GLOBALSOFT TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE ST...
choose the one that maximizes its own net reward, i.e., its utility obtained by
choosing the IaaS cloud service minus its...
 A static pricing scheme cannot be optimal if the demand for services has
deterministic seasonal fluctuations.
 Static...
Advantage:
 A novel demand-pricing model designed for cloud caching services and the
problem formulation for the dynami...
 Coding Language : C#.NET.
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2014 IEEE DOTNET CLOUD COMPUTING PROJECT Price competition in an oligopoly market with multiple iaa s cloud providers

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Published on: Mar 4, 2016
Published in: Engineering      
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Transcripts - 2014 IEEE DOTNET CLOUD COMPUTING PROJECT Price competition in an oligopoly market with multiple iaa s cloud providers

  • 1. GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmai l.com Price Competition in an Oligopoly Market with Multiple IaaS Cloud Providers Abstract: As an increasing number of infrastructure-as-a-service (IaaS) cloud providers start to provide cloud computing services, they form a competition market to compete for users of these services. Due to different resource capacities and service workloads, users may observe different finishing times for their cloud computing tasks and experience different levels of service qualities as a result. To compete for cloud users, it is critically important for each cloud service provider to select an “optimal” price that best corresponds to their service qualities, yet remaining attractive to cloud users. We characterize the nature of non-cooperative competition in an IaaS cloud market, with a goal of capturing how each IaaS cloud provider will select its optimal prices to compete with the others. One of the possible types of cloud services provided by today’s cloud providers, such as Amazon EC2 and Rackspace, is referred to as infrastructure as a service (IaaS). Since a user’s cloud service demand may be satisfied by any of these IaaS cloud providers, a rational user will
  • 2. choose the one that maximizes its own net reward, i.e., its utility obtained by choosing the IaaS cloud service minus its payment.In this More specifically, we present an in-depth analytical study on the monopoly, duopoly, and oligopoly markets, in which multiple IaaS cloud providers are competing with one another. Since the pricing strategy of a cloud provider depends on its competitors, we take a game theoretic perspective to study the strategic situation. 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  Closely related to cloud computing is research on accounting in wide-area networks that offer distributed services. Mariposa discusses an economy for querying in distributed databases. Disadvantage:
  • 3.  A static pricing scheme cannot be optimal if the demand for services has deterministic seasonal fluctuations.  Static pricing results in an unpredictable and, therefore, uncontrollable behavior of profit.  Dynamic pricing can lead to customer alienation. If customers realize they paid higher prices than others for the same solution, they may demand their money back or spread negative messages in the marketplace. Proposed System:-  Optimal resource allocation for cloud users in VM-based IaaS clouds, with full awareness of different prices charged by cloud providers.  We first consider the case of a duopoly cloud market, in which two IaaS cloud providers compete with each other, with a similar game theoretic analysis as the monopoly case.  Dynamic pricing often is referred to as discriminatory pricing because it allows you to maximize profits with each customer.  This approach is common in event promotions: If initial demand is low, facility or event managers work to sell off open seats to generate whatever revenue is possible.  Existing papers were concerned with the problem of how optimal pricing in the cloud can be achieved.  Strength of dynamic pricing is the ability to adjust prices for service projects or products based on the time and costs involved or fluctuating demand.
  • 4. Advantage:  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.  An efficient solution to the pricing problem, based on non-linear programming, adaptable to time changes.  A correlation measure for cache structures that is suitable for the cloud cache pricing scheme and a method for its efficient computation.  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. Hardware Requirements:-  SYSTEM : Pentium IV 2.4 GHz  HARD DISK : 40 GB  RAM : 256 MB Software Requirements:-  Operating system : Windows 7  IDE : Microsoft Visual Studio 2010  Database : Sql server 2005
  • 5.  Coding Language : C#.NET.

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