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Tobias Gatschet

dblp:305/9168 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 87% Wireless networking · 13%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › iot networks › iot communication › sensor network communication
event-driven communication
0.512021
STeC: Exploiting Spatial and Temporal Correlation for Event-based Communication in WSNs · SenSys 2021
Internet of things and sensor networks › wireless sensor network
spatial and temporal correlation
0.512021
STeC: Exploiting Spatial and Temporal Correlation for Event-based Communication in WSNs · SenSys 2021

Methods — techniques the papers use, named apart from their topics

trace-based experimentation · 0.5
YearPublicationVenuePosition
2021 STeC: Exploiting Spatial and Temporal Correlation for Event-based Communication in WSNs
abstract
Low-power wireless sensor networks have demonstrated their potential for the detection of rare events such as rockfalls and wildfires, where rapid reporting as well as long-term energy-efficient operation is vital. However, current systems require periodic synchronization to maintain network coordination, heavily rely on node placement or use costly long-range links to infrastructure. We present STeC, a novel wireless communication design that directly exploits the spatial and temporal correlation of signals from the sensed phenomenon to orchestrate event-based communication. We leverage the locality of a co-detection, where a physical event triggers multiple sensors quasi-simultaneously, to efficiently collect, characterize and report sensor data. This eliminates the overhead of periodic network activity and centralized control, resulting in more energy-efficient communication with a lower, more consistent detection latency. In doing so, we propose a fundamentally new approach to avoid the elementary conflict between duty cycle and latency requirements immanent to synchronous protocols by exploiting correlated sensor signals for networking. Experiments using real-world traces of a natural hazard detection application show that STeC reduces the detection latency by up to 87 % compared to standard single-hop communication and outperforms traditional schedule-based methods by up to 58.4 x in energy efficiency.
Andreas Biri, Reto Da Forno, Tonio Gsell, Tobias Gatschet, Jan Beutel, Lothar Thiele
SenSys4