Network Data Processing and Storage

As the size of networks increases, real-time fault management becomes difficult due to the volume of traffic. A single problem can generate numerous symptoms, which are received as events by a network management system. These events could be correlated to deduce the source of the problem. One of the correlation techniques used is codebook approach, developed by Yemini et. al. Codebook is a matrix relating problems with symptoms. We present a way to transform the original algorithm used in deriving the codebook. Our algorithm improves the efficiency by reducing the matrix as well as by ensuring the selection of minimum number of symptoms required to uniquely identify each problem in the codebook. This avoids an exponential growth in the number of symptoms as number of problems increase, which in turn shows up as saving in real-time processing.