Network Fault Diagnosis: An Artificial Immune System Approach

Artificial immune systems (AIS) have been widely used in many fields such as data analysis, multimodal function optimization, error detection, etc. In this paper, we introduce a novel artificial immune systems approach for diagnosing faults in a network of processors under the PMC model. We investigate how AIS can be used for system-level fault diagnosis. Our theoretical analysis and experimental results demonstrate the effectiveness of the AIS-based diagnosis approach for small and large class of networks in both the worst and average cases, making it a viable alternative to traditional fault diagnosis approaches.