An Open-Space Museum as a Testbed for Popularity Monitoring in Real-World Settings

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This paper reports our experience with crowd monitoring technologies in the challenging real-world conditions of a modern, open-space museum. We seized the opportunity to use the NEMO science center as a testbed, and studied the effectiveness of neighborhood discovery and density estimation algorithms in a network formed by visitors wearing bracelets emitting RF beacons. The diverse set of conditions (flash crowds in open spaces vs. single person booths) revealed three interesting findings: (i) state-of-the-art density estimation fails in 80% of the cases, (ii) RSS-based classifiers fail too, because their underlying assumptions do not hold in many scenarios, and (iii) neighborhood discovery can obtain exact information in an energy-efficient way, provided that static and mobile nodes are differentiated to filter out “passers by” clobbering the true popularity of an exhibit. The overall lesson from the experiment is that today’s algorithms are quite far from the ideal of monitoring popularity in a privacy-preserving and energy-efficient way with minimal infrastructure across the set of heterogeneous conditions encountered in practice.

Acm Digital Library | Paper

Authors: Marco Cattani and Ioannis Protonotarios and Claudio Martella and and Joost Van Velzen and Marco A. Zuniga and Koen G. Langendoen
Research groups:  Embedded Software group, Delft University of Technology and  Large-scale Distributed Systems group, VU University Amsterdam
Conference:  International Conference on Embedded Wireless Systems and Networks (EWSN)
Year: 2017

SOFA: Communication in Extreme Wireless Sensor Networks

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Sensor networks can nowadays deliver 99.9% of their data with duty cycles below 1%. This remarkable performance is, however, dependent on some important underlying assumptions: low traffic rates, medium size densities and static nodes. In this paper, we investigate the performance of these same resource-constrained devices, but under scenarios that present extreme conditions: high traffic rates, high densities and mobility. To cope with these stringent requirements, we propose a novel communication protocol named SOFA (Stop On First Ack). SOFA utilizes opportunistic anycast to drastically reduce the rendezvous times of asynchronous duty cycled nodes -long rendezvous times are the key limitation of protocols operating under high densities and high traffic conditions. SOFA is also stateless, which makes it resilient to mobility. We implemented SOFA in the Contiki OS and tested it both in simulation and on a 100-node testbed. Our results show that SOFA reliably communicates in mobile networks with extreme densities (hundreds of nodes) and higher traffic rates (packets per second) while maintaining a low duty cycle (~2%). Under these extreme conditions, current duty cycled protocols collapse.

In the first video, we use SOFA to run a push-pull, gossip-based protocol that computes the average of the nodes’ values. Nodes’ values are shown in red, while the averages are shown in black. In the second video, we run SLICE, a push-pull, gossip-based protocol to automatically partition the nodes’ values into “slices”. In this case the nodes’ values (in red) are partitioned in percentiles (in black). The experiment was recorded in real-time speed (1x) in the TU Delft testbed.

Download pdf | Springer Library | SlidesSource code on GitHub

AuthorsMarco Cattani and Marco A. Zuniga and Matthias Woehrle and Koen G. Langendoen
Research group: Embedded Software group, Delft University of Technology, Delft, Netherlands
Conference11th European Conference on Wireless Sensor Network (EWSN)
Year: 2014