A Queuing Model To Improve Quality of Service by Reducing Waiting Time in Cloud Computing
G. Vijaya Lakshmi1, C. Shoba Bindhu2
1G. Vijaya Lakshmi, Asst. Pro. Department of Computer Science, Vikrama Simhapuri University Dargamitta, Potti Sreeramulu, Nellore, Andhra Pradesh, India .
2C. Shoba Bindhu, Asst. Pro. Department of Computer Science, Vikrama Simhapuri University Dargamitta, Potti Sreeramulu, Nellore, Andhra Pradesh, India
Manuscript received on November 02, 2014. | Revised Manuscript received on November 04, 2014. | Manuscript published on November 05, 2014. | PP: 1-3 | Volume-4 Issue-5, November 2014. | Retrieval Number: E2384114514/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud computing is an emerging technology to provide cost effective and to deliver the business applications, services in an adaptable way. In cloud computing, multi resources such as processing, bandwidth and storage, need to be allocated simultaneously to multiple users. The When cloud computing users(CCU’S) requests for the service to the cloud computing service providers (CCSP) at the same time but while at a moment, if cloud computing server is busy CCU’s needs to enter into the waiting line until CCSP completes its service to the previous CCU . So this may leads to bottleneck in the network. . Therefore cloud computing users neither utilize the resources nor waits in the queue. Cloud Computing service providers use multiple servers to reduce the waiting time .Therefore, it is necessary to consider a measure for congestion control in cloud computing environment. This paper proposes a (M/M/C): (∞/FIFO) Queuing model which is applied at multiple servers inorder to reduce waiting time , queue length also improving the network performance and QOS effectively in cloud computing environment.
Keywords: Cloud Computing, waiting time, Queuing Theory, QOS.