Power management by load forecasting in web server clusters
Power management by load forecasting in web server clusters
复制标题
DOI：
10.1007/s10586-011-0187-2
复制
发表时间：
2011-10
期刊：
影响因子：
--
通讯作者：
Carlos Santana;J. Leite;D. Mossé
中科院分区：
文献类型：
--
作者：
Carlos Santana;J. Leite;D. Mossé
为了满足更复杂的业务模式(例如，Web服务和云计算)，Web应用程序的复杂性和要求都在不断增加。为此，在Web服务器集群设计中考虑了性能、可扩展性和安全性等特性。由于能源成本的上升和对环境的关注，这类系统的能源消耗已成为一个主要问题。本文介绍了在软实时Web服务器集群环境中，使用负荷预测方法，结合动态电压和频率调整(DVFS)和动态配置技术(打开和关闭服务器)来降低能耗的技术。我们的系统促进了能源消耗的降低，同时保持了用户对满足请求截止日期的满意度。结果表明，预测能力提高了系统的服务质量，同时保持或改善了与现有电源管理机制相比的节能效果。为了验证这一预测策略，在运行Linux的Apache服务器集群试验床上部署了一个运行真实工作负载配置文件的Web应用程序。
The complexity and requirements of web applications are increasing in order to meet more sophisticated business models (web services and cloud computing, for instance). For this reason, characteristics such as performance, scalability and security are addressed in web server cluster design. Due to the rising energy costs and also to environmental concerns, energy consumption in this type of system has become a main issue. This paper shows energy consumption reduction techniques that use a load forecasting method, combined with DVFS (Dynamic Voltage and Frequency Scaling) and dynamic configuration techniques (turning servers on and off), in a soft real-time web server clustered environment. Our system promotes energy consumption reduction while maintaining user’s satisfaction with respect to request deadlines being met. The results obtained show that prediction capabilities increase the QoS (Quality of Service) of the system, while maintaining or improving the energy savings over state-of-the-art power management mechanisms. To validate this predictive policy, a web application running a real workload profile was deployed in an Apache server cluster testbed running Linux.