Journal
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
Volume 18, Issue 2, Pages 2030-2045Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSM.2020.3036989
Keywords
Cloud computing; resource management; market-based pricing; auction mechanism
Categories
Funding
- National Natural Science Foundation of China [61972414]
- Beijing Nova Program of Science and Technology [Z201100006820082]
- Beijing Natural Science Foundation [4202066]
- National Key Research and Development Program of China [2018YFB1003800]
- Fundamental Research Funds for Central Universities [2462018YJRC040]
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This article introduces a price-incentive resource auction mechanism in a cloud environment to balance the interests of users and cloud service providers. Through a market-based pricing strategy, it encourages users to purchase resources and execute applications, while ensuring a minimum profit rate for the cloud service provider. The proposed approach includes user utility function and an approximate algorithm PIRA, and its effectiveness is validated through simulations.
For a cloud service provider, it necessitates an emerging cloud ecosystem to consolidate the existing users and attract more potential users, further gaining its market share. Therefore, in this article, we design a price-incentive resource auction mechanism in cloud environment. In response to the cloud resource price, each user synthesizes her bidding budget and QoS requirement, and purchases cloud resources according to her resource demand in a strategic manner. The cloud service provider, meanwhile, can regulate the resource demands of users through conducting a market-based pricing strategy, against too low prices to cover the operational costs (i.e., energy costs) or too high prices resulting in user churn. In virtue of an elaborate market-based pricing strategy, the interests of users and the cloud service provider are balanced. Our price-incentive resource auction mechanism targets to stimulate maximum users willing to purchase resources and perform their applications at the cloud, on the premise of a minimum profit rate guaranteed for the cloud service provider. It is also able to provide budge balance and truthfulness guarantee, and satisfy the envy-freeness. In order to carry out the above objectives, we carefully design the user utility function reflecting the complicated user interest, and formulate our resource pricing and auction problem as a bin packing problem, which has non-polynomial computational complexity. Regarding the NP-hardness of optimization problem and the concavity of user utility, we present a computational-efficient (1 + epsilon)-approximate algorithm namely PIRA. Finally, we conduct simulations based on the real-world dataset to validate the effectiveness of our proposed approach.
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