A Framework and Classification for Fault Detection Approaches in Wireless Sensor Networks with an Energy Efficiency Perspective

Wireless Sensor Networks (WSNs) are more and more considered a key enabling technology for the realisation of the Internet of Things (IoT) vision. With the long term goal of designing fault-tolerant IoT systems, this paper proposes a fault detection framework for WSNs with the perspective of energy efficiency to facilitate the design of fault detection methods and the evaluation of their energy efficiency. Following the same design principle of the fault detection framework, the paper proposes a classification for fault detection approaches. The classification is applied to a number of fault detection approaches for the comparison of several characteristics, namely, energy efficiency, correlation model, evaluation method, and detection accuracy. The design guidelines given in this paper aim at providing an insight into better design of energy-efficient detection approaches in resource-constraint WSNs

Packet-Level Attestation (PLA):A framework for in-network sensor-data reliability

Wireless sensor networks (WSN) show enormous potential for collection and analysis of physical data in real-time. Many papers have proposed methods for improving the network reliability of WSNs. However, real WSN deployments show that sensor data-faults are very common. Several server-side data reliability techniques have been proposed to detect these faults and impute missing or erroneous data. Typically, these techniques reduce the lifetime of the network due to redundant data transmission, increase latency, and are computation and storage intensive. Herein, we propose Packet-Level Attestation (PLA), a novel framework for sensor data reliability assessment. It exploits the spatial correlation of data sensed at nearby sensors. The method does not incur additional transmission of control message between source and sink; instead, a verifier node sends a validation certificate as part of the regular data packet. PLA was implemented in TinyOS on TelosB motes and its performances was assessed. Simulations were performed to determine its scalability. It incurs only an overhead of 1.45% in terms of packets transmitted. Fault detection precision of the framework varied from 100% to 99.48%. Comparisons with existing methods for data reliability analysis showed a significant reduction in data transmission, prolonging the network lifetime.Higher Education AuthorityScience Foundation Irelan

Packet-Level Attestation (PLA):a framework for in-network sensor data reliability

Wireless sensor networks (WSN) show enormous potential for collection and analysis of physical data in real-time. Many papers have proposed methods for improving the network reliability of WSNs. However, real WSN deployments show that sensor data-faults are very common. Several server-side data reliability techniques have been proposed to detect these faults and impute missing or erroneous data. Typically, these techniques reduce the lifetime of the network due to redundant data transmission, increase latency, and are computation and storage intensive. Herein, we propose Packet-Level Attestation (PLA), a novel framework for sensor data reliability assessment. It exploits the spatial correlation of data sensed at nearby sensors. The method does not incur additional transmission of control message between source and sink; instead, a verifier node sends a validation certificate as part of the regular data packet. PLA was implemented in TinyOS on TelosB motes and its performances was assessed. Simulations were performed to determine its scalability. It incurs only an overhead of 1.45% in terms of packets transmitted. Fault detection precision of the framework varied from 100% to 99.48%. Comparisons with existing methods for data reliability analysis showed a significant reduction in data transmission, prolonging the network lifetime.</jats:p