Infrastructure as a Service (IaaS) is one of the most significant and fastest growing fields in cloud computing. To efficiently use the resources of an IaaS cloud, several important factors such as performance, availability, and power consumption need to be considered and evaluated carefully. Evaluation of these metrics is essential for cost-benefit prediction and quantification of different strategies which can be applied to cloud management. In this paper, analytical models based on Stochastic Reward Nets (SRNs) are proposed to model and evaluate an IaaS cloud system at different levels. To achieve this, an SRN is initially presented to model a group of physical machines which are controlled by a management layer. Afterwards, the SRN models presented for the groups of physical machines in the first stage are combined to capture a monolithic model representing an entire IaaS cloud. Since the monolithic model does not scale well for large cloud systems, two approximate SRN models using folding and fixed-point iteration techniques are proposed to evaluate the performance, availability, and power consumption of the IaaS cloud. The existence of a solution for the fixed-point approximate model is proved using Brouwer's fixed-point theorem. A validation of the proposed monolithic and approximate models against both an ad-hoc discrete-event simulator developed in Java and the CloudSim framework is presented. The analytic-numeric results obtained from applying the proposed models to sample cloud systems show that the errors introduced by approximate models are insignificant while an improvement of several orders of magnitude in the state space reduction of the monolithic model is obtained.

中文翻译：

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IaaS 云性能、可用​​性和功耗分析的分层随机模型

基础设施即服务 (IaaS) 是云计算中最重要和发展最快的领域之一。为了有效地使用 IaaS 云的资源，需要仔细考虑和评估几个重要因素，例如性能、可用​​性和功耗。这些指标的评估对于可应用于云管理的不同策略的成本效益预测和量化至关重要。在本文中，提出了基于随机奖励网络 (SRN) 的分析模型，以在不同级别对 IaaS 云系统进行建模和评估。为了实现这一点，最初提出了一个 SRN 来对由管理层控制的一组物理机器进行建模。然后，在第一阶段为物理机组呈现的 SRN 模型组合在一起，以捕获代表整个 IaaS 云的单体模型。由于单体模型不适用于大型云系统，因此提出了两种使用折叠和定点迭代技术的近似 SRN 模型来评估 IaaS 云的性能、可用​​性和功耗。使用 Brouwer 的不动点定理证明了不动点近似模型的解的存在性。提出了针对用 Java 开发的临时离散事件模拟器和 CloudSim 框架对所提出的整体模型和近似模型进行的验证。