OPTIMAL SERVICE PRICING FOR A CLOUD CACHE

OPTIMAL SERVICE PRICING FOR A CLOUD CACHE

ABSTRACT:

Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. 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. 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. 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.

INTRODUCTION:

Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. 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. 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. 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

The leading trend for service infrastructures in the IT domain is called cloud computing, a style of computing that allows users to access information services. Cloud providers trade their services on cloud resources for money. The quality of services that the users receive depends on the utilization of the resources.

The operation cost of used resources is amortized through user payments. Cloud resources can be anything, from infrastructure (CPU, memory, bandwidth, network), to platforms and applications deployed on the infrastructure. Cloud management necessitates an economy, and, therefore, incorporation of economic concepts in the provision of cloud services.

The goal of cloud economy is to optimize: 1) user satisfaction and 2) cloud profit. While the success of the cloud service depends on the optimization of both objectives, businesses typically prioritize profit. To maximize cloud profit we need a pricing scheme that guarantees user satisfaction while adapting to demand changes.

 Recently, cloud computing has found its way into the provision of web services, Information, as well as software is permanently stored in Internet servers and probably cached temporarily on the user side.

Current businesses on cloud computing such as Amazon Web Services and Microsoft Azure have begun to offer data management services: the cloud enables the users to manage the data of back-end databases in a transparent manner. Applications that collect and query massive data, like those supported by CERN , need a caching service, which can be provided by the cloud. The goal of such a cloud is to provide efficient querying on the back-end data at a low cost, while being economically

viable, and furthermore, profitable.

SYSTEM ARCHITECTURE

EXISTING SYSTEM:

Existing clouds focus on the provision of web services targeted to developers, such as Amazon Elastic Compute Cloud (EC2), or the deployment of servers, such as Go Grid.

There are two major challenges when trying to define an optimal pricing scheme for the cloud caching service. The first is to define a simplified enough model of the price demand dependency, to achieve a feasible pricing solution, but not oversimplified model that is not representative.

A static pricing scheme cannot be optimal if the demand for services has deterministic seasonal fluctuations. The second challenge is to define a pricing scheme that is adaptable to

(i)                 Modeling errors,

(ii)               Time-dependent model changes, and

(iii)             Stochastic behavior of the application.

Disadvantage:

Ø  A static pricing scheme cannot be optimal if the demand for services has deterministic seasonal fluctuations.

Ø  Static pricing results in an unpredictable and, therefore, uncontrollable behavior of profit.

PROPOSED SYSTEM:

The cloud caching service can maximize its profit using an optimal pricing scheme. Optimal pricing necessitates 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.

Advantages:

Ø  A novel demand-pricing model designed for cloud caching services and the problem formulation for the dynamic pricing scheme that maximizes profit and incorporates the objective for user satisfaction.

Ø   An efficient solution to the pricing problem, based on non-linear programming, adaptable to time changes.

Ø  A correlation measure for cache structures that is suitable for the cloud cache pricing scheme and a method for its efficient computation.

Ø  An experimental study which shows that the dynamic pricing scheme out-performs any static one by achieving 2 orders of magnitude more profit per time unit.