Special Issue Article Open Access

Optimization of Content Downloading Using Dynamic Cache Memory

Abstract

Cloud applications that offer data management services are emerging in vehicular networks. Such clouds support caching of data in order to provide quality query services in vehicles. The connection to cloud server is automatically transferred to the next connection point in the vehicle travels. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service of multiple users in an efficient, but also, resource economic way that allows for cloud profit. Naturally, the maximization of cloud profit given some guarantees for user satisfaction presumes an appropriate price-demand model that enables optimal pricing of query services. The model should be plausible in that it reflects the correlation of cache structures involved in the queries. Optimal pricing is achieved based on a dynamic pricing scheme that adapts to time changes. It proposes a novel price-demand model designed for a cloud cache and a dynamic pricing scheme for queries executed in the cloud cache. The pricing solution employs a novel method that estimates the correlations of the cache services in an time-efficient manner. The experimental study shows the efficiency of the solution.

Ms.A.Gayathri, Ms.M.M.Chithra, Ms.R.Jeyashree, Mr.A.Premkumar

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