Ramya.R
Cloud applications are evolving that offer data management services. The applications that involved in heavy I/O activities in the Cloud Technology, utilizes most of the services from Caching. Caching the data may be either spatial data or temporal data. The Local volatile memory might be an alternative support for Cache, but the capacity and the utilization of host machines reduces its usage. The existing system provided the Cache as a Service (CaaS) model as an additional service along with Infrastructure as a Service (IaaS). Particularly, the Cloud Provider sets a large collection of memory that can be dynamically separated and allocated to standard infrastructure services as Disk cache. An effective cache mechanism known as the elastic cache system provides the feasibility of CaaS using dedicated remote memory servers. The novel pricing scheme provides the maximization of cloud profit which gives the guarantee for user satisfaction. The performance degradation occurs due to increasing in the utilization of Energy. The proposed system utilizes Virtual Machines (VM) and doing server consolidation in a data center, by which a Cloud provider can reduce the total Energy consumption for servicing the clients as well as increasing the resource availability in the data center. Multiple copies of VMs are created and place these copies on the servers by using dynamic programming to reduce the total energy consumption. The communication parameters such as latency, bandwidth, and distance are considered in making the decision of assigning VMs to the servers. The algorithm is implemented with the help of the simulation tool (CloudSim) and the result obtained from this reduces the energy utilization and also increases the performance