Demo Data from EDBT 2026 / reviewers in the wild / expert
Gregory Moore
dblp:33/4777
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 77% Parallel and multicore computing · 12% Embedded and real-time systems · 12% | |
| Computer networks
1 paper |
Internet of things and sensor networks · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › wireless sensor network
sensor network simulation |
0.1 | 1 | 2007 | Disens: scalable distributed sensor network simulation · PPoPP 2007 |
Performance modeling and evaluation › simulation › parallel and distributed simulation
distributed simulation |
0.1 | 1 | 2007 | Disens: scalable distributed sensor network simulation · PPoPP 2007 |
Performance modeling and evaluation
simulation |
0.1 | 1 | 2007 | Disens: scalable distributed sensor network simulation · PPoPP 2007 |
Parallel and multicore computing › parallel architecture
distributed-memory parallel computing |
0.0 | 1 | 2007 | Disens: scalable distributed sensor network simulation · PPoPP 2007 |
Embedded and real-time systems
synchronization protocols |
0.0 | 1 | 2007 | Disens: scalable distributed sensor network simulation · PPoPP 2007 |
Methods — techniques the papers use, named apart from their topics
node partitioning · 0.1discrete-event simulation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Disens: scalable distributed sensor network simulationabstractSimulation is widely used for developing, evaluating and analyzing sensor network applications, especially when deploying a large scale sensor network remains expensive and labor intensive. However, due to its computation intensive nature, existent simulation tools have to make trade-offs between fidelity and scalability and thus offer limited capabilities as design and analysis tools. In this paper, we introduce DiSenS (DIstributed SENsor network Simulation) -- a highly scalable distributed simulation system for sensor networks. DiSenS does not only faithfully emulates an extensive set of sensor hardware and supports extensible radio/power models, so that sensor network applications can be simulated transparently with high fidelity, but also employs distributed-memory parallel cluster system to attack the complex simulation problem. Combining an efficient distributed synchronization protocol and a sophisticated node partitioning algorithm (based on existent research), DiSenS achieves greater scalability than even many discrete event simulators. On a small to medium size cluster (16-64 nodes), DiSenS is able to simulate hundreds of motes in realtime speed and scale to thousands in sub-realtime speed. To our knowledge, DiSenS is the first full-system sensor network simulator with such scalability. Ye Wen, Richard Wolski, Gregory Moore |
PPoPP | 3 |