WiRoTip: an IoT-based Wireless Sensor Network for Water Pipeline Monitoring

One of the key components of the Internet of Things (IoT) is the Wireless Sensor Network (WSN). WSN is an effective and efficient technology. It consists of senor nodes; smart devices that allows data collection and pre-processing wirelessly from real world. However, issues related to power consumption and computational performance still persist in classicalwireless nodes since power is not always available in application like pipeline monitoring. Moreover, they could not be usually suitable and adequate for this kind of application due to memory shortage and performance constraints. Designing new IoT WSN system that matches the application specific requirements is extremely important. In this paper, wepresent WiRoTip, a WSN node prototype for water pipeline application. An experimental and a comparative studies have been performed for the different node’s components to achieve a final adequate design

An overview of outlier detection technique developed for wireless sensor networks

International audienceOutliers in wireless sensor networks are measurements that deviate from the normal model of sensed data and result from errors, events or malicious attacks on the network. The dynamic nature of sensor data and the specificity of the wireless sensor network make traditional outlier detection techniques unsuitable for direct application in such contexts so it is essential to select and adapt appropriate techniques to implement in wireless sensor networks for better sensing quality and more reliable system. This paper provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy to be used as a guideline to select a suitable technique for the application at hand based on characteristics such as data type, outlier type and outlier degree

Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are prone to highly constrained resources, as a result ensuring the proper functioning of the network is a requirement. Therefore, an effective WSN management system has to be integrated for the network efficiency. Our objective is to model, design, and propose a homogeneous WSN hybrid architecture. This work features a dedicated power utilization optimization strategy specifically for WSNs application. It is entitled Hybrid Energy-Efficient Power manager Scheduling (HEEPS). The pillars of this strategy are based on the one hand on time-out Dynamic Power Management (DPM) Intertask and on the other hand on Dynamic Voltage and Frequency Scaling (DVFS). All tasks are scheduled under Global Earliest Deadline First (GEDF) with new scheduling tests to overcome the Dhall effect. To minimize the energy consumption, the HEEPS predicts, defines and models the behavior adapted to each sensor node, as well as the associated energy management mechanism. HEEPS’s performance evaluation and analysis are performed using the STORM simulator. A comparison to the results obtained with the various state of the art approaches is presented. Results show that the power manager proposed effectively schedules tasks to use dynamically the available energy estimated gain up to 50%