Demo Data from EDBT 2026 / reviewers in the wild / expert
Yue Wang 0072
dblp:33/4822-72
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0003-6204-5810ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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 |
Edge and fog computing · 50% Internet of things and sensor networks · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Energy-efficient computing · 77% Emerging computing paradigms · 23% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › energy efficiency
energy-efficient scheduling |
0.8 | 1 | 2024 | Battery-Aware Energy Optimization for Satellite Edge Computing · IEEE Trans. Serv. Comput. 2024 |
Edge and fog computing
satellite edge computing |
0.8 | 1 | 2024 | Battery-Aware Energy Optimization for Satellite Edge Computing · IEEE Trans. Serv. Comput. 2024 |
Energy-efficient computing › battery-aware computing
battery-aware power management |
0.8 | 1 | 2024 | Battery-Aware Energy Optimization for Satellite Edge Computing · IEEE Trans. Serv. Comput. 2024 |
Methods — techniques the papers use, named apart from their topics
online convex optimization · 1.5lyapunov optimization · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Battery-Aware Energy Optimization for Satellite Edge ComputingabstractSatellite edge computing can incur dramatically increased energy demand onboard, which is met by satellite batteries during eclipses. Excessive energy usage during regular operations accelerates battery wear. Therefore, it is important and timely to optimize the energy consumption onboard to extend satellite batteries life. This paper investigates battery-aware energy optimization for satellite edge computing under energy harvesting dynamics and wireless environment uncertainty. Inspired by the periodical energy harvesting and satellite-ground connection, we develop a pattern-aware online energy scheduling algorithm within an online convex optimization framework. This learning algorithm achieves theoretical guarantees of no regret and gradually zeroing constraint violations. We further exploit inter-satellites collaboration to extend the average battery life in a whole constellation where satellites have different battery capacity degradation. Trace-driven simulations show that our algorithm can significantly extend the battery life by 1.32× and effectively adapt to the energy harvesting dynamics and wireless environment uncertainty. Qing Li 0028, Shangguang Wang, Xiao Ma 0009, Ao Zhou 0001, Yue Wang 0072, Gang Huang 0001, Xuanzhe Liu |
IEEE Trans. Serv. Comput. | 5 |