Control-based event-driven bandwidth allocation scheme for video-surveillance systems

Abstract

Modern computer systems consist of large number of entities connected through a shared resource. One such system is a video surveillance network consisting of a set of cameras and a network manager. The surveillance cameras capture a stream of images, encode them with a quality factor and transmit them to the manager over a shared constrained network. The central manager allocates bandwidth to the cameras in a fair manner using a threshold based gametheoretic approach. The presence of these multiple control loops that interact with each other leads to complexity in providing performance and safety guarantees. Our previous work explored performance of the eventbased manager using model checking to verify relevant properties of linear models. In this paper we build on our previous work by verifying complex camera models that capture uncertainties during image capture. We model the uncertainties using probabilistic Markov Decision Processes (MDPs) and verify relevant properties of the system. We also evaluate system performance for different system parameters with varying triggering thresholds, showing the advantage of model checking for safe and informed parameter selection. Finally, we evaluate the effect of varying thresholds on manager interventions by capturing images on a commercial off-the-shelf (COTS) camera test-bed.

Engineering Self-Adaptive Capabilities in Wireless Sensors Based on Control Algorithms and Model-Based Design Methodologies

“…The control action has been designed based on a dynamic model of hardware and software resources, which use the flow of resources as a common entity. Moreover, Nayak Seetanadi et al [32] have designed a solution based on control engineering to optimize both the resource consumption and allocation by the cameras in a video-surveillance system.…”