TY - JOUR
AU1 - Zhang, Shunli
AB - With the rapid development and application of driverless technology, the number and location of vehicles, the channel and bandwidth of wireless network are time-varying, which leads to the increase of offloading delay and energy consumption of existing algorithms. To solve this problem, the vehicle terminal task offloading decision problem is modelled as a Markov decision process, and a task offloading algorithm based on DDQN is proposed. In order to guide agents to quickly select optimal strategies, this paper proposes an offloading mechanism based on task feature. In order to solve the problem that the processing delay of some edge server tasks exceeds the upper limit of their delay, a task scheduling mechanism based on buffer delay is proposed. Simulation results show that the proposed method has greater performance advantages in reducing delay and energy consumption compared with existing algorithms.
TI - Feature-aware task offloading and scheduling mechanism in vehicle edge computing environment
JF - International Journal of Vehicle Information and Communication Systems
DO - 10.1504/ijvics.2024.142101
DA - 2024-01-01
UR - https://www.deepdyve.com/lp/inderscience-publishers/feature-aware-task-offloading-and-scheduling-mechanism-in-vehicle-edge-Vu19aXcJip
SP - 415
EP - 433
VL - 9
IS - 4
DP - DeepDyve
ER -