Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
On Distributed Fault-Tolerant Detection in Wireless Sensor Networks
IEEE Transactions on Computers
Distributed fault detection of wireless sensor networks
DIWANS '06 Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks
Fault-Tolerant Systems
A Survey of Fault Management in Wireless Sensor Networks
Journal of Network and Systems Management
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Fault detection of wireless sensor networks
Computer Communications
Developing cooperation mechanism for multi-agent systems with Petri nets
Engineering Applications of Artificial Intelligence
Error control in wireless sensor networks: a cross layer analysis
IEEE/ACM Transactions on Networking (TON)
FIND: faulty node detection for wireless sensor networks
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Detection and diagnosis of data inconsistency failures in wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
IEEE Communications Letters
Fault diagnosis of sensor by chaos particle swarm optimization algorithm and support vector machine
Expert Systems with Applications: An International Journal
Fault detection in wireless sensor networks: a hybrid approach
Proceedings of the 11th international conference on Information Processing in Sensor Networks
Hi-index | 0.00 |
In most fault-detection algorithms in wireless sensor networks (WSNs), each sensor compares its data with the data of neighboring nodes. The majority of comparative methods will not work properly if more than half of the neighboring nodes of a sensor are faulty. Moreover, such comparative methods are unable to detect common mode failures (CMFs). Hence, having noticed the deficiencies of the existing comparative methods and as a reaction against such problems, we introduced a novel self-diagnosing approach to reduce the effect of neighboring node's data in determining the status of nodes so that a sensor's status will be determined independently of any comparisons. A sensor will be deemed to be fault-free if its components and the inner links between the components are flawless. In this paper, the behaviors of the components of a sensor are independently analyzed by means of the proposed model based on Petri nets and the links of the sensor's components are investigated by means of the correlation graph. In addition, the authors extended and generalized the proposed method to all the nodes of a network and evaluated their operation. Simulation results showed that the modeling implemented by the HPSim tool can cover both permanent and transient faults accurately. Moreover, using the correlation graph and Pearson correlation coefficient helped us to gain confidence in the correctness of the inner links between the components of a sensor. Evaluation of the results indicated that the statistical results from the QI Macros tool were substantially similar to those from HPSim and Matlab tools. Furthermore, simulations results demonstrated that the detection accuracy and false alarm rate of the proposed method is acceptable even when the fault probability of each sensor is generally to be high. As a result, using these mechanisms leads to the development of the self-diagnosing capability in the sensors of a WSN.