Demo Data from EDBT 2026 / reviewers in the wild / expert
Tobias Vaegs
dblp:03/8070
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2Human-computer interaction and ubiquitous computing · 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
3 papers |
Internet of things and sensor networks · 34% Routing and switching · 31% Internet architecture and protocols · 15% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks
wireless sensor network |
0.2 | 2 | 2011 | Probabilistic addressing: Stable addresses in unstable wireless networks · IPSN 2011 Statistical vector based point-to-point routing in wireless networks · IPSN 2010 |
Routing and switching
geographic routing |
0.1 | 2 | 2011 | Statistical vector based point-to-point routing in wireless networks · IPSN 2010 Probabilistic addressing: Stable addresses in unstable wireless networks · IPSN 2011 |
Internet architecture and protocols › naming and addressing
addressing |
0.1 | 1 | 2011 | Probabilistic addressing: Stable addresses in unstable wireless networks · IPSN 2011 |
Wireless networking › mobile ad hoc networks
floating content |
0.1 | 1 | 2011 | Floating content: Information sharing in urban areas · PerCom 2011 |
Internet of things and sensor networks
opportunistic networks |
0.1 | 1 | 2011 | Floating content: Information sharing in urban areas · PerCom 2011 |
Routing and switching
wireless routing |
0.1 | 1 | 2010 | Statistical vector based point-to-point routing in wireless networks · IPSN 2010 |
Content delivery and video streaming
content sharing |
0.0 | 1 | 2011 | Floating content: Information sharing in urban areas · PerCom 2011 |
Methods — techniques the papers use, named apart from their topics
probabilistic addressing · 0.1mobility simulation · 0.1analytical modeling · 0.1statistical vector routing · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Probabilistic addressing: Stable addresses in unstable wireless networks
Muhammad Hamad Alizai, Tobias Vaegs, Olaf Landsiedel, Stefan Götz 0001, Jó Ágila Bitsch, Klaus Wehrle |
IPSN | 2 |
| 2011 | Floating content: Information sharing in urban areasabstractContent sharing using personal web pages, blogs, or online social networks is a common means for people to maintain contact with their friends, colleagues, and acquaintances. While such means are essential to overcome distances, using infrastructure services for location-based services may not be desirable. In this paper, we analyze a fully distributed variant of an ephemeral content sharing service, solely dependent on the mobile devices in the vicinity using principles of opportunistic networking. The net result is a best effort service for floating content in which: 1) information dissemination is geographically limited; 2) the lifetime and spreading of information depends on interested nodes being available; 3) content can only be created and distributed locally; and 4) content can only be added, but not explicitly deleted. First we present our system design and summarize its analytical modeling. Then we perform extensive evaluation for a map-based mobility model in downtown Helsinki to assess the operational range for floating content, which, at the same time also validate the analytical results obtained for a more abstract model of the system. Jörg Ott, Esa Hyytiä, Pasi E. Lassila, Tobias Vaegs, Jussi Kangasharju |
PerCom | 4 |
| 2010 | Statistical vector based point-to-point routing in wireless networksabstractWe present Statistical Vector Routing (SVR), a protocol that efficiently deals with communication link dynamics in wireless networks. It assigns virtual coordinates to nodes based on the statistical distribution of their distance from a small set of beacons. The distance metric predicts the current location of a node in its address distribution. Our initial results from a prototype implementation over real testbeds demonstrate the feasibility of SVR. Muhammad Hamad Alizai, Tobias Vaegs, Olaf Landsiedel, Raimondas Sasnauskas, Klaus Wehrle |
IPSN | 2 |