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Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud...

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Detalles Bibliográficos
Autores principales: Loganathan, Shyamala, Mukherjee, Saswati
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4587428/
https://www.ncbi.nlm.nih.gov/pubmed/26473166
http://dx.doi.org/10.1155/2015/983018
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author Loganathan, Shyamala
Mukherjee, Saswati
author_facet Loganathan, Shyamala
Mukherjee, Saswati
author_sort Loganathan, Shyamala
collection PubMed
description Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.
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spelling pubmed-45874282015-10-15 Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter Loganathan, Shyamala Mukherjee, Saswati ScientificWorldJournal Research Article Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms. Hindawi Publishing Corporation 2015 2015-09-15 /pmc/articles/PMC4587428/ /pubmed/26473166 http://dx.doi.org/10.1155/2015/983018 Text en Copyright © 2015 S. Loganathan and S. Mukherjee. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Loganathan, Shyamala
Mukherjee, Saswati
Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter
title Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter
title_full Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter
title_fullStr Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter
title_full_unstemmed Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter
title_short Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter
title_sort job scheduling with efficient resource monitoring in cloud datacenter
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4587428/
https://www.ncbi.nlm.nih.gov/pubmed/26473166
http://dx.doi.org/10.1155/2015/983018
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