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

Abstract

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.

A novel software framework for embedded multiprocessor smart cameras

“…The dynamic loading facilities are also the basis for more sophisticated services like load distribution [Bramberger 2005], dynamic power management [Maier 2006], and graceful degradation to cope with faults. …”

An Efficient Middleware for Power-Aware Service Reconfiguration in Multi-DSP Smart Cameras

“…An advantage of this method is a more autonomous system behavior instead of using pre-defined modes for reconfiguration [10]. As a consequence, reconfiguration is utilized on both cluster-and camera-evel.…”

“…It performs a randomized computation of feasible Pareto-optimal camera configurations and is described in more detail in [10].…”