一种面向分布式网络管理的自适应可扩展模型

A self-adapting scalable model for distributed network management

本文针对大规模分布式网络的特点,提出了一种灵活、动态、自适应伸展性网络管理方案。它采用层次型体系结构,支持多个管理域的分布式网络管理,适应了大规模网络的规模可变性和弹性的特点。为了解决网络事件大量性、多样性和相关性的问题,本文将网络事件分为简单事件和复合事件两种类型,采用层次型事件处理机制和基于动态时间窗的事件合成方法,保证了事件检测的可靠性,平衡了系统负载,降低了网络资源的占用率。

A flexible, dynamic, self-adapting and scalable model is presented for managing large-scale distributed networks. A hierarchical architecture, supporting distributed management based on domain, is adopted. It achieves scalability by modifying the number of components according to the size of network. To monitoring network events efficiently, two event types are defined, primitive event and composite event. Event hierarchical processing mechanism can efficiently distribute the loads and improve the reliability of the system. Event composition approach named dynamic time windows can deal with out-of-order sequences of event arrivals due to communication delays in an efficient manner. Moreover, the system can trigger or disable management tasks automatically according to some network events.