Deep Reinforcement Learning for Dynamic Workflow Scheduling in Cloud Environment-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning for Dynamic Workflow Scheduling in Cloud Environment

Published:2021-09 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Services Computing (SCC)
language:
Short-container-title:

Author:

Dong Tingting,Xue Fei,Xiao Changbai,Zhang Jiangjiang

Funder

Ministry of Education

Beijing Intelligent Logistics System Collaborative Innovation Center

Beijing Wuzi University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9592361/9592191/09592509.pdf?arnumber=9592509

Cited by 6 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. Deep reinforcement learning-based scheduling in distributed systems: a critical review;Knowledge and Information Systems;2024-06-26

2. Hybrid Edge-Cloud Collaborator Resource Scheduling Approach Based on Deep Reinforcement Learning and Multiobjective Optimization;IEEE Transactions on Computers;2024-01

3. A survey study on task scheduling schemes for workflow executions in cloud computing environment: classification and challenges;The Journal of Supercomputing;2023-12-07

4. Data-intensive workflow scheduling strategy based on deep reinforcement learning in multi-clouds;Journal of Cloud Computing;2023-08-26

5. A novel seq2seq-based prediction approach for workflow scheduling;Cluster Computing;2023-06-11

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