EDBT 2026 Demo / reviewers in the wild / expert
Eduardo C. Paim
dblp:282/8615
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0003-3116-6484ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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 measurement and analytics · 67% Internet of things and sensor networks · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks
crowdsensing |
0.9 | 1 | 2025 | Hidden Impact of Hardware Technologies on Throughput: a Case Study on a Brazilian Mobile Web Network · WWW 2025 |
Network measurement and analytics
mobile network measurement |
0.9 | 1 | 2025 | Hidden Impact of Hardware Technologies on Throughput: a Case Study on a Brazilian Mobile Web Network · WWW 2025 |
Network measurement and analytics › web performance measurement
mobile web performance |
0.9 | 1 | 2025 | Hidden Impact of Hardware Technologies on Throughput: a Case Study on a Brazilian Mobile Web Network · WWW 2025 |
Methods — techniques the papers use, named apart from their topics
measurement session analysis · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Hidden Impact of Hardware Technologies on Throughput: a Case Study on a Brazilian Mobile Web NetworkabstractThe Web has shifted towards a mobile-first ecosystem with tools, frameworks, and forums explicitly discussing and catering for the mobile users, both mobile apps and mobile web-pages. Unfortunately, much of the studies and designs are often based on analysis and findings from developed regions (e.g., N. America and Europe) or based on user-generated data (introducing bias). In this paper, we present one of the first studies to understand the interplay between hardware characteristics (e.g., cellular and mobile) on expected network and application level performance in Brazil (the largest developing region in S. America). We analyze more than 170 million measurement sessions collected from within the network of one of the largest Mobile Network Operators in Brazil. Our findings (1) illustrate limitations of existing crowdsourced measurements and inaccuracies in assumptions about adoption patterns and performance in the global south, (2) highlight the differences between recommendations made by standardization bodies and real world performance, (3) disclose a significant change pre- and post-pandemic, and (4) quantify the benefits of using both client side and network data for analysis. Eduardo C. Paim, Roberto Irajá Tavares da Costa Filho, Valter Roesler, Theophilus Benson, Alberto E. Schaeffer Filho |
WWW | 1 |