Monte Carlo Simulation-Based Robust Workflow Scheduling for Spot Instances in Cloud Environments-Reference-Cited by-同舟云学术

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Monte Carlo Simulation-Based Robust Workflow Scheduling for Spot Instances in Cloud Environments

Published:2024-02 Issue:1 Volume:29 Page:112-126
ISSN:1007-0214
Container-title:Tsinghua Science and Technology
language:
Short-container-title:Tsinghua Sci. Technol.

Author:

Wu Quanwang¹,Fang Jianzhao¹,Zeng Jie²,Wen Junhao³,Luo Fengji⁴

Affiliation:

1. College of Computer Science, Chongqing University,Chongqing,China,400044

2. Chongqing University,National Experimental Teaching Demonstration Center,Chongqing,China,400044

3. College of Big Data and Software Engineering, Chongqing University,Chongqing,China,400044

4. School of Civil Engineering, The University of Sydney,Sydney,Australia,2006

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing

Publisher

Tsinghua University Press

Subject

Multidisciplinary

Link

http://xplorestaging.ieee.org/ielx7/5971803/10225032/10225282.pdf?arnumber=10225282

Reference49 articles.

1. GRP-HEFT: A Budget-Constrained Resource Provisioning Scheme for Workflow Scheduling in IaaS Clouds

2. Deadline-Constrained Cost Optimization Approaches for Workflow Scheduling in Clouds

3. A budget constrained scheduling algorithm for executing workflow application in infrastructure as a service clouds

4. Performance-effective and low-complexity task scheduling for heterogeneous computing

5. Deadline Based Resource Provisioningand Scheduling Algorithm for Scientific Workflows on Clouds

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