Dynamic Pricing of Applications in Cloud Marketplaces using Game Theory

The competitive nature of Cloud marketplaces as new concerns in delivery of services makes the pricing policies a crucial task for firms. so that, pricing strategies has recently attracted many researchers. Since game theory can handle such competing well this concern is addressed by designing a normal form game between providers in current research. A committee is considered in which providers register for improving their competition based pricing policies. The functionality of game theory is applied to design dynamic pricing policies. The usage of the committee makes the game a complete information one, in which each player is aware of every others payoff functions. The players enhance their pricing policies to maximize their profits. The contribution of this paper is the quantitative modeling of Cloud marketplaces in form of a game to provide novel dynamic pricing strategies; the model is validated by proving the existence and the uniqueness of Nash equilibrium of the game

Towards an open cloud marketplace: vision and first steps

As one of the most promising, emerging concepts in Information Technology (IT), cloud computing is transforming how IT is consumed and managed; yielding improved cost efficiencies, and delivering flexible, on-demand scalability by reducing computing infrastructures, platforms, and services to commodities acquired and paid-for on-demand through a set of cloud providers. Today, the transition of cloud computing from a subject of research and innovation to a critical infrastructure is proceeding at an incredibly fast pace. A potentially dangerous consequence of this speedy transition to practice is the premature adoption, and ossification, of the models, technologies, and standards underlying this critical infrastructure. This state of affairs is exacerbated by the fact that innovative research on production-scale platforms is becoming the purview of a small number of public cloud providers. Specifically, the academic research communities are effectively excluded from the opportunity to contribute meaningfully to the evolution not to mention innovation and healthy mutation of cloud computing technologies. As the dependence on our society and economy on cloud computing increases, so does the realization that the academic research community cannot be shut out from contributing to the design and evolution of this critical infrastructure. In this article we provide an alternative vision that of an Open Cloud eXchange (OCX) a public cloud marketplace, where many stakeholders, rather than just a single cloud provider, participate in implementing and operating the cloud, thus creating an ecosystem that will bring the innovation of a broader community to bear on a much healthier and more efficient cloud marketplace

A Study of Competitive Cloud Resource Pricing under a Smart Grid Environment

In the current IaaS cloud market, to achieve profit maximization, multiple cloud providers compete non-cooperatively by offering diverse price rates. At the same time, tenant consumers judiciously adjust demands accordingly, which in turn affects cloud resource prices. In this paper, we tackle this fundamental but daunting cloud price competition problem with Bertrand game modeling, and propose a dynamic game to achieve Nash equilibrium in a distributed manner. Specifically, we realistically consider spot electricity prices under a smart grid environment, and systematically investigate the impact of different system parameters such as network delay, renewable availability, and cloud resource substitutability. We also perform stability analysis to investigate the convergence of the proposed dynamic game to Nash equilibrium. Cooperation among cloud providers can achieve aggregate cloud profit maximization, but is subject to strategic manipulations. We then propose our Striker strategy to stimulate cooperation, the efficiency of which is validated by repeated game analysis. Our evaluation is augmented with realistic electricity prices in the spot energy market, and reveals insightful observations for both theoretic analysis and practical pricing scheme design.published_or_final_versio

Service provisioning problem in cloud and multi-cloud systems

Cloud computing is a new emerging paradigm that aims to streamline the on-demand provisioning of resources as services, providing end users with flexible and scalable services accessible through the Internet on a pay-per-use basis. Because modern cloud systems operate in an open and dynamic world characterized by continuous changes, the development of efficient resource provisioning policies for cloud-based services becomes increasingly challenging. This paper aims to study the hourly basis service provisioning problem through a generalized Nash game model. We take the perspective of Software as a Service (SaaS) providers that want to minimize the costs associated with the virtual machine instances allocated in a multiple Infrastructures as a Service (IaaS) scenario while avoiding incurring penalties for execution failures and providing quality of service guarantees. SaaS providers compete and bid for the use of infrastructural resources, whereas the IaaSs want to maximize their revenues obtained providing virtualized resources. We propose a solution algorithm based on the best-reply dynamics, which is suitable for a distributed implementation. We demonstrate the effectiveness of our approach by performing numerical tests, considering multiple workloads and system configurations. Results show that our algorithm is scalable and provides significant cost savings with respect to alternative methods (5% on average but up to 260% for individual SaaS providers). Furthermore, varying the number of IaaS providers means an 8%-15% cost savings can be achieved from the workload distribution on multiple IaaSs

Competitive Cloud Resource Procurements via Cloud Brokerage

In current IaaS cloud markets, tenant consumers non-cooperatively compete for cloud resources via demand quantities, and the service quality is offered in a best effort manner. To better exploit tenant demand correlation, cloud brokerage services provide cloud resource multiplexing so as to earn profits by receiving volume discounts from cloud providers. A fundamental but daunting problem facing a tenant consumer is competitive resource procurements via cloud brokerage. In this paper, we investigate this problem via non-cooperative game modeling. In the static game, to maximize the experienced surplus, tenants judiciously select optimal demand responses given pricing strategies of cloud brokers and complete information of the other tenants' demands. We also derive Nash equilibrium of the non-cooperative game for competitive resource procurements. Performance evaluation on Nash equilibrium reveals insightful observations for both theoretical analysis and practical cloud resource procurements scheme design.published_or_final_versio

A Competition-based Pricing Strategy in Cloud Markets using Regret Minimization Techniques

Cloud computing as a fairly new commercial paradigm, widely investigated by different researchers, already has a great range of challenges. Pricing is a major problem in Cloud computing marketplace; as providers are competing to attract more customers without knowing the pricing policies of each other. To overcome this lack of knowledge, we model their competition by an incomplete-information game. Considering the issue, this work proposes a pricing policy related to the regret minimization algorithm and applies it to the considered incomplete-information game. Based on the competition based marketplace of the Cloud, providers update the distribution of their strategies using the experienced regret. The idea of iteratively applying the algorithm for updating probabilities of strategies causes the regret get minimized faster. The experimental results show much more increase in profits of the providers in comparison with other pricing policies. Besides, the efficiency of a variety of regret minimization techniques in a simulated marketplace of Cloud are discussed which have not been observed in the studied literature. Moreover, return on investment of providers in considered organizations is studied and promising results appeared

Security-Induced Lock-In in the Cloud

Cloud services providers practice security-induced lock-in when employing cryptography and tamper-resistance to limit the portability and interoperability of users’ data and applications. Moreover, security-induced lock-in and users’ anti-lock-in strategies intersect within the context of platform competition. When users deploy anti-lock in strategies, such as using a hybrid cloud, a leader–follower pricing framework increases profits for cloud services providers relative to Nash equilibrium prices. This creates a second-mover advantage, as the follower’s increase in profits exceeds that of the leader owing to the potential for price undercutting. By contrast, introducing or enhancing security-induced lock-in creates both an increase in profits and a first-mover advantage. Cloud services providers therefore favor security-induced lock-in over price leadership. More broadly, we show why standardization of semantics, technologies, and interfaces is a nonstarter for cloud services providers