An Improved Task Duplication based Clustering Algorithm for DAG Task Scheduling in Heterogenous and Distributed Systems

• Published in: Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics pp. 878 - 883
• Main Authors: Fan, Wei, Zhu, Jie, Ding, Kexin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09.10.2022
• Subjects: Clustering algorithms; DAG scheduling; Directed acyclic graph; Greedy algorithms; heterogenous environment; Processor scheduling; Robustness; Schedules; Scheduling; task clustering; task dupliction
• ISSN: 2577-1655
• DOI: 10.1109/SMC53654.2022.9945255

Task scheduling in heterogenous and distributed systems for the directed acyclic graph (DAG) based applications has been widely studied. In DAG task scheduling problems, a set of distributed tasks with dependencies are dispatched to appropriate computing instances. The objective is to obtain the feasible schedule with the minimal schedule length, i.e., makespan. In this paper, we propose a task duplication based clustering framework for the problem under study. We employ the task duplication scheme in the framework which allows task clusters contain duplicated tasks in order to reduce the communication cost. A selection matrix is introduced to record the candidate tasks to generate clusters. Multiple feasible task clustering solutions are obtained based on the selection matrix and among which the best one with the minimal makespan is output. Experimental results indicate that the proposal outperforms compared algorithms on both effectiveness and robustness.