Efficient Resource Provisioning in Cloud Environment in Terms of Profit using Hybrid Load Balancing Algorithm
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2016 by IJCTT Journal | ||
| Volume-36 Number-1 |
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| Year of Publication : 2016 | ||
| Authors : P.Karthika, K.C.Palanisamy | ||
| DOI : 10.14445/22312803/IJCTT-V36P106 |
P.Karthika, K.C.Palanisamy "Efficient Resource Provisioning in Cloud Environment in Terms of Profit using Hybrid Load Balancing Algorithm". International Journal of Computer Trends and Technology (IJCTT) V36(1):32-37, June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Resource provisioning plays a major role in the cloud computing environment due to increased number of cloud users. The user satisfaction level can be improves in the considerable manner by provisioning the resources to the users which can process them with more profit. In this research work, resource provisioning is done with the consideration of the objective called profit. The profit of cloud service providers and as well as users are improved in the considerable manner through the method named as double renting scheme. This double renting method collects the amount for dealing the user request in several way depends on type resource access. The public cloud resources charges for specific amount as like secret cloud resources charged for particular amount. The proposed hybrid load balancing method is used to increase the maximal profit values more significantly rather than the existing system. In this scenario, it shows that the hybrid algorithm insert an important improvements on average response time and profit values. This research provides QoS assured resource selection for the user submitted task in the considerable manner. The experimental tests conducted was proves that the proposed research scenario provides better result than the existing research scenario in terms of increased profit.
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Keywords
SLA parameter, Profit, Resource provisioning, dynamic pricing, Hybrid load balancing.