CPPM:用于云平台的轻量级性能预测中间件

Xiao Peng
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引用次数: 0

摘要

随着越来越多的商业云应用于各个领域,如何评估云平台的性能已经成为一个需要解决的重要问题。此外,有效的性能预测机制对于改善当前的云服务,如资源分配和任务调度具有重要的价值。本文提出了一种性能预测系统的设计和原型实现,即云性能预测中间件(CPPM),该系统旨在为现有云基础设施提供一套轻量级、灵活的服务,使云提供商能够从各个方面对运行时性能进行监控、估计和预测。CPPM使云提供商能够基于其短期工作负载预测机制制定更高效、更细粒度的资源管理和调度策略;此外,它还提供了一个应用程序级的性能预测服务,该服务使用框架方法捕获正在运行的应用程序的执行特征,从而预测它们实际的运行时性能和效率。为了检验CPPM的有效性和效率,进行了大量的实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CPPM: a lightweight performance prediction middleware for cloud platforms
As more and more commercial clouds have been applied in various areas, how to evaluate the performance of a cloud platform has become an important issue that needs to be addressed. Furthermore, an effective performance prediction mechanism is of significant value for improving the current cloud services, such as resource allocation and task scheduling. In the paper, we present the design and prototype implementation of a performance prediction system, namely cloud performance prediction middleware (CPPM), which is aiming at providing a set of lightweight and flexible services on existing cloud infrastructure so as to allow cloud providers monitoring, estimating and predicting the runtime performance from various aspects. The CPPM enables cloud providers to make more efficient and fine-grained resource management and scheduling policies based on their short-term workload prediction mechanism; also it provides an application-level performance prediction service which uses skeleton approach to capture execution characteristics of the running applications so as to predict their actual runtime performance and efficiency. Extensive experiments are conducted to examine the effectiveness and efficiency of the CPPM.
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