/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

https://link.springer.com/content/pdf/10.1057%2Frpm.2010.24.pdf

Free: The future of a radical price

Elastic scaling allows data stream processing systems to dynamically scale in and out to react to workload changes. As a consequence, unexpected load peaks can be handled and the extent of the overprovisioning can be reduced. However, the strategies used for elastic scaling of such systems need to be tuned manually by the user. This is an error prone and cumbersome task, because it requires a detailed knowledge of the underlying system and workload characteristics. In addition, the resulting quality of service for a specific scaling strategy is unknown a priori and can be measured only during runtime. In this paper we present an elastic scaling data stream processing prototype, which allows to trade off monetary cost against the offered quality of service. To that end, we use an online parameter optimization, which minimizes the monetary cost for the user. Using our prototype a user is able to specify the expected quality of service as an input to the optimization, which automatically detects significant changes of the workload pattern and adjusts the elastic scaling strategy based on the current workload characteristics. Our prototype is able to reduce the costs for three real-world use cases by 19% compared to a naive parameter setting and by 10% compared to a manually tuned system. In contrast to state of the art solutions, our system provides a stable and good trade-off between monetary cost and quality of service.

Online parameter optimization for elastic data stream processing

This article discusses revenue sources and pricing models for business-to-consumer electronic commerce. We outline why revenue sources and pricing models should be separated, how pricing models can contribute to strategic and tactic goals and which pricing models the Internet facilitates mostly. Thereby, we discuss the different forms of price discrimination and the possibilities of interactive pricing models.

Revenue sources and pricing models for business-to-consumer electronic commerce | Erlösquellen und Preismodelle für den Business-to-Consumer- Bereich im Internet

Cloud applications can achieve similar performance with diverse multi-resource configurations, allowing cloud service providers to benefit from optimal resource allocation for reducing their operation cost. This paper aims to solve the problem of multi-resource negotiation with considerations of both the service-level agreement (SLA) and the cost efficiency. The performance and resource demand are usually application-dependent, making the optimization problem complicated, especially when the dimension of multi-resource configuration is large. To this end, we use reinforcement learning to solve the optimization problem of multi-resource configuration with simultaneous optimization of the learning efficiency and performance guarantee. The developed prototype named SmartYARN is extended Apache YARN equipped with our learning algorithm which can enable cloud applications to negotiate multiple resources cost-effectively. The extensive evaluations show that SmartYARN performs well in reducing the cost of resource usage while maintaining compliance with the SLA constraints of cloud service simultaneously.

Cost-efficient negotiation over multiple resources with reinforcement learning

With the increasing maturity of the cloud computing market, specifically in the Infrastructure as a Service (IaaS) domain, adequate pricing of services has become a crucial success factor for providers. In this work, we take a threefold approach to examine the current situation concerning pricing in the IaaS market. Based on an initial literature review, we find that pay-as-you-go pricing is perceived as the dominant scheme by the scientific community. Based on this notion, we discuss other pricing schemes with respect to their advantages, disadvantages, and challenges for a cloud provider. These results are complemented by an empirical study, in which we identify pay-as-you-go and subscription pricing as the dominant options that are practically applied in the IaaS market today.

Pricing in Infrastructure Clouds – An Analytical and Empirical Examination

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Pricing in Infrastructure Clouds – An Analytical and Empirical Examination