Performance measure of multi stage scheduling algorithm in cloud computing

Indukuri, R Krishnam Raju; Varma, P. Suresh; Gummadi, Jose Moses

doi:10.1109/iccctam.2012.6488062

Cited by 5 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several research works addressed the importance of placing VMs appropriately. Recently in works [2] and [3] two stage scheduling model is designed and developed for allocation of resources in cloud to the incoming jobs in the form of Virtual machines. Load balancing affects cloud computing and improves the performance by re-distributing the load among the computing resources.…”

Section: Introductionmentioning

confidence: 99%

Design and Development of Efficient Cloud Scheduling Algorithm based on Load Balancing Analytics

Sridevi¹,

Varma²,

Krishna³

2016

IJCA

View full text Add to dashboard Cite

Cloud computing involves sharing computing resources rather than having individual servers or personal devices to handle applications. Cloud computing architectures include the delivery of software, infrastructure, storage and technology enabled services over internet to the people and organizations on demand. Cloud scheduling is the process of allocating resources to the job requests in the form of Virtual Machines. In this paper we designed and developed a novel, efficient cloud scheduling algorithm based on load balancing analytics for allocation of physical resources in the form of virtual machine to the incoming job requests. In this paper we measured various cloud performance metrics like mean turnaround time and mean waiting time. The results obtained with this method compared with traditional methods like First Come First Serve (FCFS), two stage scheduling algorithms and observed considerable increase in the performance Metrics.

show abstract

Section: Introductionmentioning

confidence: 99%