Auto-scaling of Web applications is an extensively investigated issue in cloud computing. To evaluate auto-scaling mechanisms, the cloud community is facing considerable challenges on either real cloud platforms or custom test-beds. Challenges include – but not limited to – deployment impediments, the complexity of setting parameters, and most importantly, the cost of hosting and testing Web applications on a massive scale. Hence, simulation is presently one of the most popular evaluation solutions to overcome these obstacles. Existing simulators, however, fail to provide support for hosting, deploying and subsequently auto-scaling of Web applications. In this paper, we introduce AutoScaleSim, which extends the existing CloudSim simulator, to support auto-scaling of Web applications in cloud environments in a customizable, extendable and scalable manner. Using AutoScaleSim, the cloud community can freely implement/evaluate policies for all four phases of auto-scaling mechanisms, that is, Monitoring, Analysis, Planning and Execution. AutoScaleSim can also be used for evaluating load balancing algorithms similarly. We conducted a set of experiments to validate and carefully evaluate the performance of AutoScaleSim in a real cloud platform, with a wide range of performance metrics.

Web应用程序的自动缩放是云计算中广泛研究的问题。为了评估自动扩展机制，云社区在真实云平台或自定义测试平台上都面临着巨大的挑战。挑战包括但不限于部署障碍，参数设置的复杂性，最重要的是大规模托管和测试Web应用程序的成本。因此，仿真是目前克服这些障碍的最受欢迎的评估解决方案之一。但是，现有的模拟器无法为Web应用程序的托管，部署和自动缩放提供支持。在本文中，我们介绍了AutoScaleSim，它扩展了现有的CloudSim模拟器，以支持可自定义的云环境中Web应用程序的自动扩展，可扩展和可扩展的方式。使用AutoScaleSim，云社区可以为自动扩展机制的所有四个阶段（即监视，分析，计划和执行）自由地实施/评估策略。AutoScaleSim也可以类似地用于评估负载平衡算法。我们进行了一系列实验，以验证并仔细评估AutoScaleSim在真实云平台上的性能，并采用多种性能指标。