Author:
Long Saiqin,Dai Xin,Pei Tingrui,Cao Jiasheng,Sekiya Hiroo,Choi Young-June
Funder
Education Department of Hunan Province
National Natural Science Foundation of China
Hunan Provincial Science and Technology Department
Hunan Provincial Natural Science Foundation
National Key Laboratory Foundation of China
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications
Reference36 articles.
1. Optimizing energy consumption for data centers;Rong;Renew. Sustain. Energy Rev.,2016
2. Multi-objective task and workflow scheduling approaches in cloud computing: a comprehensive review;Hosseinzadeh;J. Grid Comput.,2020
3. Q. Huang, S. Su, J. Li, P. Xu, K. Shuang, X. Huang, Enhanced energy-efficient scheduling for parallel applications in cloud, in: 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012), IEEE, 2012, pp. 781–786.
4. Performance-effective and low-complexity task scheduling for heterogeneous computing;Topcuoglu;IEEE Trans. Parallel Distrib. Syst.,2002
5. Interconnection network energy-aware workflow scheduling algorithm on heterogeneous systems;Tang;IEEE Trans. Industr. Inf.,2019
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. ESSA Scheduling Algorithm for Optimizing Budget-Constrained Workflows;2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME);2022-11-16