Abstract
Wireless sensor networks have been considered as an effective solution to a wide range of applications due to their prominent characteristics concerning information retrieving and distributed processing. When visual information can be also retrieved by sensor nodes, applications acquire a more comprehensive perception of monitored environments, fostering the creation of wireless visual sensor networks. As such networks are being more often considered for critical monitoring and control applications, usually related to catastrophic situation prevention, security enhancement and crises management, fault tolerance becomes a major expected service for visual sensor networks. A way to address this issue is to evaluate the system dependability through quantitative attributes (e.g., reliability and availability), which require a proper modeling strategy to describe the system behavior. That way, in this paper, we propose a methodology to model and evaluate the dependability of wireless visual sensor networks using Fault Tree Analysis and Markov Chains. The proposed modeling strategy considers hardware, battery, link and coverage failures, besides considering routing protocols on the network communication behavior. The methodology is automated by a framework developed and integrated with the SHARPE (Symbolic Hierarchical Automated Reliability and Performance Evaluator) tool. The achieved results show that this methodology is useful to compare different network implementations and the corresponding dependability, enabling the uncovering of potentially weak points in the network behavior.
Highlights
Wireless Sensor Networks (WSNs) are nowadays a trend as a support technology for many types of monitoring applications
This paper focuses on how redundancy should be considered to improve the availability level of Wireless VisualSensor Networks (WVSNs), with respect to a camera’s field of view (FoV) overlapping, sensing similarity and sensing relevance
The battery behavior presented in Equation (5) is nonlinear and cannot be modeled using the same reasoning of the hardware modeling. To cope with this problem and to evaluate the battery availability, we propose an approximation of the nonlinear battery discharging behavior by a stochastic process, following the approach proposed by Bruneo et al [60]
Summary
Wireless Sensor Networks (WSNs) are nowadays a trend as a support technology for many types of monitoring applications. A street lighting application triggered by motion sensors can be wrongly activated upon the presence of birds; a traffic light control system can better manage its time intervals with an image of how many people or cars are occupying the sidewalk or the road; an intelligent transportation system can use images to detect a car accident and call the proper authorities in addition to the obvious usage of visual data, like surveillance, face detection, intrusion detection, etc All of these problems can be supported by the use of adequate Wireless Visual. Sensor Networks (WVSNs) [2,3,4].
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