Autonomic metered pricing for a utility computing service

Yeo, Chee Shin; Venugopal, Srikumar; Chu, Xingchen; Buyya, Rajkumar

doi:10.1016/j.future.2009.05.024

Cited by 100 publications

(52 citation statements)

References 10 publications

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“…The fixed pricing schemes that currently used by the service providers are not able to adapt to the rapid changes between supply and demand in the market. Besides, the schemes are unfair to the service providers and end users with specific quality of service (QoS) requirements [8].…”

Section: Related Workmentioning

confidence: 99%

“…In contrast, the dynamic pricing scheme is better than the fixed pricing scheme in terms of unpredictable demand [2,[8][9][10][11][12]. A strategy-proof dynamic scheme for resource allocation on federated clouds is proposed by [2].…”

Section: Related Workmentioning

confidence: 99%

“…The authors concluded that the dynamic pricing scheme is more suitable for federated clouds. The pros and cons of charging fixed prices over variable prices for cloud resources are investigated in [8]. The authors evaluated the fixed price scheme with the proposed autonomic pricing mechanisms that self-adjust pricing parameters to meet users' requirements.…”

Section: Related Workmentioning

confidence: 99%

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Dynamic Pricing Scheme for Resource Allocation in Multi-Cloud Environment

Shaari

Ang

Por

et al. 2017

MJCS

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Cloud computing has taken the IT and business world by storm through its cost savings and quick-and-easy adoption. Currently, fixed price model is dominating the pricing schemes in the cloud market. However, this model is unable to reflect the current market needs for cost savings as the number of cloud provider and user increases. As a result, a dynamic pricing scheme has emerged as an attractive strategy to better cope with the unpredictable cloud demand. This paper proposed a dynamic pricing scheme that provides fairness among the service providers in a multi-cloud environment. The scheme adjusts the price accordingly to encourage the low utilized resources' usage and discourage over utilized resources' usage. The evaluation results showed that the proposed scheme is able to reduce the cost of the end user when running compute-intensive and data-intensive jobs in the multi-cloud environment.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Pricing Scheme for Resource Allocation in Multi-Cloud Environment

Shaari

Ang

Por

et al. 2017

MJCS

View full text Add to dashboard Cite

show abstract

“…The resource requirement characteristics of different workload types and the corresponding revenue generating constant for an SaaS provider is presented in Table 2, given below: In this model, the SaaS providers charge the end customers in a pay as you go manner, which is the pricing scheme prevalent in the market [45]. The model presented in Section 2 assumes that the IaaS providers follow a revenue based model for profit, i.e., the profit earned by the IaaS providers operating in the market is a linear function of the cost incurred to service the given workload.…”

Section: Performance Evaluationmentioning

confidence: 99%

Energy Aware Pricing in a Three-Tiered Cloud Service Market

2016

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Abstract:We consider a three-tiered cloud service market and propose an energy efficient pricing strategy in this market. Here, the end customers are served by the Software-as-a-Service (SaaS) providers, who implement customized services for their customers. To host these services, these SaaS providers, in turn, lease the infrastructure related resources from the Infrastructure-as-a-Service (IaaS) or Platform-as-a-Service (PaaS) providers. In this paper, we propose and evaluate a mechanism for pricing between SaaS providers and Iaas/PaaS providers and between SaaS providers and the end customers. The pricing scheme is designed in a way such that the integration of renewable energy is promoted, which is a very crucial aspect of energy efficiency. Thereafter, we propose a technique to strategically provide an improved Quality of Service (QoS) by deploying more resources than what is computed by the optimization procedure. This technique is based on the square root staffing law in queueing theory. We carry out numerical evaluations with real data traces on electricity price, renewable energy generation, workload, etc., in order to emulate the real dynamics of the cloud service market. We demonstrate that, under practical assumptions, the proposed technique can generate more profit for the service providers operating in the cloud service market.

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“…Customer-based pricing model in [2] was introduced that; the price could be specified according to the customers' needs (what the consumer ready to pay). However, the consumer does not know what he/she is ready to pay at every time.…”

Section: Related Workmentioning

confidence: 99%

Pricing Models for Cloud Computing Services, a Survey

Ali¹,

Ammar²

2016

IJCATR

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Abstract:Recently, citizens and companies can access utility computing services by using Cloud Computing. These services such as infrastructures, platforms and applications could be accessed on-demand whenever it is needed. In Cloud Computing, different types of resources would be required to provide services, but the demands such as requests rates and user's requirements of these services and the cost of the required resources are continuously varying. Therefore, Service Level Agreements would be needed to guarantee the service's prices and the offered Quality of Services which are always dependable and interrelated to guarantee revenues maximization for cloud providers as well as improve customers' satisfaction level. Cloud consumers are always searching for a cloud provider who provides good service with the least price, so Cloud provider should use advanced technologies and frameworks to increase QoS, and decrease cost. This paper provides a survey on cloud pricing models and analyzes the recent and relevant research in this field.

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Autonomic metered pricing for a utility computing service

Cited by 100 publications

References 10 publications

Dynamic Pricing Scheme for Resource Allocation in Multi-Cloud Environment

Dynamic Pricing Scheme for Resource Allocation in Multi-Cloud Environment

Energy Aware Pricing in a Three-Tiered Cloud Service Market

Pricing Models for Cloud Computing Services, a Survey

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