Improving fault-tolerance in intelligent video surveillance by monitoring, diagnosis and dynamic reconfiguration

Abstract

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.

Faster abnormality localization and recognition in a secured video bitstream by implementation of video encryption techniques

“…The High-Efficiency Video Coding (HEVC) methodology was developed by Liang Zhao et al [9]. Segmenting and classifying moving objects from compressed data is necessary for intelligent video monitoring [10]. In contrast to H.264/AVC, High-Efficiency Video Coding (HEVC) possesses more technical coding characteristics that may be applied to a broader range of situations; for the segmentation and classification of moving objects.…”