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Stephen M. George

dblp:57/7219 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0001-9011-2097ORCID · corroborated

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

Computer networks · 3Systems, architecture and hardware · 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
2 papers
Wireless sensing and localization · 41% Internet of things and sensor networks · 32% Network measurement and analytics · 21%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › sensor network localization
node localization
0.112012
Asymmetric Event-Driven Node Localization in Wireless Sensor Networks · IEEE Trans. Parallel Distributed Syst. 2012
Internet of things and sensor networks
wireless sensor network
0.112012
Asymmetric Event-Driven Node Localization in Wireless Sensor Networks · IEEE Trans. Parallel Distributed Syst. 2012
Network measurement and analytics › sampling
sub-nyquist sampling
0.112009
Demo abstract: Signal reconstruction with subnyquist sampling using wireless sensor networks · IPSN 2009
Wireless sensing and localization
outdoor localization
0.012012
Asymmetric Event-Driven Node Localization in Wireless Sensor Networks · IEEE Trans. Parallel Distributed Syst. 2012
Physical-layer communications › signal processing for communications
signal recovery
0.012009
Demo abstract: Signal reconstruction with subnyquist sampling using wireless sensor networks · IPSN 2009

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

evaluation · 0.1deployment · 0.1sub-nyquist sampling · 0.1
YearPublicationVenuePosition
2012 Asymmetric Event-Driven Node Localization in Wireless Sensor Networks
abstract
Localization of wireless sensor nodes has long been regarded as a problem that is difficult to solve, especially when considering characteristics of real-world environments. This paper formally describes, designs, implements, and evaluates a novel localization system called Spotlight. The system uses spatiotemporal properties of well-controlled events in the network, light in this case, to obtain locations of sensor nodes. Performance of the system is evaluated through deployments of Mica2 and XSM motes in an outdoor environment, where 20 cm localization error is achieved. A sensor network consisting of any number of nodes deployed in a 2,500 m2area can be localized in under 10 minutes. Submeter localization error in an outdoor environment is made possible without equipping the wireless sensor nodes with specialized ranging hardware.
Radu Stoleru, Tian He 0001, Siddhartha S. Mathiharan, Stephen M. George, John A. Stankovic
IEEE Trans. Parallel Distributed Syst.4
2011 Towards robustness and energy efficiency of cut detection in wireless sensor networks
Myounggyu Won, Stephen M. George, Radu Stoleru
Ad Hoc Networks2
2009 Demo abstract: Signal reconstruction with subnyquist sampling using wireless sensor networks
Andria Pazarloglou, Stephen M. George, Radu Stoleru, Ricardo Gutierrez-Osuna
IPSN2
2009 RE2-CD: Robust and Energy Efficient Cut Detection in Wireless Sensor Networks
Myounggyu Won, Stephen M. George, Radu Stoleru
WASA2