Year-end Sale % OFF 
Abstract
Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept “Internet of Things” has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed.
Highlights
Wireless sensor networks (WSNs) are networks of tiny, low cost, low energy, and multifunctional sensors which are densely deployed to monitor a phenomenon, track an object, or control a process [1].Wireless Sensor Networks (WSNs) are used in many application domains which include: personal applications such as home automation; business applications such as sales tracking; industrial applications such as architectural and control; and military applications such as enemy target monitoring and tracking [1,2,3]
A variety of anomaly detection models were proposed in the literature; most of them suffer from low detection effectiveness or high energy consumption
We studied the challenges that face the design of an efficient and effective anomaly detection model for WSNs and stated the requirements (RODAC components) that should be satisfied to design such models
Summary
Wireless sensor networks (WSNs) are networks of tiny, low cost, low energy, and multifunctional sensors which are densely deployed to monitor a phenomenon, track an object, or control a process [1].WSNs are used in many application domains which include: personal applications such as home automation; business applications such as sales tracking; industrial applications such as architectural and control; and military applications such as enemy target monitoring and tracking [1,2,3]. Wireless sensor networks (WSNs) are networks of tiny, low cost, low energy, and multifunctional sensors which are densely deployed to monitor a phenomenon, track an object, or control a process [1]. According to [6], the future internet as known by IoT is expected to be a “world-wide network of interconnected objects uniquely addressable, based on standard communication protocols”. The most critical constraint on the sensor nodes is the energy consumption, since these nodes have very limited and unchangeable power sources. As a result, this restriction influences the design of WSN protocols or algorithms. The energy is consumed in three forms: sensing, data processing, and communication operations
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
