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Loosely-Coupled Benchmark Framework Automates Performance Modeling on IaaS Clouds

机译:松散耦合的基准框架可在IaaS云上自动化性能建模

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Cloud computing is under rapid development, which brings the urgent need of evaluation and comparison of cloud systems. The performance testers often struggle in tedious manual operations, when carrying out lots of similar experiments on the cloud systems. However, few of current benchmark tools provide both flexible workflow controlling methodology and extensible workload abstraction at the same time. We present a modeling methodology to compare the performance from multiple aspects based on a loosely coupled benchmark framework, which automates experiments under agile workflow controlling and achieves broad cloud supports, as well as good workload extensibility. With several built-in workloads and scenario templates, we performed a series of tests on Amazon EC2 services and our private Open Stack-based cloud, and analyze the elasticity and scalability based on the performance models. Experiments show the robustness and compatibility of our framework, which makes remarkable guarantee that it can be leveraged in practice for researchers and testers to perform their further study.
机译:云计算发展迅速,迫切需要对云系统进行评估和比较。当在云系统上执行许多类似的实验时,性能测试人员通常会在繁琐的手动操作中苦苦挣扎。但是,当前很少有基准测试工具同时提供灵活的工作流控制方法和可扩展的工作量抽象。我们提供一种建模方法论,以基于松散耦合的基准框架从多个方面比较性能,该框架可在敏捷工作流控制下自动进行实验,并获得广泛的云支持以及良好的工作负载可扩展性。通过几个内置的工作负载和场景模板,我们在Amazon EC2服务和基于私有Open Stack的私有云上​​进行了一系列测试,并基于性能模型分析了弹性和可扩展性。实验表明我们框架的鲁棒性和兼容性,这为研究人员和测试人员在实践中可以进行进一步研究提供了有力的保证。

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