Intelligent video surveillance (IVS) systems are based on the recent development of so called embedded smart cameras. Delivering a good service quality in IVS usually results in a higher level of computing activity and therefore in increased power consumption.This work presents PoQoS, a novel approach that aims in maximizing the service quality (i.e., the number of IVSservices and their QoS) while minimizing the system's power consumption. PoQoS enables power-aware reconfiguration of services and hardware resources in distributed logical clusters of embedded smart cameras. In order to find optimal camera configurations during operation, Po-QoS integrates PoSeGA, an online genetic multi-criterion optimization algorithm. A configuration manager properly selects among optimized camera configurations and consequently initializes intra-camera or intra-cluster poweraware reconfiguration with respect to application-and situation-specific context.The evaluation of PoQoS on the PoQoCam, a powerefficient embedded smart camera platform, shows the feasibility of the presented approach.
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 reconfiguration 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 reconfigurations 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 configuration by trading off quality of service (QoS), energy consumption, and service availability. We demonstrate the functionality of our approach by an illustrative example.
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