Energy Efficient Partitioning and Scheduling Approach for Scientific Workflows in the Cloud
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/7557343/7557418/07557447.pdf?arnumber=7557447
Cited by 15 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. A Systematic Mapping Study of Italian Research on Workflows;Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis;2023-11-12
2. Parallelizing Quantum-Classical Workloads: Profiling the Impact of Splitting Techniques;2023 IEEE International Conference on Quantum Computing and Engineering (QCE);2023-09-17
3. Energy-Efficient Scientific Workflow Scheduling Algorithm in Cloud Environment;Wireless Communications and Mobile Computing;2022-03-14
4. GMTA: A Geo-Aware Multi-Agent Task Allocation Approach for Scientific Workflows in Container-Based Cloud;IEEE Transactions on Network and Service Management;2020-09
5. Energy and resource efficient workflow scheduling in a virtualized cloud environment;Cluster Computing;2020-07-23
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