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A Profit Maximization Scheme for Enhancing Quality of Service (QoS) in Cloud Computing
Author(s) -
P. Poonam,
D. Sudha Devi
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016910812
Subject(s) - computer science , cloud computing , quality of service , profit maximization , scheme (mathematics) , maximization , service quality , profit (economics) , computer network , service (business) , distributed computing , mathematical optimization , operating system , business , mathematical analysis , mathematics , marketing , economics , microeconomics
Internet basis computing that is depending upon on-demand work is called as Cloud computing. Cloud computing provides shared resources as well as data over the network to user on the basis of his demand. Cloud computing has very essential part that is called as the cloud economics analysis. In cloud economics, work of enhancement of profit is accomplished. Large benefit is the most essential aspect as correspondence with cloud service providers and also depending upon markets demand through the management of cloud service platform it is compelled. Initially, determination of the cost as well as revenue for increasing the profit is very essential. The user satisfaction in profit increment is additionally considered as the cost of the cloud. Under the cost, both the renting cost as well as energy utilization cost also considered. To increase the profit there is must decrease the cost. To minimize the cost have to configure the server accurately. At the time of server configuration, computing is done over the assumed waiting time as well as service charge. Existing cloud providers was utilized a single long-term strategy to setup cloud platform. But this single long-term renting strategy has the issue of unable to provide the service with the high quality and additionally leads wasting the resources. To solve this issue, a system called Double resource Renting (RR) is developed. This concept includes the both short term as well as long-term renting methodologies. Double resource renting methodology ensures the quality of service and minimizes the wastage of resources. Previous system also implemented double renting system, but only for the homogeneous cloud scenario. By comparing both heterogeneous as well as homogeneous environment, the study says that a heterogeneous environment is most difficult. So, to solve this drawback, proposed system is working over a heterogeneous environment.

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