8,376 research outputs found
Ensuring Trust in One Time Exchanges: Solving the QoS Problem
We describe a pricing structure for the provision of IT services that ensures
trust without requiring repeated interactions between service providers and
users. It does so by offering a pricing structure that elicits truthful
reporting of quality of service (QoS) by providers while making them
profitable. This mechanism also induces truth-telling on the part of users
reserving the service
Pricing the Cloud: An Auction Approach
Cloud computing has changed the processing and service modes of information communication technology and has affected the transformation, upgrading and innovation of the IT-related industry systems. The rapid development of cloud computing in business practice has spawned a whole new field of interdisciplinary, providing opportunities and challenges for business management research.
One of the critical factors impacting cloud computing is how to price cloud services. An appropriate pricing strategy has important practical means to stakeholders, especially to providers and customers. This study addressed and discussed research findings on cloud computing pricing strategies, such as fixed pricing, bidding pricing, and dynamic pricing. Another key factor for cloud computing is Quality of Service (QoS), such as availability, reliability, latency, security, throughput, capacity, scalability, elasticity, etc. Cloud providers seek to improve QoS to attract more potential customers; while, customers intend to find QoS matching services that do not exceed their budget constraints.
Based on the existing study, a hybrid QoS-based pricing mechanism, which consists of subscription and dynamic auction design, is proposed and illustrated to cloud services. The results indicate that our hybrid pricing mechanism has potential to better allocate available cloud resources, aiming at increasing revenues for providers and reducing expenses for customers in practice
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Enhancing IT investments productivity: Integrating network QOS and it indirect costs
Increasing productivity is considered one of the major driving factors for a successful business. From an Information Technology (IT) infrastructure perspective, obtaining an optimised performance of resources is expected to improve productivity. From a technical viewpoint, the introduction of Quality of Service (QoS) models have been perceived to optimise the performance of the organisation network backbone. These models aim to provide an acceptable level of service assurance to the newly introduced applications and services such as voice and video. From a management viewpoint, the proper management of IT investments indirect costs can lead to a reduction of the overall cost portfolio. Consequently, both benefits and productivity increase are likely to be realised. This paper introduces network QoS strategy within the hierarchy of business infrastructure. In addition, it aims to identify the relationship between network QoS and IT indirect costs. Such integration demonstrates how network QoS strategy can be used to control IT indirect costs as well as enhancing network performance
Optimization of Wireless Internet Pricing Scheme in Serving Multi QoS Network Using Various Attributes
Pricing scheme in wireless networks were developed to provide maximum benefit to the internet service provider (ISP), where the given scheme can guarantee customer satisfaction and service providers who use such services. So that the proposed model should be able to attract consumer interest in applying such services. In this research we established wireless pricing model that involve QoS attributes then the model will be transformed into a model of optimization. Pricing models in wireless networks will be studied by looking at existing models as a nonlinear programming problem that can be solved optimally using LINGO 11.0. The solution is to maximize the total price for the connection based on the QoS parameters. Optimal results in the maximizing of pricing scheme is achieved when providers set the increase of price changes due to QoS changes and number of QoS value
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