6533b85bfe1ef96bd12bbf47

RESEARCH PRODUCT

A distributed real-time data prediction and adaptive sensing approach for wireless sensor networks

Jacques DemerjianGaby Bou TayehAbdallah MakhoulDavid Laiymani

subject

Adaptive samplingComputer Networks and CommunicationsComputer scienceReal-time computing[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technology[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringReal-time dataWork (physics)020206 networking & telecommunicationsEnergy consumption[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science Applications[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Hardware and Architecture[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]020201 artificial intelligence & image processing[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Wireless sensor networkSoftwarePredictive modellingEnergy (signal processing)Information SystemsData reduction

description

International audience; Many approaches have been proposed in the literature to reduce energy consumption in Wireless Sensor Networks (WSNs). Influenced by the fact that radio communication and sensing are considered to be the most energy consuming activities in such networks. Most of these approaches focused on either reducing the number of collected data using adaptive sampling techniques or on reducing the number of data transmitted over the network using prediction models. In this article, we propose a novel prediction-based data reduction method. furthermore, we combine it with an adaptive sampling rate technique, allowing us to significantly decrease energy consumption and extend the whole network lifetime. To validate our work, we tested our approach on real sensor data collected at our offices. The final results were promising and confirmed our theoretical claims.

https://doi.org/10.1016/j.pmcj.2018.06.007