Data Freshness in Information-update Systems: Modeling, Scheduling, and Tradeoffs

Brief Biography: Zhongdong Liu is a final-year Ph.D. student in the Department of Computer Science at Virginia Tech. He received his B.S. degree in Mathematics and Applied Mathematics with honors from Northeast Forestry University in 2016. His research interests are in the modeling, analysis, contro...

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Veröffentlicht in:	Performance evaluation review 2024-01, Vol.51 (3), p.46-49
1. Verfasser:	Liu, Zhongdong
Format:	Artikel
Sprache:	eng
Schlagworte:	General and reference Networks Theory of computation Theory of computation / Design and analysis of algorithms Theory of computation / Design and analysis of algorithms / Approximation algorithms analysis Theory of computation / Design and analysis of algorithms / Approximation algorithms analysis / Scheduling algorithms Theory of computation / Design and analysis of algorithms / Online algorithms Theory of computation / Design and analysis of algorithms / Online algorithms / Online learning algorithms Theory of computation / Design and analysis of algorithms / Online algorithms / Online learning algorithms / Scheduling algorithms Theory of computation / Theory and algorithms for application domains Theory of computation / Theory and algorithms for application domains / Machine learning theory Theory of computation / Theory and algorithms for application domains / Machine learning theory / Reinforcement learning Theory of computation / Theory and algorithms for application domains / Machine learning theory / Reinforcement learning / Sequential decision making
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Zusammenfassung:	Brief Biography: Zhongdong Liu is a final-year Ph.D. student in the Department of Computer Science at Virginia Tech. He received his B.S. degree in Mathematics and Applied Mathematics with honors from Northeast Forestry University in 2016. His research interests are in the modeling, analysis, control, and optimization of complex network systems. His specific area of focus lies in analyzing and improving data freshness within real-time applications and services through the development of efficient scheduling algorithms. Zhongdong's research has been featured in notable publications, including IEEE INFOCOM, Proceedings of ICCCN (as an invited paper), IEEE Internet of Things Journal, and IEEE/ACM Transactions on Networking.
ISSN:	0163-5999 1557-9484
DOI:	10.1145/3639830.3639849