Dependency-aware Task Scheduling and Cache Placement in Vehicular Networks

Abstract

Mobile Edge Computing (MEC) enables vehicles to flexibly obtain computing, content storage and other services by deploying at the network edge, which is of great research significance. The application tasks in vehicular networks can be distributed to MEC or task vehicle for collaborative processing. Aiming at the situation that the task dependency graph with multiple corresponding relationships is represented by Directed Acyclic Graph (DAG), this paper considers caching the program data of the corresponding node, and explores the problem of task scheduling and resource allocation in the cache enhancement scenario. Firstly, the task scheduling and cache placement decision are modeled as the optimization problem of minimizing the completion time. Then, through the analysis of the optimization problem, the problem is divided into two sub problems: task scheduling and cache decision. For the two sub problems, the task scheduling algorithm based on the latest start time and the cache decision algorithm based on dynamic programming are designed respectively. Simulation results show that the proposed algorithms and scheme can significantly reduce the completion time and task failure rate compared with the benchmark scheme.