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S-Cube session

Schedule : 9H00 – 10H20
Chairman : L. Lizzi
Place : Amphi

Topic : This session will focus on WSN challenges


9H00 – 9H20 : Invited paper
SNW-MAC: an Asynchronous Protocol Leveraging Wake-up Receivers for Data Gathering in Star Networks”

Fayçal Ait Aoudia 1, Matthieu Gautier 1, Michele Magno 2, Olivier Berder 1, and Luca Benini 2
1 University of Rennes 1, IRISA, France, 2 ETH Zürich

Abstact : A widespread approach to extend lifetime of battery-powered wireless sensor nodes is duty-cycling, which consists in periodically switching on and off node transceiver. However, energy waste in idle listening periods is still a bottleneck. These periods can be completely removed using emerging ultra-low power wake-up receivers, which continuously listen to the channel with negligible power consumption. In this paper, an asynchronous medium access control protocol is proposed for data gathering in a star network topology. The protocol exploits state-of-the-art wake-up receivers to minimize the energy required to transmit a packet and to make collisions impossible. The proposed approach has been implemented on a real hardware platform and tested in-field. Experimental results demonstrate the benefits of the proposed approach in terms of energy efficiency, power consumption and throughput, which can be up to more than two times higher compared to traditional schemes.

9H20 – 9H40 : “266727: Energy consumption and data amount reduction using object detection on WSN nodes”

Boris Snajder, Zoran Kalafatic, and Vedran Bilas
University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia

Abstract : High resolution image handling often results with high energy burden for battery-powered devices, such as sensor nodes in WSN. Motivation for this study is assessment of energy consumption of the sensor node with high-resolution camera, featuring image processing. We present a selection of object detection algorithms and evaluate their efficiency. To verify applicability of those algorithms, we acquired image sequence that correspond to applications of pests detection in agriculture. We verified considered algorithms’ performances: recall, precision and expected reduction of the data amount. Energy required to execute considered algorithms was measured on ARM processor based platform. Our results show that object extraction on a node can provide reduction of the data amount by up to three orders of magnitude. While simple algorithms can lead to lower overall energy consumption of the node, the more complex algorithm provides better performances, but at a cost of prohibitively high energy consumption.

9H40 – 10H00 : “266991 Comparison of Different Reconfigurable Directional Antennas for Improving WSN Autonomy

Trong Nhan Le 1, Alain Pegatoquet 1, Trinh Le Huy 2, Leonardo Lizzi 1 and Fabien Ferrero 1
1 Universit´e Cote d’azur, CNRS, LEAT, Batiment forum, Campus SophiaTech, 06903 Sophia Antipolis Cedex, France,
2 University of Information and Technology, National University Ho Chi Minh City, Vietnam

Abstract : Most of the Wireless sensor networks (WSN) are using passive Omni-Directionnal antennas (ODA). Reconfigurable Directional Antennas (RDA) have the potential to reduce data collision and increase the communication range when compared to ODA solution. In this paper, a comparison of two different RDA specifically designed for WSNs, including the Single Pole N Through (SPNT) and the Digital Tunable Capacitor (DTC), is presented. In order to demonstrate the benefits of using RDAs in terms of Received Signal Strength Indicator (RSSI), Packet Error Rate (PER), data collision avoidance and end-to-end delay, OMNeT++ simulations are performed for a single hop autonomous WSN. Moreover, a mobility scenario is also used to investigated the adaptability of using RDAs in the context of WSNs.


10H00 – 10H20 :
266939 Monitoring Approach of Cyber-physical Systems by Quality Measures”

Pedro Merino Laso 1, David Brosset 1,2, and John Puentes1,3
1 Chair of Naval Cyber Defense, Ecole navale – CC 600 F29240 Brest Cedex 9, France ´
2 Naval Academy Research Institute, Ecole navale – CC 600 F29240 Brest Cedex 9, France ´
3 Departement ITI – Institut Mines-Telecom;Telecom Bretagne, Lab-STICC UMR CNRS 6285 Equipe DECIDE, CS 83818 29238 Brest, France ´

Abstact : Nowadays, cities, industrial plants, cars, trucks, and vessels make extensive use of cyber-physical systems and sensors. These systems are very critical and contribute to assist decision making. Large data streams are thus produced and analyzed to extract information that allows building knowledge through a set of principles called wisdom. However, because of multiple imperfections, as well as intrinsic, contextual, and extrinsic conditions that alter data, the quality of the generated streams must be evaluated, to determine how relevant they are for decision support. This paper presents a methodology for quality estimation, which defines suitable evaluation characteristics for pertinent analysis. Quality assessment is defined for data imperfections, information dimensions, knowledge factors, and wisdom aspects. The case study of a cyber-physical network of a liquid container training platform is presented in detail, to show how the approach can be applied. Future works will use this methodology for detecting anomalies in other cyber physical systems.