Intelligence Enabled SDN Fault Localization via Programmable In-band Network Telemetry
Yongning Tang, Yangxuan Wu, Guang Cheng, Zhiwei Xu · 2019
Intelligent Fault localization for SDN becomes one of the most critical but difficult tasks. This paper proposes a new approach called Policy-Aware In-band Network Telemetry (PAINT) to tackle SDN fault localization. In the PAINT system, network operators define and deploy network services using a high-level Service Provisioning Language (SPL). Then, PAINT automatically parses the service policy to infer the causal relationship between service related network components and (end-to-end) service-level observable symptoms. Based on the causality model, PAINT deploys monitoring instruments for the symptoms. PAINT utilizes a dynamically created Symptom-Fault-Telemetry model to incorporate In-band Network Telemetry (INT) actions systematically into the fault reasoning process to improve the efficiency and accuracy of fault localization for SDN. PAINT has been extensively evaluated in a simulation environment for its accuracy and scalability with very positive results.