Low-energy algorithm for self-controlled Wireless Sensor Nodes

• Published in: 2016 International Conference on Wireless Networks and Mobile Communications (WINCOM) pp. 42 - 46
• Main Authors: bin Baharudin, Ahmad Muzaffar, Saari, Mika, Sillberg, Pekka, Rantanen, Petri, Soini, Jari, Kuroda, Tadahiro
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2016
• Subjects: Compressed sensing; Data communication; Data compression; Intelligent Sensing; Internet of Things (IoT); Low-Energy Algorithm; Power demand; Radio frequency; Wireless communication; Wireless sensor networks
• DOI: 10.1109/WINCOM.2016.7777188

In Internet of Things (IoT), the lifespan of Wireless Sensor Networks (WSN) has often become an issue. Sensor nodes are typically battery powered. However, high energy consumption by Radio Frequency (RF) module limits the lifespan of sensor nodes. In conventional WSN, the frequency of data transmission is normally fixed or adjusted according to requests from the gateway. In this paper, we present a WSN system for intelligent sensing. We propose a low-energy algorithm for sensor data transmission from sensor nodes for such system. In this algorithm, the sensor nodes are able to self-control their data transmission according to the trends of data. We adopt Adaptive Duty Cycle for adjustment of data transmission frequency and Compressive Sensing (CS) for sensor data compression. The simulation results show that Collective Transmission with CS-based data compression achieves 83.34% of RF energy reduction for the best-case transmission and 83.31% of RF energy reduction in the worst-case transmission, compared to the Continuous Transmission.