Pricing Schemes in Cloud Computing: An Overview

Mazrekaj, Artan; Shabani, Isak; Sejdiu, Besmir

doi:10.14569/ijacsa.2016.070211

Cited by 45 publications

(36 citation statements)

References 21 publications

(21 reference statements)

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“…Many studies have introduced different potential pricing strategies for cloud services, such as pay-as-you-go pricing, subscription pricing, pay-for-resources pricing, value-based pricing, cost-based pricing, customer-based pricing, competition-based pricing, and other dynamic pricing strategies [4,5]. In reality, the most popular pricing strategies are subscription, pay-as-you-use, and two-part tariff models.…”

Section: Introductionmentioning

confidence: 99%

“…NetSuite, SalesForce.com, and SAP are examples of companies offering SaaS. For instance, the Sales Cloud of SalesForce.com provides features such a sales representatives service with a complete customer profile and account history for managing marketing campaigns and increasing sales [5]. The pricing plans for Sales Cloud are shown in the Table 3.…”

Section: Introductionmentioning

confidence: 99%

“…They provide users with services at a low price per GB of storage, charge hidden costs for inbound and/or outbound data transfer, and offer basic packages at a fixed price which can be extended according to the user's needs, similar to a two-part tariff scheme mixing subscription plus pay-per-use pricing. Also, users can pay a fixed price in order to get discounts on usage-dependent prices [5].…”

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confidence: 99%

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Cloud Services and Pricing Strategies for Sustainable Business Models: Analytical and Numerical Approaches

Chun

2019

Sustainability

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Previous studies have introduced different potential pricing strategies for cloud services. However, not much research has been done comparing subscription pricing and pay-per-use pricing, which are commonly used pricing schemes. Also, there are very few studies which analyze a two-part tariff pricing scheme for cloud services, even though this option may increasingly attract service providers as the cloud market becomes more competitive and the profit margin grows narrower. Previous research has focused on firms' profitability rather than social welfare due to the limitations of free services. This study uses theoretical and numerical analysis to compare the social welfare and profitability of three pricing schemes commonly used by firms: subscription pricing, pay-per-use pricing, and two-part tariff pricing. It shows that the pay-per-use pricing is the best solution from the perspective of social welfare, which contrasts with the conclusion of a previous study stating that social welfare is maximized under a two-part tariff. This paper also shows that the two-part tariff is the most profitable pricing scheme for firms.Sustainability 2020, 12, 49 2 of 15 but a comparative analysis of subscription pricing and pay-per-use pricing has not been done, although these pricing methods are commonly used in cloud service systems. Also, an analytical study is required for the two-part tariff pricing scheme, since the concept of a two-part tariff is nowadays adopted as a cloud services' pricing strategy and could gain in popularity among service providers as the cloud market becomes more competitive and the profit margin grows narrower. Previous research has focused on firms' profitability with respect to the limitations of free services. Chun and Choi [7] analyzed the two pricing schemes of subscription and pay-per-use pricing models from a provider's standpoint and discussed their implications for consumer surplus and social welfare. Chun et al. [8] compared the three pricing schemes of subscription pricing, pay-per-use pricing, and two-part tariff from the perspectives of a provider's profit, consumer surplus, and social welfare.This study differentiates itself from previous ones in several aspects. Firstly, I applied two-part tariff pricing to cloud services by considering subscription pricing and pay-per-use pricing and extended the previous two-part tariff to a more generalized customer heterogeneous model, in order to utilize it for a cloud service pricing strategy. Secondly, I clarified the previous two-part tariff model and compared the results from subscription, pay-per-use, and two-part tariff pricing with those obtained from analytical and numerical approaches and recent real-world examples. In particular, I show how two-part tariff pricing can include the other two pricing schemes of subscription and pay-per-use pricing, through theoretical and numerical analysis. Thirdly, I discuss some possible conflicting issues between customers and providers, in terms of consumer and producer surpluses.This paper shows tha...

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Cloud Services and Pricing Strategies for Sustainable Business Models: Analytical and Numerical Approaches

Chun

2019

Sustainability

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“…Special attention must be also paid to works related to the derivation of metrics that assess different features of IT solutions, particularly to those dimensions used by our methodology as design criteria, that is, cost, reliability, and computing capacity. To begin with, two recent contributions lie at the baseline on which our approach stands: Mazrekaj, Shabani, and Sejdiu (2016), which thoroughly reviews pricing models from different providers and overviews existing related works; and Mitropoulou, Filiopoulou, Michalakelis, and Nikolaidou (2016), where a hedonic multidimensional price index is proposed for IaaS infrastructure pricing based on different characteristics of the deployed services and other factors alike. Similarly, the community has also focused on the trade-off between redundancy/scheduling or planning/reliability of IaaS systems (Gupta, Goyal, Kumar, & Aggarwal, 2013;Li et al, 2012).…”

Section: Related Workmentioning

confidence: 99%

A heuristic approach to the multicriteria design of IaaS cloud infrastructures for Big Data applications

et al. 2018

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The rapid growth of new computing paradigms such as Cloud Computing and Big Data has unleashed great opportunities for companies to shift their business model towards a fully digital strategy. A major obstacle in this matter is the requirement of highly specialized ICT infrastructures that are expensive and difficult to manage. It is at this point that the IaaS (infrastructure as a service) model offers an efficient and cost‐affordable solution to supply companies with their required computing resources. In the Big Data context, it is often a hard task to design an optimal IaaS solution that meets user requirements. In this context, we propose a methodology to optimize the definition of IaaS cloud models for hosting Big Data platforms, following a threefold criterion: cost, reliability, and computing capacity. Specifically, the proposed methodology hinges on evolutionary heuristics in order to find IaaS configurations in the cloud that optimally balance such objectives. We also define measures to quantify the aforementioned metrics over a Big Data platform hosted within an IaaS cloud model. The proposed method is validated by using real information from three IaaS providers and three Big Data platforms. The obtained results provide an insightful input for system managers when initially designing cloud infrastructures for Big Data applications.

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“…In fact, more detailed reviews can be found in several surveys, for instance, [2], [3], [4], [5], [6], and [7].…”

Section: Related Workmentioning

confidence: 99%

A Novel Algorithm for Optimizing Multiple Services Resource Allocation

Gawanmeh¹,

April²

2016

ijacsa

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Abstract-Resource provisioning becomes more and more challenging problem in cloud computing environment since cloudbased services become more numerous and dynamic. The problem of scheduling multiple tasks for multiple users on a given number of resources is considered NP-Complete problem, and therefore, several heuristic based research methods were proposed, yet, there are still many improvements can be done, since the problem has several optimization parameters. In addition, most proposed solutions are built on top of several assumptions and simplifications by applying computational methods such as game theory, fuzzy logic, or evolutionary computing. This paper presents an algorithm to address the problem of resource allocation across a cloud-based network, where several resources are available, and the cost of computational service depends on the amount of computation. The algorithm is applicable without restrictions on cost vector or compaction time matrix as opposed to methods in the literature. In addition, the execution of the algorithm shows better utility compared to methods applied on similar problems.

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Pricing Schemes in Cloud Computing: An Overview

Abstract: Abstract-Cloud

Cited by 45 publications

References 21 publications

Cloud Services and Pricing Strategies for Sustainable Business Models: Analytical and Numerical Approaches

Cloud Services and Pricing Strategies for Sustainable Business Models: Analytical and Numerical Approaches

A heuristic approach to the multicriteria design of IaaS cloud infrastructures for Big Data applications

A Novel Algorithm for Optimizing Multiple Services Resource Allocation

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