Effective Resource Utilization for Caching as a Service in Cloud
Samir S. Rathod1, G. Niranjana2
1Mr. Samir .S. Rathod, Department of Computer Science and Engineering, SRM University, Chennai, India.
2Asst Prof. G .Niranjana, Department of Computer Science and Engineering, SRM University, Chennai, India.
Manuscript received on March 24, 2014. | Revised Manuscript received on April 19, 2014. | Manuscript published on April 30, 2014. | PP: 174-178 | Volume-3, Issue-4, April 2014. | Retrieval Number: D2949043414/2013©BEIESP
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© The Authors. 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: With the growing popularity of cloud based data centers as the enterprise IT platform of choice, there is a need for effective management strategies capable of maintaining performance. Caching technology improves the performance of the cloud. Cache as a service (CaaS) model is an additional service to Infrastructure as a service (IaaS). The cloud server process introduce, pricing model together with the elastic cache system. This will increase the disk I/O performance of the IaaS, and it will reduce the usage of the physical machines. The emerging cloud applications provide data management services allowing the user to query the cloud data, paying the price for the infrastructure they use. Cloud management necessitate an economy that manages the services of multiple users in an efficient, but also, resource economic way that allows for cloud profit. The cloud caching service can maximize its profit using an optimal pricing scheme. This scheme requires an appropriately simplified price-demand model that incorporates the correlations of structures in the cache services. The pricing scheme should be adaptable to time changes. This paper proposes a novel price demand model designed for a cloud cache and a dynamic pricing scheme for queries executed in the cloud cache. This will estimates the correlations of the cache services in a time-efficient manner and improve the efficiency of resources in cloud storage infrastructure to deliver scalable service.
Keywords: Cloud Computing, CaaS model, Virtual Machine, Remote Memory, Optimal pricing scheme.