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.
