VLDB 2026 Research / reviewers in the wild / expert
Zhaolin Xi
dblp:397/2188
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0001-4768-0993ORCID · reported
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 · 62% Internet of things and sensor networks · 38% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › telemedicine
remote patient monitoring |
0.3 | 1 | 2025 | Telemedicine Monitoring System Based on Fog/Edge Computing: A Survey · IEEE Trans. Serv. Comput. 2025 |
Medical and health informatics
telemedicine |
0.3 | 1 | 2025 | Telemedicine Monitoring System Based on Fog/Edge Computing: A Survey · IEEE Trans. Serv. Comput. 2025 |
Internet of things and sensor networks › wireless body area network
health monitoring |
0.3 | 1 | 2025 | Telemedicine Monitoring System Based on Fog/Edge Computing: A Survey · IEEE Trans. Serv. Comput. 2025 |
Internet of things and sensor networks › iot applications
internet of medical things |
0.3 | 1 | 2025 | Telemedicine Monitoring System Based on Fog/Edge Computing: A Survey · IEEE Trans. Serv. Comput. 2025 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Telemedicine Monitoring System Based on Fog/Edge Computing: A SurveyabstractTelemedicine Monitoring (TM) integrates mobile communication technology and Internet of Things (IoT) technology for health monitoring and data management. Amidst the escalating demand for telemedicine, traditional cloud computing struggles to guarantee real-time performance and data privacy. To address these challenges, we systematically survey the application of fog and edge computing technologies in TM systems. We focus on the following key aspects: (1) We delve into the theoretical foundations of fog and edge computing, underscoring their salient advantages including low latency, location awareness, high mobility, and more. (2) We elaborate on the architecture of a TM system hinged on fog and edge computing. (3) We outline key challenges facing fog/edge computing-based TM systems, including bandwidth limitations, low latency, data security, privacy, heterogeneity, and reliability. (4) We discuss the need for future advancements in the realms of security defense capability, system adaptability, and convergence of scheduling algorithms to refine the construction of the TM system and stimulate the development of telemedicine. Qiang He 0002, Zhaolin Xi, Zheng Feng, Yueyang Teng, Lianbo Ma 0004, Yuliang Cai, Keping Yu |
IEEE Trans. Serv. Comput. | 2 |