Computation Offloading with Time-Varying Fading Channel in Vehicular Edge Computing

Abstract

Vehicular edge computing (VEC) is considered as a novel paradigm to enhance the safety of automated vehicles and intelligent transportation systems. The computation offloading strategies are the key point of VEC, and the effect of time-varying channel cannot be ignored during the task transmission period. This paper investigates the utility maximization problem with task delay requirement constraints, in which the influence of time-varying channel on the task offloading strategies during the task offloading period is considered. Due to the influence of time-varying channel, location of the vehicle and the allocated bandwidth, the task transmission time is uncertain. In order to deal with it, we first utilize the fixed spectrum efficiency (SE) instead of the time-varying SE, and then propose a linearization based Branch and Bound (LBB) algorithm to solve the fixed SE problem. After that, a fixed SE based heuristic (FSEH) algorithm is proposed to solve the original problem. The simulation results are provided to show that the performance of FSEH algorithm has a small gap of 3.93% only to the upper bound, and increased by 20.8% compared with the Minimum Overhead Offloading Algorithm (MOOA), when the bandwidth grows from 5 MHz to 30 MHz.