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Yue Wang 0072

dblp:33/4822-72 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › energy efficiency
energy-efficient scheduling
0.812024
Battery-Aware Energy Optimization for Satellite Edge Computing · IEEE Trans. Serv. Comput. 2024
Edge and fog computing
satellite edge computing
0.812024
Battery-Aware Energy Optimization for Satellite Edge Computing · IEEE Trans. Serv. Comput. 2024
Energy-efficient computing › battery-aware computing
battery-aware power management
0.812024
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
YearPublicationVenuePosition
2024 Battery-Aware Energy Optimization for Satellite Edge Computing
abstract
Satellite 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