Integrating Cognition Cost With Reliability QoS for Dynamic Workflow Scheduling Using Reinforcement Learning-Reference-Cited by-同舟云学术

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Integrating Cognition Cost With Reliability QoS for Dynamic Workflow Scheduling Using Reinforcement Learning

Published:2023-07-01 Issue:4 Volume:16 Page:2713-2726
ISSN:1939-1374
Container-title:IEEE Transactions on Services Computing
language:
Short-container-title:IEEE Trans. Serv. Comput.

Author:

Yu Xiaoming¹^ORCID,Wu Wenjun¹,Wang Yangzhou¹

Affiliation:

1. State Key Lab of Software Development, Beihang University, Beijing, China

Funder

National Key R&D Program of China

State Key Laboratory of Software Development Environment

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/4629386/10213383/10061217.pdf?arnumber=10061217

Reference34 articles.

1. A novel directional and non-local-convergent particle swarm optimization based workflow scheduling in cloud–edge environment

2. Optimal scheduling workflows in cloud computing environment using Pareto-based Grey Wolf Optimizer

3. PSO-DS: a scheduling engine for scientific workflow managers

4. Multi-objective workflow scheduling in cloud system based on cooperative multi-swarm optimization algorithm

5. A multi-objective workflow scheduling algorithm for cloud environment;singh;Proc 3rd Int Conf Internet Things Smart Innov Usages,2018

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1. Entropy Weight Method-Based Multi-Attribute Decision-Making for Web Service Selection;2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS);2024-05-17

2. Clustering-assisted gradient-based optimizer for scheduling parallel cloud workflows with budget constraints;The Journal of Supercomputing;2024-04-23

3. Pattern learning for scheduling microservice workflow to cloud containers;International Journal of Machine Learning and Cybernetics;2024-03-16

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