Automated Methodology for Dependability Evaluation of Wireless Visual Sensor Networks

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.

Modelling Coverage Failures Caused by Mobile Obstacles for the Selection of Faultless Visual Nodes in Wireless Sensor Networks

“…Such maximization can then be exploited to potentially achieve higher redundancy and increased coverage perspectives over multiple targets. Finally, a robust methodology to integrate different types of hardware and communication failures was proposed in [14], but in that work visual sensors are always considered as active and fully functional when concerning coverage failures, which may be unrealistic in many scenarios.…”

“…For example, some works have proposed mechanisms to optimize the way routing paths are created to deliver visual data, as in [11], [12]. In a different perspective, dependability and availability of wireless visual sensor networks have been optimized in the context of visual sensing, as performed in [13], [14]. Moreover, visual coverage optimizations have also been proposed, trying to improve the attainable viewed areas and targets by visual sensors, as in [15], [16].…”

On the Use of Cameras for the Detection of Critical Events in Sensors-Based Emergency Alerting Systems

“…For example, since an EDU will "cover" a particular area, its disconnection may result in emergencies that are not being properly detected: in fact, it may be detected, but the EPU is not being informed. Some previous works have addressed this issue, employing different formalisms for that [44,45], but with some limitations. However, some strategies can be used to enhance reliability even in the presence of emergencies, usually employing wireless communication technologies since they are more resistant to critical situations [46].…”

FoV-Based Quality Assessment and Optimization for Area Coverage in Wireless Visual Sensor Networks

“…Nevertheless, such metrics could be an important require-ment to develop and manage some applications in any context, such as in Industrial 4.0 [2], environmental monitoring [3], mobility tracking [4], Internet of Things [5] or just for network metric analysis, such as in dependability assessment [6].…”