Power consumption costs of computer fleets can be one of the main operational costs of medium or large-sized office sites. In order to optimise the power consumption of the fleet, a set of optimal power management policies must be generated and enforced.

Generating these policies is an optimisation problem of finding the power off timeout value for each computer that maximises energy savings while guaranteeing user satisfaction. To solve this problem, understanding the computer utilisation patterns of the users and defining a metric of user satisfaction is fundamental.

This paper presents a method to analyse user activity and inactivity, extract models from previously recorded utilisation logs and use them to manage a whole computer fleet. A tool that implements this method is also introduced. This tool generates power management policies from utilisation logs. It analyses the effects of variations in fleet characteristics on policies by means of discrete event simulation. It also seeks to understand the behavioural patterns of users over weekly periods. Finally, it generates utilisation logs from high level descriptions of fleets. This tool offers a simulation to study diverse fleet configurations and generation of synthetic fleets.

计算机机队的功耗成本可能是中型或大型办公场所的主要运营成本之一。为了优化车队的功耗，必须生成并实施一组最佳电源管理策略。

生成这些策略是一个优化问题，即找到每台计算机的电源关闭超时值，以最大程度地节省能源，同时保证用户满意度。为了解决此问题，了解用户的计算机使用模式并定义用户满意度的度量标准至关重要。

本文提出了一种分析用户活动和不活动的方法，从以前记录的利用率日志中提取模型，并使用它们来管理整个计算机群。还介绍了实现此方法的工具。该工具从利用率日志中生成电源管理策略。它通过离散事件模拟来分析车队特征变化对政策的影响。它还试图了解用户每周的行为模式。最后，它从车队的高级描述中生成利用率日志。该工具提供了一种模拟，以研究各种车队配置和合成车队的生成。