5 research outputs found
Simple Pricing Schemes for the Cloud
The problem of pricing the cloud has attracted much recent attention due to
the widespread use of cloud computing and cloud services. From a theoretical
perspective, several mechanisms that provide strong efficiency or fairness
guarantees and desirable incentive properties have been designed. However,
these mechanisms often rely on a rigid model, with several parameters needing
to be precisely known in order for the guarantees to hold. In this paper, we
consider a stochastic model and show that it is possible to obtain good welfare
and revenue guarantees with simple mechanisms that do not make use of the
information on some of these parameters. In particular, we prove that a
mechanism that sets the same price per time step for jobs of any length
achieves at least 50% of the welfare and revenue obtained by a mechanism that
can set different prices for jobs of different lengths, and the ratio can be
improved if we have more specific knowledge of some parameters. Similarly, a
mechanism that sets the same price for all servers even though the servers may
receive different kinds of jobs can provide a reasonable welfare and revenue
approximation compared to a mechanism that is allowed to set different prices
for different servers.Comment: To appear in the 13th Conference on Web and Internet Economics
(WINE), 2017. A preliminary version was presented at the 12th Workshop on the
Economics of Networks, Systems and Computation (NetEcon), 201
Who Benefits from a Multi-Cloud Market? A Trading Networks Based Analysis
In enterprise cloud computing, there is a big and increasing investment to
move to multi-cloud computing, which allows enterprises to seamlessly utilize
IT resources from multiple cloud providers, so as to take advantage of
different cloud providers' capabilities and costs. This investment raises
several key questions: Will multi-cloud always be more beneficial to the cloud
users? How will this impact the cloud providers? Is it possible to create a
multi-cloud market that is beneficial to all participants?
In this work, we begin addressing these questions by using the game theoretic
model of trading networks and formally compare between the single and
multi-cloud markets. This comparson a) provides a sufficient condition under
which the multi-cloud network can be considered more efficient than the single
cloud one in the sense that a centralized coordinator having full information
can impose an outcome that is strongly Pareto-dominant for all players and b)
shows a surprising result that without centralized coordination, settings are
possible in which even the cloud buyers' utilities may decrease when moving
from a single cloud to a multi-cloud network. As these two results emphasize
the need for centralized coordination to ensure a Pareto-dominant outcome and
as the aforementioned Pareto-dominant result requires truthful revelation of
participant's private information, we provide an automated mechanism design
(AMD) approach, which, in the Bayesian setting, finds mechanisms which result
in expectation in such Pareto-dominant outcomes, and in which truthful
revelation of the parties' private information is the dominant strategy. We
also provide empirical analysis to show the validity of our AMD approach
Simple pricing schemes for the cloud
The problem of pricing the cloud has attracted much recent attention due to the widespread use of cloud computing and cloud services. From a theoretical perspective, several mechanisms that provide strong efficiency or fairness guarantees and desirable incentive properties have been designed. However, these mechanisms often rely on a rigid model, with several parameters needing to be precisely known in order for the guarantees to hold. In this paper, we consider a stochastic model and show that it is possible to obtain good welfare and revenue guarantees with simple mechanisms that do not make use of the information on some of these parameters. In particular, we prove that a mechanism that sets the same price per time step for jobs of any length achieves at least 50 % of the welfare and revenue obtained by a mechanism that can set different prices for jobs of different lengths, and the ratio can be improved if we have more specific knowledge of some parameters. Similarly, a mechanism that sets the same price for all servers even though the servers may receive different kinds of jobs can provide a reasonable welfare and revenue approximation compared to a mechanism that is allowed to set different prices for different servers
Simple pricing schemes for the cloud
The problem of pricing the cloud has attracted much recent attention due to the widespread use of cloud computing and cloud services. From a theoretical perspective, several mechanisms that provide strong efficiency or fairness guarantees and desirable incentive properties have been designed. However, these mechanisms often rely on a rigid model, with several parameters needing to be precisely known in order for the guarantees to hold. In this paper, we consider a stochastic model and show that it is possible to obtain good welfare and revenue guarantees with simple mechanisms that do not make use of the information on some of these parameters. In particular, we prove that a mechanism that sets the same price per time step for jobs of any length achieves at least 50 % of the welfare and revenue obtained by a mechanism that can set different prices for jobs of different lengths, and the ratio can be improved if we have more specific knowledge of some parameters. Similarly, a mechanism that sets the same price for all servers even though the servers may receive different kinds of jobs can provide a reasonable welfare and revenue approximation compared to a mechanism that is allowed to set different prices for different servers
Simple pricing schemes for the cloud
The problem of pricing the cloud has attracted much recent attention due to the widespread use of cloud computing and cloud services. From a theoretical perspective, several mechanisms that provide strong efficiency or fairness guarantees and desirable incentive properties have been designed. However, these mechanisms often rely on a rigid model, with several parameters needing to be precisely known in order for the guarantees to hold. In this paper, we consider a stochastic model and show that it is possible to obtain good welfare and revenue guarantees with simple mechanisms that do not make use of the information on some of these parameters. In particular, we prove that a mechanism that sets the same price per time step for jobs of any length achieves at least 50 % of the welfare and revenue obtained by a mechanism that can set different prices for jobs of different lengths, and the ratio can be improved if we have more specific knowledge of some parameters. Similarly, a mechanism that sets the same price for all servers even though the servers may receive different kinds of jobs can provide a reasonable welfare and revenue approximation compared to a mechanism that is allowed to set different prices for different servers