Multiple Objective Fairness Scheduling Optimization Algorithms Based on Multiple DAGs in Heterogeneous Edge Computing

Abstract

The rapid development of edge computing has promoted the growing demand of applications. Quality of service (QoS) must be improved because this index involves issues such as unfairness and short Directed Acyclic Graph (DAG) schedule length. We propose a new algorithm named Multiple DAGs Depth Fairness Task Scheduling (MDDF) in this study to solve the multi-DAG task unfairness problem effectively, the algorithm on the basis of the measured depth of the task in the DAG, improves the fairness of multiple DAG, enhance the user QoS and obtain a fast response. The proposed algorithm is then compared with four common heuristic scheduling methods to verify its effectiveness. We propose another algorithm called Fast Multi-DAG Depth Fairness Task Scheduling (FMDDF) with high average slowdown to reduce the schedule length of short DAG and accelerate the response time. Experimental results show that FMDDF can improve scheduling and shorten the schedule length of short DAG by about 5% and MDDF can enhance fairness by about 2% while reducing the short DAG schedule length compared with other algorithms.