Online multi-criterion optimization for dynamic power-aware camera configuration in distributed embedded surveillance clusters

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 paper presents PoQoS, a novel approach that aims in maximizing the service quality (i.e., the number of IVS-services 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, PoQoS 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 power-aware reconfiguration with respect to application- and situation-specific context. The evaluation of PoQoS on the PoQoCam, a power-efficient embedded smart camera platform, shows the feasibility of the presented approach.