Improving Fault-Tolerance in Intelligent Video Surveillance by Monitoring, Diagnosis and Dynamic Reconfiguration

In this paper, we present an approach for improving fault-tolerance and service availability in intelligent video surveillance (IVS) systems. A typical IVS system consists of various intelligent video sensors that combine image sensing with video analysis and network streaming. System monitoring and fault diagnosis followed by appropriate dynamic system recon guration mitigate effects of faults and therefore enhance the system's fault-tolerance. The applied monitoring and diagnosis unit (MDU) allows the detection of both node- and system-level faults. Lacking redundant hardware such recon gurations are established by graceful degradation of the overall application. An optimizer module that performs multi-criterion optimization is used to compute a new degraded system con guration by trading off quality of service (QoS), energy consumption, and service availability. We demonstrate the functionality of our approach by an illustrative example.