13-09-2012, 05:24 PM
Optimal service pricing for a cloud cache
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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, resourceeconomic
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
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:
(i) user satisfaction and (ii) 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.
Setting the price for cloud caching services
The cloud makes profit from selling its services at a price
that is higher than the actual cost. Setting the right price
for a service is a non-trivial problem, because when there
is competition the demand for services grows inversely but
not proportionally to the price.
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 pricedemand
dependency, to achieve a feasible pricing solution,
but not oversimplified model that is not representative. For
example, 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.
Our proposal
The cloud caching service can maximize its profit using
an optimal pricing scheme. This work proposes a pricing
scheme along the insight that it is sufficient to use a
simplified price-demand model which can be re-evaluated
in order to adapt to model mismatches, external disturbances
and errors, employing feedback from the real system
behavior and performing refinement of the optimization
procedure. Overall, 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.