Network Alarm Correlation

这个小型企业创新研究第一阶段项目专注于应用编码理论技术来自动化复杂网络中的警报关联。警报指示需要立即处理的异常网络状态或行为，例如故障或拥塞，以避免中断网络操作。在网络系统中，单个问题可能会导致由多个系统组件表现出的大量警报。警报关联将这些不同的症状关联起来，以准确识别需要处理的问题，因此是网络运营和管理(OAM)的核心组件。随着企业对网络系统的依赖增加，OAM消耗的信息技术预算比例越来越高，目前估计为65%-90%，这主要是由于高昂的劳动力成本。告警关联的自动化可以大幅降低OAM成本，同时提高其质量。系统管理艺术公司预计，基于编码理论的技术可以在报警关联性能方面比目前的技术提高2个数量级，同时提高其准确性和稳健性。

This Small Business Innovation Research Phase I project focuses on applying coding theory techniques to automate alarm correlation in complex networks. Alarms indicate exceptional network states or behaviors, e.g., failure or congestion, which require immediate handling to avoid disrupting network operations. In a networked system, a single problem can result in large numbers of alarms manifested by multiple system components. Alarm correlation correlates these various symptoms to accurately identify the problems requiring handling, and is thus a central component in network operations and management (OAM). As enterprises' reliance on networked systems grows, OAM consumes an increasingly higher percentage of information technology budgets, currently estimated at 65-90%, mainly due to high labor costs. Automation of alarm correlation can substantially reduce OAM costs while improving their quality. System Management Arts, Inc., anticipates that techniques based on coding theory can yield up to 2 orders of magnitude improvement in alarm correlation performance over today's techniques, while increasing both their accuracy and robustness.