SCAN-Fault: Scalable Autonomic Fault Detection and Root-Cause Analysis in a Heterogeneous Network

To support reliable and secure communications, a suitable network analysis tool is needed for accurately and efficiently detecting, diagnosing, and predicting faults in the network. In tactical networks, faults can be very common, and are typically hard and time consuming to detect, isolate and fix. Moreover, in a heterogeneous network, a small network problem along any part of an end-to-end path can potentially degrade the user experience significantly. But identifying and resolving this problem may require knowledge and action across different domains and planes. Furthermore, fault analysis schemes designed for the traditional networks are not fully suitable to wireless networks such as mobile ad hoc networks and cognitive radio networks. To address these issues, Intelligent Automation, Inc. (IAI) proposes to develop a SCalable AutoNomic Fault detection and root-cause analysis (SCAN-Fault) scheme that can analyze the monitored network as a whole and assist the users (i.e., network operators) in maintaining, optimizing, and securing the managed network. The proposed approach will significantly improve the reliable and secure access to battlefield network, and reduce the cost and risks for network management.