一种面向大规模系统域网络性能管理系统

当前系统域网络规模日益庞大,如何监控系统域网络复杂的流量行为、发现性能瓶颈以及可能的网络故障点,为系统域网络性能优化提供有效支持的需求已经日益迫切。首先提出了一种系统域网络的性能管理体系结构SNPMA,SNPMA采用了松耦合的分层结构,通过各层之间的协同实现性能管理的自动化和可操作性。在此基础上提出了一种网络性能评估模型NPEM,解决大规模网络中对现有网络设备性能状况无法正确评估、对网络运行状态无法进行有效预测的问题,进而提出了自适应并发策略性能监控方法STM,能动态调整采集数据的策略,较好地提高了采集数据的效率。在"天河二号"真实的网络环境下,对网络设备的性能进行分级评估和分析,验证了网络性能评估和分析模型。

A performance management system for large-scale system area networks

For large-scale system area networks, how to effectively monitor the heavy traffic, detect the performance bottlenecks and locate the potential failure points in order to support the optimization of the network performance becomes a new research topic. We firstly put forward a performance management architecture for the system area network called SNPMA, which adopts the loosely coupled hierarchical structure and realizes the automation and operability of the performance management through the collaboration among different layers. Based on the SNPMA, we also propose a network performance evaluation model called NPEM to resolve the problems like the incapability of properly evaluating the performance conditions for network devices and ineffectively predicting the operational status for the whole network in terms of the large-scale system area network. And then we propose a network performance monitoring method called STM based on the adaptive concurrency strategy, which can dynamically adjust the strategies of collecting performance parameters. In the network environment of Tianhe-2, through monitoring the whole network using the STM, the performance indicators of network devices are effectively evaluated, which verifies the validity of the network performance evaluation model NPEM.