Anomaly-Detection and Health-Analysis Techniques for Core Router Systems [Hardcover]

This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to todays Internet Protocol (IP) networks. The techniques described provide the first comprehensive set of data-driven resiliency solutions for core router systems. The authors present an anomaly detector for core router systems using correlation-based time series analysis, which monitors a set of features of a complex core router system. They also describe the design of a changepoint-based anomaly detector such that anomaly detection can be adaptive to changes in the statistical features of data streams. The presentation also includes a symbol-based health status analyzer that first encodes, as a symbol sequence, the long-term complex time series collected from a number of core routers, and then utilizes the symbol sequence for health analysis. Finally, the authors describe an iterative, self-learning procedure for assessing the health status.

Introduction.- Anomaly Detection Using Correlation-Based Time-Series Analysis.- Changepoint-based Anomaly Detection.- Hierarchical Symbol-based Health-Status Analysis.- Self-Learning Health-Status Analysis.- Conclusion.

Shi Jin is a Senior DFT Engineer at Nvidia Corporation, in Santa Clara, California.

Zhaobo Zhang is a Staff Engineer at Huawei Technologies, in Santa Clara, California.

Krish Chakrabarty is the William H. Younger Distinguished Professor of Engineering in the Department of Electrical and Col£8