Limits...
Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter.

Loganathan S, Mukherjee S - ScientificWorldJournal (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Science and Technology, Anna University, Tamil Nadu 600025, India.

ABSTRACT
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.

No MeSH data available.


Modified best fit with capacity based scheduling (MBFCBS).
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Related In: Results  -  Collection


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alg1: Modified best fit with capacity based scheduling (MBFCBS).

Mentions: The objective of the scheduler is to maximize the resource utilization by allocating earliest available hosts by reducing the number of hosts. To maximize the resource utilization, we have proposed the modified best fit with capacity based scheduling (MBFCBS) algorithm which is shown in Algorithm 1. Since AR/IM jobs can preempt BE jobs, the only case where an AR/IM job is rejected is that most of the resources are reserved by some other AR at the required time, and insufficient resources are left for this job. If there are n numbers of VMs executing on a host with different finish time, then a new request is scheduled on the same host provided that the capacity of the finishing VM is greater than or equal to the new requested VM.


Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter.

Loganathan S, Mukherjee S - ScientificWorldJournal (2015)

Modified best fit with capacity based scheduling (MBFCBS).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4587428&req=5

alg1: Modified best fit with capacity based scheduling (MBFCBS).
Mentions: The objective of the scheduler is to maximize the resource utilization by allocating earliest available hosts by reducing the number of hosts. To maximize the resource utilization, we have proposed the modified best fit with capacity based scheduling (MBFCBS) algorithm which is shown in Algorithm 1. Since AR/IM jobs can preempt BE jobs, the only case where an AR/IM job is rejected is that most of the resources are reserved by some other AR at the required time, and insufficient resources are left for this job. If there are n numbers of VMs executing on a host with different finish time, then a new request is scheduled on the same host provided that the capacity of the finishing VM is greater than or equal to the new requested VM.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Information Science and Technology, Anna University, Tamil Nadu 600025, India.

ABSTRACT
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.

No MeSH data available.