A DAG Task Scheduling Scheme on Heterogeneous Computing Systems Using Invasive Weed Optimization Algorithm
- Resource Type
- Conference
- Authors
- Li, Kenli; Li, Shuai; Xu, Yuming; Xie, Zhaoxin
- Source
- 2014 Sixth International Symposium on Parallel Architectures, Algorithms and Programming Parallel Architectures, Algorithms and Programming (PAAP), 2014 Sixth International Symposium on. :262-267 Jul, 2014
- Subject
- Computing and Processing
Scheduling
Program processors
Processor scheduling
Clustering algorithms
Algorithm design and analysis
Optimal scheduling
DAG scheduling
Invasive weed optimization
heterogeneous systems
task graphs
genetic algorithms
- Language
- ISSN
- 2168-3034
2168-3042
Efficient task scheduling is crucial to heterogeneous cluster performance. And various scheduling methods based on random search technique have been proposed for both homogeneous and heterogeneous cluster systems. However, most of these methods have high computational overhead and poor convergence. Invasive weed optimization algorithm (IWO) is a novel bionic intelligent optimization algorithm that has fast convergence rate and easier implementation than traditional genetic algorithm (GA) based algorithm. In this paper, an IWO task scheduling (IWOTS) algorithm is proposed for heterogeneous cluster system. To the best of our knowledge, this study is the first time to apply IWO to discrete task scheduling problems. Extensive simulation experiment results show that IWOTS generally exhibits outstanding convergence performance and could produce an optimal scheduling strategy.