Demo Data from EDBT 2026 / reviewers in the wild / expert
Matteo Ravalli
dblp:394/2440
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0007-9888-4893ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
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 |
Network management and operations · 44% Internet architecture and protocols · 44% Network measurement and analytics · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet architecture and protocols
deterministic networking |
0.8 | 1 | 2024 | Artificial Intelligence Control Plane for Deterministic Networks Proof-of-Concept · MobiCom 2024 |
Network management and operations
intent-based networking |
0.8 | 1 | 2024 | Artificial Intelligence Control Plane for Deterministic Networks Proof-of-Concept · MobiCom 2024 |
Methods — techniques the papers use, named apart from their topics
digital twin · 0.8artificial intelligence · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Artificial Intelligence Control Plane for Deterministic Networks Proof-of-ConceptabstractThis paper presents the design and implementation of an Artificial Intelligence Control Plane (AICP) for deterministic networks, emphasizing the Proof-of-Concept (PoC) demonstration. The AICP framework integrates AI, digital twin technology, and real-time telemetry to manage complex network environments, ensuring reliable and low-latency communication. The PoC showcases the practical viability of the AICP by dynamically adapting to varying network demands and maintaining stringent to the Key Performance Indicator (KPI)s of the service. Extensive testing and real-world simulations highlight the framework's potential to enhance the efficiency and resilience of industrial communication networks. Alejandro Calvillo-Fernandez, Matteo Ravalli, Juan Brenes Baranzano, Pietro G. Giardina, Jose Luis Carcel, David Rico-Menendez, Fernando Agraz, Salvatore Spadaro, Luis Velasco 0001 |
MobiCom | 2 |