A novel QoS-aware mechanism for provisioning of virtual machine resource in cloud. Issue 3 (September 2016)

• Record Type: Journal Article
• Authors: Feng, Ye; Zhijian, Wang; Qian, Huang
• Other Names: Xhafa Fatos guest-editor.; Wang Xu An guest-editor.
• Is Part Of: Journal of algorithms & computational technology. Volume 10:Issue 3(2016)
• Page Start: 169
• Page End: 175
• Publication Date: 2016-09
• Subjects: Virtual machine -- QoS -- provisioning -- CloudSim; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/1748301816649077
• Languages: English
• ISSNs: 1748-3018

Abstract

Efficient low-level resource provisioning and QoS guaranteed are key challenges for cloud computing. Solving such kind of problem can reduce under- or over-utilization of resources, increase users' satisfaction by serving more users during peak hours, and cut down implementation cost for providers and service cost for users. The existing research works focus on the accurate estimation of the capacity needs, static or dynamic virtual machines creation and scheduling. But significant amount of time is required to create and destroy virtual machines which can be used to serve more requests. In this paper, a novel adaptive QoS-aware virtual machine provisioning mechanism is developed that ensures efficient utilization of the system resources. The VM for similar type of requests has been recycled so that the VM creation time can be minimized and used to serve more user requests. In the proposed model, QoS is linked by a low-level infrastructure resource and is ensured by serving all the tasks within the requirements described in SLA. Tasks are separated using queues and different task is given different tasks are assigned into different queue according to their priority. The CloudSim-based simulation experimental results show that a great number of tasks can be served more effectively compared to others which will help to satisfy customers during the peak hour.