Demo Data from VLDB 2026 / reviewers in the wild / expert
Jaeseong Lee 0004
dblp:141/9456-4
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
0009-0006-1746-425XORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author
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 |
Embedded and real-time systems · 44% Performance modeling and evaluation · 44% Energy-efficient computing · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Embedded and real-time systems
mobile computing |
0.2 | 1 | 2015 | Evaluating battery aging on mobile devices · DAC 2015 |
Performance modeling and evaluation
online estimation |
0.2 | 1 | 2015 | Evaluating battery aging on mobile devices · DAC 2015 |
Energy-efficient computing
battery management |
0.1 | 1 | 2015 | Evaluating battery aging on mobile devices · DAC 2015 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Evaluating battery aging on mobile devicesabstractBattery-related problems in mobile devices have been extensively investigated in both industry and literature. In particular, battery aging is a critical issue, since battery lifetime decreases as usage time increases. Battery aging primarily causes inconvenience to users by necessitating frequent recharging, and also affects the accuracy of power estimations for mobile devices. Evaluating battery aging and its effects has rarely been addressed in prior works. In this paper, we propose an online scheme to quantify the battery aging of mobile devices. Specifically, we estimate the degree of battery aging as a ratio metric based on patterns of charging time. For example, an estimate of 50% indicates that the battery capacity is only half of full capacity, meaning that the battery usage time is only approximately half that of the new battery's. Our scheme works autonomously on mobile devices and does not require any external equipment. The extensive experiments demonstrated that the proposed scheme quantifies battery aging accurately. Jaeseong Lee 0004, Yohan Chon, Hojung Cha |
DAC | 1 |