Demo Data from VLDB 2026 / reviewers in the wild / expert
András Tóbiás
dblp:251/5299
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0003-4881-2553ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 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 |
Wireless networking · 50% Routing and switching · 38% Physical-layer communications · 12% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless networking
mobile ad hoc networks |
0.4 | 1 | 2019 | Routeing Properties in a Gibbsian Model for Highly Dense Multihop Networks · IEEE Trans. Inf. Theory 2019 |
Routing and switching › routing
multihop routing |
0.4 | 1 | 2019 | Routeing Properties in a Gibbsian Model for Highly Dense Multihop Networks · IEEE Trans. Inf. Theory 2019 |
Wireless networking
interference modeling |
0.1 | 1 | 2019 | Routeing Properties in a Gibbsian Model for Highly Dense Multihop Networks · IEEE Trans. Inf. Theory 2019 |
Physical-layer communications
signal-to-interference ratio |
0.1 | 1 | 2019 | Routeing Properties in a Gibbsian Model for Highly Dense Multihop Networks · IEEE Trans. Inf. Theory 2019 |
Methods — techniques the papers use, named apart from their topics
law of large numbers · 0.4gibbs distribution · 0.4asymptotic analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Routeing Properties in a Gibbsian Model for Highly Dense Multihop NetworksabstractWe investigate a probabilistic model for routeing in a multihopad hoccommunication network, where each user sends a message to the base station. Messages travel in hops via other users, used as relays. Their trajectories are chosen at random according to a Gibbs distribution, which favors trajectories with low interference, measured in terms of signal-to-interference ratio. This model was introduced in our earlier paper, where we expressed, in the limit of a high density of users, the typical distribution of the family of trajectories in terms of a law of large numbers. In this paper, we derive its qualitative properties. We analytically identify the emerging typical scenarios in three extreme regimes. We analyze the typical number of hops and the typical length of a hop and the deviation of the trajectory from the straight line, regime 1 in the limit of a large communication area and large distances and regime 2 in the limit of a strong interference weight. In both the regimes, the typical trajectory approaches a straight line quickly, in regime 1 with equal hop lengths. Interestingly, in regime 2, the typical length of a hop diverges logarithmically in the distance of the transmitter to the base station. We further analyze (regime 3) local and global repulsive effects of a densely populated subarea on the trajectories. Wolfgang König, András Tóbiás |
IEEE Trans. Inf. Theory | 2 |