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has been cited by the following article:

• TITLE: IaaS Public Cloud Computing Platform Scheduling Model and Optimization Analysis

  AUTHORS: Aobing Sun, Tongkai Ji, Qiang Yue, Feiya Xiong

  KEYWORDS: Cloud Computing, IaaS, Scheduling Model, Optimization Analysis

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.4 No.12A, December 22, 2011

  ABSTRACT: IaaS (Infrastructure as a Platform) public cloud is one mainstream service mode for public cloud computing. The design aim of one IaaS public cloud is to enlarge the hardware-usage of whole platform, optimize the virtual machine deployment and enhance the accept rate of service demand. In this paper we create one service model for IaaS public cloud, and based on the waiting-line theory to optimize the service model, the queue length and the configuration of scheduling server. And create one demand-vector based scheduling model, to filter the available host machine according to the match of demand and metadata of available resource. The scheduling model can be bonded with the virtual machine motion to reallocate the resources to guarantee the available rate of the whole platform. The feasibility of the algorithm is verified on our own IaaS public cloud computing platform.