Demo Data from EDBT 2026 / reviewers in the wild / expert
Trolan C. L. Ma
dblp:45/7791
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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 · 50% Energy-efficient computing · 50% | |
| Software engineering, system software, and programming languages
1 paper |
Operating systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy-efficient computing
energy-aware scheduling |
0.0 | 1 | 2000 | A User-Customizable Energy-Adaptive Combined Static/Dynamic Scheduler for Mobile Applications · RTSS 2000 |
Embedded and real-time systems
real-time scheduling |
0.0 | 1 | 2000 | A User-Customizable Energy-Adaptive Combined Static/Dynamic Scheduler for Mobile Applications · RTSS 2000 |
Operating systems › resource management › process management › CPU scheduling
scheduler design |
0.0 | 1 | 2000 | A User-Customizable Energy-Adaptive Combined Static/Dynamic Scheduler for Mobile Applications · RTSS 2000 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | A User-Customizable Energy-Adaptive Combined Static/Dynamic Scheduler for Mobile ApplicationsabstractIn mobile applications, the energy consumed by operating system (OS) and application tasks primarily comes from a limited DC battery source, which imposes an upper bound to the amount of time available for execution of tasks. To achieve the best energy-aware quality of service (EQoS), it is important to prioritize the scheduling of critical tasks over non-critical tasks to improve overall performance while extending the battery life. Using the CSD (Combined Static/Dynamic) scheduler in the EMERALDS operating system as a basis, we developed EA-CSD (Energy-Adaptive CSD) with an energy-aware scheduling algorithm that executes tasks to achieve the effective use of limited energy by favoring low-energy and critical tasks. Our simulation of the EA-CSD shows that battery life can be extended up to about 100% with varying degrees of performance degradation of up to about 40%, and the actual values of both are fully customizable by the user through parametric adjustment. Trolan C. L. Ma, Kang G. Shin |
RTSS | 1 |