Study QoS-aware Fog Computing for Disease Diagnosis and Prognosis

被引:7
|
作者
Peng, Dandan [1 ]
Sun, Le [1 ]
Zhou, Rui [2 ]
Wang, YiLin [1 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210044, Peoples R China
[2] Swinburne Univ Technol, Dept Comp Sci & Software Engn, Swinburne, Vic, Australia
来源
MOBILE NETWORKS & APPLICATIONS | 2023年 / 28卷 / 02期
基金
澳大利亚研究理事会; 中国国家自然科学基金;
关键词
Internet of Things; Disease diagnosis and prognosis; EHealth; Fog computing; CLOUD; HEALTH; TECHNOLOGIES; ARCHITECTURE; FRAMEWORK;
D O I
10.1007/s11036-022-01957-z
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The development of medical sensors and the Internet of Things (IoT) offers many opportunities for research on disease diagnosis and prognosis in the electronic healthcare (eHealth) industry. IoT medical applications use wearable medical sensor devices that can be connected to the Internet for remote monitoring. However, cloud computing technology cannot meet the real-time and low-latency requirements of IoT applications in eHealth. As an intermediate layer between things and clouds, fog computing has features such as enhanced low latency, mobility, network bandwidth, security and privacy. Therefore, fog computing is very useful for the diagnosis and prognosis of diseases in the eHealth industry. In this paper, we undertake a comprehensive survey on fog computing used in eHealth. We summarize the main challenges in the eHealth industry and analyze the corresponding solutions proposed by the existing works.
引用
收藏
页码:452 / 459
页数:8
相关论文
共 50 条
  • [21] QoS-Aware Fog Service Orchestration for Industrial Internet of Things
    Tsai, Jen-Sheng
    Chuang, I-Hsun
    Liu, Jie-Jyun
    Kuo, Yau-Hwang
    Liao, Wanjiun
    [J]. IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 15 (03) : 1265 - 1279
  • [22] μ-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning Technique for Service Offloading in Fog Computing Environments
    Goudarzi, Mohammad
    Rodriguez, Maria A.
    Sarvi, Majid
    Buyya, Rajkumar
    [J]. IEEE Transactions on Services Computing, 2024, 17 (01): : 47 - 59
  • [23] Multi-objective QoS-aware optimization for deployment of IoT applications on cloud and fog computing infrastructure
    Hosseini Shirvani, Mirsaeid
    Ramzanpoor, Yaser
    [J]. NEURAL COMPUTING & APPLICATIONS, 2023, 35 (26): : 19581 - 19626
  • [24] Multi-objective QoS-aware optimization for deployment of IoT applications on cloud and fog computing infrastructure
    Mirsaeid Hosseini Shirvani
    Yaser Ramzanpoor
    [J]. Neural Computing and Applications, 2023, 35 : 19581 - 19626
  • [25] QoS-Aware Cloud Resource Prediction for Computing Services
    Osypanka, Patryk
    Nawrocki, Piotr
    [J]. IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 16 (02) : 1346 - 1357
  • [26] QoS-aware scheduling of Workflows in Cloud Computing environments
    Bousselmi, Khadija
    Brahmi, Zaki
    Gammoudi, Mohamed Mohsen
    [J]. IEEE 30TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS IEEE AINA 2016, 2016, : 737 - 745
  • [27] FOGPLAN: A Lightweight QoS-Aware Dynamic Fog Service Provisioning Framework
    Yousefpour, Ashkan
    Patil, Ashish
    Ishigaki, Genya
    Kim, Inwoong
    Wang, Xi
    Cankaya, Hakki C.
    Zhang, Qiong
    Xie, Weisheng
    Jue, Jason P.
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (03) : 5080 - 5096
  • [28] A QoS-Aware IoT Service Placement Mechanism in Fog Computing Based on Open-Source Development Model
    Defu Zhao
    Qunying Zou
    Milad Boshkani Zadeh
    [J]. Journal of Grid Computing, 2022, 20
  • [29] A QoS-Aware IoT Service Placement Mechanism in Fog Computing Based on Open-Source Development Model
    Zhao, Defu
    Zou, Qunying
    Zadeh, Milad Boshkani
    [J]. JOURNAL OF GRID COMPUTING, 2022, 20 (02)
  • [30] QoS-aware service composition in Fog-IoT computing using multi-population genetic algorithm
    Aoudia, Idir
    Kahloul, Laid
    Benharzallah, Saber
    Kazar, Okba
    [J]. 2020 21ST INTERNATIONAL ARAB CONFERENCE ON INFORMATION TECHNOLOGY (ACIT), 2020,