1,997 research outputs found
Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access
Dynamic spectrum access is a new paradigm of secondary spectrum utilization
and sharing. It allows unlicensed secondary users (SUs) to exploit
opportunistically the under-utilized licensed spectrum. Market mechanism is a
widely-used promising means to regulate the consuming behaviours of users and,
hence, achieves the efficient allocation and consumption of limited resources.
In this paper, we propose and study a hybrid secondary spectrum market
consisting of both the futures market and the spot market, in which SUs
(buyers) purchase under-utilized licensed spectrum from a spectrum regulator,
either through predefined contracts via the futures market, or through spot
transactions via the spot market. We focus on the optimal spectrum allocation
among SUs in an exogenous hybrid market that maximizes the secondary spectrum
utilization efficiency. The problem is challenging due to the stochasticity and
asymmetry of network information. To solve this problem, we first derive an
off-line optimal allocation policy that maximizes the ex-ante expected spectrum
utilization efficiency based on the stochastic distribution of network
information. We then propose an on-line VickreyCClarkeCGroves (VCG) auction
that determines the real-time allocation and pricing of every spectrum based on
the realized network information and the pre-derived off-line policy. We
further show that with the spatial frequency reuse, the proposed VCG auction is
NP-hard; hence, it is not suitable for on-line implementation, especially in a
large-scale market. To this end, we propose a heuristics approach based on an
on-line VCG-like mechanism with polynomial-time complexity, and further
characterize the corresponding performance loss bound analytically. We finally
provide extensive numerical results to evaluate the performance of the proposed
solutions.Comment: This manuscript is the complete technical report for the journal
version published in INFORMS Operations Researc
Pricing Strategy for Cloud Computing Services
The cloud services market exhibits unique characteristics such as instant accessibility, fluctuating demand and supply, and interruptible service provision. Various pricing mechanisms exist in current industry practice, however, none is comprehensive enough to capture all these features. In my work, I identify key factors related to cloud computing pricing. My dissertation includes three essays. They employ multiple approaches, including market survey, game theory modelling, simulation, lab experiments and econometric modelling, to analyse the pricing strategy of cloud services vendors. The first essay highlights nine important factors in current cloud pricing practice and proposes three missing factors based on a market survey. In the second essay, I build an analytical model and use simulation to derive optimal pricing strategies for a monopoly cloud services vendor that operates in the reserved services market and the spot services market. In the last piece of work, I examine the client’s willingness-to-pay for customized cloud services through behavioural experiments
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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