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An adaptive algorithm for scheduling parallel jobs in meteorological Cloud

  • Published:2016-04 Issue: Volume:98 Page:226-240
  • ISSN:0950-7051
  • Container-title:Knowledge-Based Systems
  • language:en
  • Short-container-title:Knowledge-Based Systems

Author:

Hao YongshengORCID,Wang Lina,Zheng Mai

Funder

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSF)

Jiangxi Normal University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference38 articles.

1. A high performance scientific cloud computing environment for materials simulations;Jorissen;Comput. Phys. Commun.,2012

2. Extended forecast of CPU and network load on computational Grid;Akioka,2004

3. Optimizing execution time predictions of scientific workflow applications in the Grid through evolutionary programming;Nadeem;Future Gener. Comput. Syst.,2013

4. An evaluation of nine heuristic algorithms with data-intensive jobs and computing-intensive jobs in a dynamic environment;Hao;IET softw.,2015

5. A cost-effective scheduling algorithm for scientific workflows in clouds;Zhu,2012

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1. Meteorological data layout and task scheduling in a multi-cloud environment;Engineering Applications of Artificial Intelligence;2023-11

2. Hyper-Heuristic Task Scheduling Algorithm Based on Reinforcement Learning in Cloud Computing;Intelligent Automation & Soft Computing;2023

3. Data Layout and Scheduling Tasks in a Meteorological Cloud Environment;Intelligent Automation & Soft Computing;2023

4. Cooperative and non-cooperative algorithms for distributed parallel jobs scheduling;Flexible Services and Manufacturing Journal;2022-09-22

5. Energy-aware offloading based on priority in mobile cloud computing;Sustainable Computing: Informatics and Systems;2021-09
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