SBIR Phase II: Codebook Correlation for Self-Healing Networked Systems

*9633004 Shaula Yemini网络事件关联的目标是在网络系统的问题中断应用程序之前识别它们。当前自动化事件关联的方法速度慢，对数据中的噪声敏感，并且不能动态适应联网系统的拓扑变化。码本方法使用编码理论作为一种新的相关过程的基础，该过程是高速的，对噪声具有鲁棒性，并且动态地适应系统的变化。关键思想是，由于问题的特征是它们引起的症状，因此监视唯一标识(“编码”)感兴趣的问题的最小症状集就足够了。因此，实时相关处理被简化为对症状进行最小距离“解码”的快速过程。可以添加症状以使代码“纠错”，以针对事件流中的噪声实现健壮性。该项目的潜在市场领域是：1.用于企业网络的自动化问题管理产品，减少关键任务应用程序在网络故障时间中的风险。2.针对网络服务提供商的自动化网络管理解决方案，在降低运营成本的同时提高服务质量。3.自愈网络、系统、应用*

*** 9633004 Shaula Yemini Network event correlation's goal is to identify a networked system's problems before they disrupt applications. Current approaches to automating event correlation are slow, sensitive to noise in their data, and cannot dynamically adapt to a networked system's topology changes. The Codebook approach uses coding theory as the base of a novel correlation process that is high speed, robust to noise, and dynarnically adapts to system changes. The key idea is that since problems are characterized by the symptoms they cause, it suffices to monitor the minimal set of symptoms that uniquely identify ("encode") the problems of interest. Real-time correlation processing is thus reduced to a fast process of minimal distance "decoding" of symptoms. Symptoms can be added to make codes "error-correcting", for robustness with respect to noise in the event stream. Potential market areas for this project are: 1.automated problem management products for enterprise networks, reducing exposure of mission critical applications to network down time. 2. Automated network management solutions for network service providers, increasing quality of service while reducing operations costs. 3. Selfhealing network, system and application ***