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Review of pricing models for grid & cloud computing

Distributed system resources have become prevalent in ICT departments to lessen the burden of huge expenses incurred by very expensive storage computer systems. Add to this the continuous introduction and ever-growing evolution of simple to complex applications, the demand to access huge quantities...

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Bibliographic Details
Main Authors: Samimi, P., Patel, A.
Format: Conference Proceeding
Language:English
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Summary:Distributed system resources have become prevalent in ICT departments to lessen the burden of huge expenses incurred by very expensive storage computer systems. Add to this the continuous introduction and ever-growing evolution of simple to complex applications, the demand to access huge quantities of data, intensive computations, powerful simulations, maintaining and offering system resources and middleware infrastructure services the need to do all of this at an affordable and reasonable price is crucial. Distributed grid and cloud computing resources are currently considered to be one of the best technology options to provide this. They have many similar features and functions, and both of them are classed as distributed systems. They are capable of offering unaffordable resources and services at a reasonable price in a mass marketplace. The big question is: what is a reasonable price? How is pricing modeled and on what kind of economic principles is it based? Much of the issues surrounding these questions are very complex in themselves. This paper provides a comparative review of grid and cloud computing economic and pricing models from which appropriate tariffs and charging models can be chosen to meet particular business objectives. The actual choice depends on many other factors like enterprise regulations, tax laws, service level agreements and return on investments, are very important but outside the scope of this paper. In this paper we give the basic core principles and a comparative review of the latest and most appropriate economic and pricing models applicable to grid and cloud computing in order to propose better models for the future.
DOI:10.1109/ISCI.2011.5958990