Multi-Objective Workflow Scheduling With Deep-Q-Network-Based Multi-Agent Reinforcement Learning

Multi-Objective Workflow Scheduling With Deep-Q-Network-Based Multi-Agent Reinforcement Learning

Cloud Computing provides an effective platform for executing large-scale and complex workflow applications with a pay-as-you-go model. Nevertheless, various challenges, especially its optimal scheduling for multiple conflicting objectives, are yet to be addressed properly. The existing multi-objecti...

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Bibliographic Details
Main Authors: Yuandou Wang, Hang Liu, Wanbo Zheng, Yunni Xia, Yawen Li, Peng Chen, Kunyin Guo, Hong Xie
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Multi-objective workflow scheduling
deep-Q-network (DQN)
multi-agent reinforcement learning (MARL)
infrastructure-as-a-service (IaaS) cloud
quality-of-service (QoS)
Online Access:https://ieeexplore.ieee.org/document/8676306/

Internet

https://ieeexplore.ieee.org/document/8676306/

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