Abstract
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.
Highlights
The new paradigm of the Internet of Things (IoT) envisions a computing era outside the realm of the traditional desktop, where devices will be more and more connected, ubiquitous, dynamic, adaptive, and even embedded, so that we will encounter and use them in a variety of contexts, sometimes even without being aware of it
With the long term goal of designing fault-tolerant IoT systems, this paper proposes a fault detection framework for Wireless Sensor Networks (WSNs) with the perspective of energy efficiency to facilitate the design of fault detection methods and the evaluation of their energy efficiency
We investigate a number of existing fault detection approaches and classify them into four categories according to the proposed classification
Summary
The new paradigm of the Internet of Things (IoT) envisions a computing era outside the realm of the traditional desktop, where devices (as well as any kind of object) will be more and more connected, ubiquitous, dynamic, adaptive, and even embedded, so that we will encounter and use them in a variety of contexts, sometimes even without being aware of it. With the rapid technological development of sensors, Wireless Sensor Networks (WSNs) are more and more becoming a key enabling technology to realise the IoT vision [1]. WSNs are regarded as a key information gathering method to build the information and communication infrastructure of future IoT systems. The correctness of sensor data is crucial to WSN applications. Faults are inevitable and WSNs are prone to be faulty [2], which may be due to abnormal software or hardware, poor communication link quality, or depletion of battery. Szewczyk et al [3] classified 3% to 60% of data from each sensor as faulty in a deployment at Great Duck Island. Tolle et al [4] discovered that only 49% of the collected data could be used for meaningful interpretation in a sensor network for examining microclimate surrounding a redwood tree
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