Sharing end-user negative symptoms for improving overlay network dependability

The dependability of overlay services rely on the overlay network´s capabilities to effectively diagnose and recover faults (e.g., link failures, overlay node outages). However, overlay applications bring to overlay fault diagnosis new challenges, which include large-scale deployment, inaccessible underlying network information, dynamic symptom-fault causality relationship, and multi-layer complexity. In this paper, we develop an evidential overlay fault diagnosis framework (called DigOver) to tackle these challenges. Firstly, the DigOver identifies a set of potential faulty components based on shared end-user observed negative symptoms. Then, each potential faulty component is evaluated to quantify its fault likelihood and the corresponding evaluation uncertainty. Finally, the DigOver dynamically constructs a plausible fault graph to locate the root causes of end-user observed negative symptoms.