offloading scheduling, and employs an online bin-packing algorithm to compute the resource allocation modified from the First Fit algorithm, which can be adapted to various traffic flow and service attributes. Extensive simulations are conducted, and a numerical analysis of simulation results verifies the effectiveness of the OOSRA-VEC system. The algorithms proposed in this paper are online, adaptive, and distributed, which can provide useful references for future development in VEC system protocols.