Title: A game-based virtual machine pricing mechanism in federated clouds

Authors: Ying Hu

Addresses: College of Computer and Communication, Hunan Institute of Engineering, Xiangtan 411104, China

Abstract: In a federated cloud environment, diverse pricing schemes among different IaaS service providers (ISPs) form a complex economic landscape that nurtures the market of cloud brokers. Although pricing mechanisms have been proposed in the past few years, few of them address the issue of competitive and cooperative behaviours among different ISPs. In this paper, we employ the learning curve to model the operation cost of ISPs, and introduce a novel algorithm that determines the cooperative pricing mechanism among different ISPs. The cooperation decision algorithm uses the operation cost computed based on the learning curve model and price policies obtained from the competition part as parameters to calculate the final revenue when outsourcing or locally satisfying users' resource requests. Extensive experiments are conducted in a real-world federated cloud platform, and the experimental results are compared with three existing pricing mechanisms. Our experimental results show that the proposed pricing mechanism is effective to improve resource utilisation as well as reduce the profit loss caused by request rejection.

Keywords: cloud computing; pricing mechanism; resource market; game theory.

DOI: 10.1504/IJISTA.2019.102668

International Journal of Intelligent Systems Technologies and Applications, 2019 Vol.18 No.6, pp.606 - 622

Received: 15 Feb 2018
Accepted: 13 May 2018
Published online: 01 Oct 2019 *

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