Active integrated fault localization in communication networks

Abstract

Fault localization is a core element in fault management. Many fault reasoning techniques use deterministic or probabilistic symptom-fault causality model for fault diagnoses and localization. Symptom-fault map is commonly used to describe symptom-fault causality in fault reasoning. However, due to lost and spurious symptoms in fault reasoning systems that passively collect symptoms, the performance and accuracy of the fault localization can be significantly degraded. In this paper, we propose an extended symptom-fault-action model to incorporate actions into fault reasoning process to tackle the above problem. This technique is called active integrated fault reasoning (AIR), which contains three modules: fault reasoning, fidelity evaluation and action selection. Corresponding fault reasoning and action selection algorithms are elaborated. Simulation study shows both performance and accuracy of fault reasoning can be greatly improved by taking actions, especially when the rate of spurious and lost symptoms is high.