DYSWIS: Crowdsourcing a home network diagnosis

Existing failure diagnostic techniques for end users are insufficient to pinpoint the root causes of network failures due to their limited capabilities to probe other network elements. We present DYSWIS, an automatic network fault detection and diagnosis system for end-users. DYSWIS leverages user collaboration to distinguish important network faults from false positive indications, and diagnoses the root cause of the fault using diagnostic rules that consider diverse information from multiple nodes. Our rule system is specially designed to support crowdsourcing and distributed probes. We have implemented DYSWIS and compared its performance with other tools to prove that several network failures which are difficult to be diagnosed by the single-user probe can be detected and diagnosed successfully with our approach.