导　　师： 杨坚

学科专业： 081101

授予学位： 硕士

作　　者： ;

机构地区： 中国科学技术大学

摘　　要： 随着科技的发展,计算机在各行业的应用日益广泛,很多行业对计算机性能要求日益增加。大规模服务器集群在为科研、工作、生活带来便利的同时,也带来一个严峻的问题——巨大的能耗。能耗问题对于服务器集群来说是个重大的问题,因为它不仅是一台或是一群服务器消耗能源的问题,还直接影响到系统的冷却需求、备用设备的冷却需求,以及备用发电设备的需求。尽管很多地方投入大量资金用于解决供电问题,但是基本上所有的发电技术都对环境有巨大的副作用。无论从互联网的角度,还是从整个社会的角度,集群的节能问题都已经成为一个非常现实、严峻的问题。 对于系统级的节能调度算法有比较成熟的策略,如动态电源管理策略/(DPM/)、动态电压和频率调整策略/(DVFS/)、动态电压调整策略/(DVS/)等。这几种策略在系统级节能层次上应用的很成功,但并不适合用在服务器集群层次上。适用于集群层面的节能策略是目前业界研究的热点问题,出现的比较早的策略是比例积分微分反馈控制策略/(PID/)和负载集中策略/(LC/)等。随着集群系统构造的复杂化、集群提供业务的多样化,这两种节能策略的有效性在降低。动态集群配置是根据网络中负载情况动态地调整服务器规模,在最小系统功耗下实现最优的服务性能。本文提出了基于预测的动态集群配置策略,该方法根据网络中服务请求的历史信息,运用最小均方误差/(LMS/)和递归最小二乘/(RLS/)预测未来时刻服务请求情况,根据负载请求与集群处理能力来决策服务器规模的增减,动态地调节服务器集群中计算机的开启与关断。 另外,文中对于计算密集型服务器集群提出了特殊的集群配置策略。根据超负率提供有QoS保证的服务,我们将节能问题抽象为约束最优化问题,即在保持超负率低于某个期望阈值的情� With the development of the science and technology, computers are widely applied in many fields, and their performance is expected higher and higher. A possible solution is to introduce giant computers, to meet the large-scale scientific computing of there emerging industries. But the astronomical costs of the giant computers are high enough to discourage most of the potential users. As the large-scale server clusters bring great convenience for scientific research, work, study and daily life, it also brings another serious problem—a huge energy consumption issue. A power issue is an important problem for server clusters, because it is not only a concern of a single computer or a group of servers, but also directly influences their cooling requirements. In fact, a medium to large number of high-performance nodes racked closely in the same work environment, as is usually the case with clusters, requires a significant investment in cooling, both in terms of sophisticated racks and heavy duty air consumption also influences the required investments in backup cooling and backup power-generation equipment for clusters that can never be unavailable, such as those of companies that provide services on the Internet. By extension, the server cluster energy conservation becomes a major issue for the whole society. Although, many local authorities invested heavily in power plants to solve power problems, most power-generation technologies have a negative impact on the environment. Clusters energy-saving issue has been a very real, serious problem, not only from the perspective of the Internet, but also from the point of the whole society. There are some mature energy-saving strategies for system-level scheduling, such as dynamic power management policy /(DPM/), dynamic voltage and frequency adjustment strategy /(DVFS/), dynamic voltage scaling strategy /(DVS/) and so on. These strategies are applied successfully on system-level energy conservation, but they are not suitable for cluster level. The strategies for clust

关 键 词： 服务器集群 节能 负载在线预测 算法 算法

领　　域： [自动化与计算机技术] [自动化与计算机技术]