Demo Data from EDBT 2026 / reviewers in the wild / expert
Marco Fiscato
dblp:28/7636
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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.
| Databases, data mining, and information retrieval
1 paper |
Data stream processing · 67% Distributed and cloud data management · 33% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed and cloud data management › federated database
federated query processing |
0.2 | 1 | 2016 | THEMIS: Fairness in Federated Stream Processing under Overload · SIGMOD Conference 2016 |
Data stream processing
load shedding |
0.2 | 1 | 2016 | THEMIS: Fairness in Federated Stream Processing under Overload · SIGMOD Conference 2016 |
Cloud and datacenter computing › cloud deployment
multi-cloud deployment |
0.1 | 1 | 2016 | THEMIS: Fairness in Federated Stream Processing under Overload · SIGMOD Conference 2016 |
Methods — techniques the papers use, named apart from their topics
query fragmentation · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | THEMIS: Fairness in Federated Stream Processing under OverloadabstractFederated stream processing systems, which utilise nodes from multiple independent domains, can be found increasingly in multi-provider cloud deployments, internet-of-things systems, collaborative sensing applications and large-scale grid systems. To pool resources from several sites and take advantage of local processing, submitted queries are split into query fragments, which are executed collaboratively by different sites. When supporting many concurrent users, however, queries may exhaust available processing resources, thus requiring constant load shedding. Given that individual sites have autonomy over how they allocate query fragments on their nodes, it is an open challenge how to ensure global fairness on processing quality experienced by queries in a federated scenario. Evangelia Kalyvianaki, Marco Fiscato, Theodoros Salonidis, Peter R. Pietzuch |
SIGMOD Conference | 2 |