Tobias Hamann

dblp:216/5585 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

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

Computer networks · 1Security and privacy · 1

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 · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › wireless sensor network › duty cycling
adaptive duty cycling
0.312017
Light in the Box: Reproducible Lighting Conditions for Solar-Powered Sensor Nodes · SenSys 2017
Internet of things and sensor networks › energy harvesting
energy harvesting sensor networks
0.312017
Light in the Box: Reproducible Lighting Conditions for Solar-Powered Sensor Nodes · SenSys 2017

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

light replay testbed · 0.3energy-aware algorithm comparison · 0.3
YearPublicationVenuePosition
2018 An Evaluation of Bucketing in Systems with Non-deterministic Timing Behavior
Yuri Gil Dantas, Richard Gay, Tobias Hamann, Heiko Mantel, Johannes Schickel
SEC3
2017 Light in the Box: Reproducible Lighting Conditions for Solar-Powered Sensor Nodes
abstract
The restricted energy budget of energy-harvesting sensor nodes demands algorithms for adaptive duty-cycling. However, their comparison and development is hindered by the lack of reproducibility of environmental conditions. We enable replaying recorded light conditions by building an affordable light box. Our self-developed control circuit and high power LEDs allow us to repeatedly replay real environmental illumination data through current and voltage traces. This allows us to directly compare the behavior of nodes running different energy-aware and -predictive algorithms.
Lars Hanschke, Christian Renner, Jannick Brockmann, Tobias Hamann, Jannes Peschel, Alexander Schell, Alexander Sowarka
SenSys4