Energy-Efficient Scientific Workflow Scheduling Algorithm in Cloud Environment

Scheduling extensive scientific applications that are deadline-aware (usually referred to as workflow) is a difficult task. This research provides a virtual machine (VM) placement and scheduling approach for effectively scheduling process tasks in the cloud environment while maintaining dependency a...

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Bibliographic Details
Published in:Wireless communications and mobile computing Vol. 2022; no. 1
Main Authors: Garg, Neha, Neeraj, Raj, Manish, Gupta, Indrajeet, Kumar, Vinay, Sinha, G. R.
Format: Journal Article
Language:English
Published: Oxford Hindawi 2022
John Wiley & Sons, Inc
Subjects:
Algorithms
Bandwidths
Cloud computing
Energy consumption
Placement
Random access memory
Scheduling
Servers
Software
Task scheduling
Telescopes
Virtual environments
Workflow
ISSN:1530-8669, 1530-8677
Online Access:Get full text
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Summary:Scheduling extensive scientific applications that are deadline-aware (usually referred to as workflow) is a difficult task. This research provides a virtual machine (VM) placement and scheduling approach for effectively scheduling process tasks in the cloud environment while maintaining dependency and deadline constraints. The suggested model’s aim is to reduce the application’s energy consumption and total execution time while taking into account dependency and deadline limitations. To select the VM for the tasks and dynamically deploy/undeploy the VM on the hosts based on the jobs’ requirements, an energy-efficient VM placement (EVMP) algorithm is presented. Demonstrate that the proposed approach outperforms the existing PESVMC (power-efficient scheduling and VM consolidation) algorithm.
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ISSN:1530-8669
1530-8677
DOI:10.1155/2022/1637614