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A Game-Based Price Bidding Algorithm for Multi-attribute Cloud Resource Provision - 2018

Research Area:  Cloud Computing

Abstract:

The pricing mechanism of cloud-computing resources is an essential issue for both cloud customers and providers, especially in the view point of multi-provider competition. Although various mechanisms for resource provision are proposed, few studies have focused on multi-attribute resource provision with the objective of improving benefits of both cloud customers and providers. To address the issue, we propose a price bidding mechanism for multi-attribute cloud-computing resource provision from the perspective of a non-cooperative game. Considering the fairness pricing competition, we propose a novel and incentive resource provision model referring to the Quality-of-Service (QoS) and the bidding price. Then, combining with the resource provision model, the problem of price bidding is formulated as a game to find a proper price for each cloud provider. We demonstrate the existence of Nash equilibrium solution set for the formulated game model by assuming that the quantity function of provided resources from every provider is continuous. We propose an Equilibrium Solution Iterative (ESI) algorithm, which is proved to converge to a Nash equilibrium. Finally, a Near-equalization Price Bidding (NPB) algorithm is proposed to modify the obtained Nash equilibrium solution. Extensive experiments and the comparison experiments validate and show the feasibility of the proposed method.

Author(s) Name:  Junyan Hu; Kenli Li; Chubo Liu and Keqin Li

Journal name:  IEEE Transactions on Services Computing ( Early Access )

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/TSC.2018.2860022

Volume Information:  Page(s): 1 - 1