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12.04.2022

Study QoS-aware Fog Computing for Disease Diagnosis and Prognosis

verfasst von: Dandan Peng, Le Sun, Rui Zhou, YiLin Wang

Erschienen in: Mobile Networks and Applications | Ausgabe 2/2023

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Abstract

Der Artikel geht auf die entscheidende Rolle der QoS-bewussten Nebelberechnung bei der Krankheitsdiagnose und -prognose innerhalb der eHealth-Branche ein. Zunächst wird die Bedeutung eines effektiven Krankheitsmanagements durch elektronische Gesundheitstechnologien skizziert, angetrieben durch Fortschritte bei medizinischen Sensoren und IoT. Das Papier benennt dann fünf große Herausforderungen, vor denen eHealth steht: Sicherheit und Datenschutz, Energieeffizienz, Latenz, Netzwerkbandbreite und Zuverlässigkeit. Darin wird untersucht, wie Nebel Computing, eine Erweiterung des Cloud Computing bis zum Netzwerkrand, diese Herausforderungen wirksamer bewältigt als herkömmliche Cloud-Lösungen. Der Artikel untersucht bestehende Ansätze im Bereich Nebelcomputing und kategorisiert sie in Lösungen für Sicherheit und Privatsphäre, Energieeffizienz, Latenzreduzierung und andere Probleme. Es werden innovative Methoden wie Verschlüsselung, Zugangskontrolle, Authentifizierung, energiebewusste Zuweisung und Aufgabenzuweisung vorgestellt und gezeigt, wie diese Techniken Sicherheit, Effizienz und Zuverlässigkeit in eHealth-Anwendungen verbessern. Die Schlussfolgerung betont die Grenzen des Cloud Computing im Bereich eHealth und befürwortet eine weitere Erforschung des Edge Computing in diesem Bereich. Dieser Artikel bietet ein überzeugendes Argument für die Überlegenheit von Nebelcomputern bei der Bewältigung der vielfältigen Herausforderungen der elektronischen Gesundheitsfürsorge und macht ihn zu einem Pflichtlektüre für Fachleute, die Gesundheitstechnologien optimieren wollen.

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Metadaten
Titel
Study QoS-aware Fog Computing for Disease Diagnosis and Prognosis
verfasst von
Dandan Peng
Le Sun
Rui Zhou
YiLin Wang
Publikationsdatum
12.04.2022
Verlag
Springer US
Erschienen in
Mobile Networks and Applications / Ausgabe 2/2023
Print ISSN: 1383-469X
Elektronische ISSN: 1572-8153
DOI
https://doi.org/10.1007/s11036-022-01957-z