Price Competition in an Oligopoly Market with Multiple IaaS Cloud Providers

Feng, Yuan; Li, Baochun; Li, Bo

doi:10.1109/tc.2013.153

Cited by 121 publications

(66 citation statements)

References 27 publications

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“…In [31] the authors present a methodical in-depth game theory study on price competition, moving progressively from a monopoly market to a duopoly market, and finally to an oligopoly Cloud market. They characterize the nature of non-cooperative competition with multiple competing Cloud service providers, derive algorithms representing the influence of resource capacity and operating costs on the solution and prove the existence of a Nash equilibrium.…”

Section: Related Workmentioning

confidence: 99%

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Ardagna

Ciavotta

Passacantando

2017

IEEE Trans. Serv. Comput.

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Abstract-The adoption of Cloud technologies is steadily increasing. In such systems, applications can benefit from nearly infinite virtual resources on a pay-per-use basis. However, being the Cloud massively multi-tenant and characterized by highly variable workloads the development of more and more effective provisioning policies assumes paramount importance. Boosted by the success of the Cloud, the application of Game Theory models and methodologies has also become popular, since they have been demonstrated to suit perfectly to Cloud social, economic, and strategic structures. This paper aims to study, model and efficiently solve the cost minimization problem associated with the service provisioning of SaaS virtual machines in multiple IaaSs. We propose a game-theoretic approach for the runtime management of resources from multiple IaaS providers to be allocated to multiple competing SaaSs, along with a cost model including revenues and penalties for requests execution failures. A distributed algorithm for identifying Generalized Nash Equilibria has been developed and analysed in detail. The effectiveness of our approach has been assessed by performing a wide set of analyses under multiple workload conditions. Results show that our algorithm is scalable and provides significant cost savings with respect to alternative methods (80% on average). Furthermore, increasing the number of IaaS providers SaaSs can achieve 9-15% cost savings from the workload distribution on multiple IaaSs.

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Section: Related Workmentioning

confidence: 99%

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Ardagna

Ciavotta

Passacantando

2017

IEEE Trans. Serv. Comput.

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“…As cloud-assisted WBANs are being exploited by the global population, the pricing of services undergoes competition. In general the CSPs always try to maximize their profits, while guaranteeing different levels of satisfaction to the customers [6], [7]. However, continuous competition in profit-maximization of the service providers do not leave any space for price bargaining to the end-users.…”

Section: A Motivationmentioning

confidence: 99%

Cost-Effective Mapping between Wireless Body Area Networks and Cloud Service Providers Based on Multi-Stage Bargaining

Moulik

Misra

Gaurav

2017

IEEE Trans. on Mobile Comput.

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This paper presents a bargaining-based resource allocation and price agreement in an environment of cloudassisted Wireless Body Area Networks (WBANs). The challenge is to finalize a price agreement between the Cloud Service Providers (CSPs) and the WBANs, followed by a cost-effective mapping among them. Existing solutions primarily focus on profits of the CSPs, while guaranteeing different user satisfaction levels. Such pricing schemes are bias prone, as quantifying user satisfaction is fuzzy in nature and hard to implement. Moreover, such traditional approach may lead to an unregulated market, where few service providers enjoy the monopoly/oligopoly situation. However, in this work, we try to remove such biasness from the pricing agreements, and envision this challenge from a comparatively fair point of view. In order to do so, we use the concept of bargaining, an interesting approach involving cooperative game theory. We introduce an exposition -multistage Nash bargaining solution (MUST-NBS), that unfolds into multiple stages of bargaining, as the name suggests, until we conclude price agreement between the CSPs and the WBANs. In addition, the proposed approach also consummates the final mapping between the CSPs and the WBANs, depending on the cost-effectiveness of the WBANs. Analysis of the proposed algorithms and the inferences of the results validates the usefulness of the proposed mapping technique.

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“…The paper models u(x i ) by the following utility function which is widely used in the literature [11],…”

Section: B Cloud Users' Decision Choicesmentioning

confidence: 99%

Pricing for Resource Allocation in Cloud Computing

Cai¹,

Yang²,

Chen³

et al. 2015

Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

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Abstract-In cloud computing environment, pricing is an effective method for resource allocation and it provides efficient incentive for cloud providers to provide cloud services. In this paper, the author investigates two pricing schemes for the allocation of cloud resources in a monopoly cloud market subject to constrained capacity of the cloud provider. There are two main pricing schemes, on-demand and reserved pricing mechanisms adopted by leading cloud providers, i.e., Amazon and Gogrid. The paper analyzes how cloud users make their choice decisions to subscribe to cloud resources under different pricing schemes.

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Price Competition in an Oligopoly Market with Multiple IaaS Cloud Providers

Cited by 121 publications

References 27 publications

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems

Cost-Effective Mapping between Wireless Body Area Networks and Cloud Service Providers Based on Multi-Stage Bargaining

Pricing for Resource Allocation in Cloud Computing

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