Zhaolin Xi

dblp:397/2188 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Medical and health informatics › telemedicine
remote patient monitoring
0.312025
Telemedicine Monitoring System Based on Fog/Edge Computing: A Survey · IEEE Trans. Serv. Comput. 2025
Medical and health informatics
telemedicine
0.312025
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
0.312025
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
0.312025
Telemedicine Monitoring System Based on Fog/Edge Computing: A Survey · IEEE Trans. Serv. Comput. 2025
YearPublicationVenuePosition
2025 Telemedicine Monitoring System Based on Fog/Edge Computing: A Survey
abstract
Telemedicine 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