Issue No. 02 - April-June (2016 vol. 4)
He Li , Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Japan
Mianxiong Dong , Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Japan
Kaoru Ota , Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Japan
Minyi Guo , Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Processing streaming big data becomes critical as new diver Internet of Thing applications begin to emerge. The existing cloud pricing strategy is unfriendly for processing streaming big data with varying loads. Multiple cloud environments are a potential solution with an efficient pay-on-demand pricing strategy for processing streaming big data. In this paper, we propose an intermediary framework with multiple cloud environments to provide streaming big data computing service with lower cost per load, in which a cloud service intermediary rents the cloud service from multiple cloud providers and provides streaming processing service to the users with multiple service interfaces. In this framework, we also propose a pricing strategy to maximize the revenue of the multiple cloud intermediaries. With extensive simulations, our pricing strategy brings higher revenue than other pricing methods.
Cloud computing, Big data, Pricing, Computational modeling, Computers, Games, Real-time systems
H. Li, M. Dong, K. Ota and M. Guo, "Pricing and Repurchasing for Big Data Processing in Multi-Clouds," in IEEE Transactions on Emerging Topics in Computing, vol. 4, no. 2, pp. 266-277, 2016.