research-article

Cloud-Fog Interoperability in IoT-enabled Healthcare Solutions

Authors:

Redowan Mahmud,

Fernando Luiz Koch,

Rajkumar BuyyaAuthors Info & Claims

ICDCN '18: Proceedings of the 19th International Conference on Distributed Computing and Networking

Article No.: 32, Pages 1 - 10

https://doi.org/10.1145/3154273.3154347

Published: 04 January 2018 Publication History

Abstract

The issue of utilizing Internet of Things (IoT) in Healthcare solutions relates to the problems of latency sensitivity, uneven data load, diverse user expectations and heterogeneity of the applications. Current explorations consider Cloud Computing as the base stone to create IoT-Enable solution. Nonetheless, this environment entails limitations in terms of multi-hop distance from the data source, geographical centralized architecture, economical aspects, etc. To address these limitations, there is a surge of solutions that apply Fog Computing as an approach to bring computing resources closer to the data sources. This approach is being fomented by the growing availability of powerful edge computing at lower cost and commercial developments in the area. Nonetheless, the implementation of Cloud-Fog interoperability and integration implies in complex coordination of applications and services and the demand for intelligent service orchestrations so that solutions can make the best use of distributed resources without compromising stability, quality of services, and security. In this paper, we introduce a Fog-based IoT-Healthcare solution structure and explore the integration of Cloud-Fog services in interoperable Healthcare solutions extended upon the traditional Cloud-based structure. The scenarios are evaluated through simulations using the iFogSim simulator and the results analyzed in relation to distributed computing, reduction of latency, optimization of data communication, and power consumption. The experimental results point towards improvement in instance cost, network delay and energy usage.

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Cited By

Du HLiu MLiu NLi DLi WXu L(2025)Scheduling of Low-Latency Medical Services in Healthcare Cloud with Deep Reinforcement LearningTsinghua Science and Technology10.26599/TST.2024.901003330:1(100-111)Online publication date: Feb-2025
https://doi.org/10.26599/TST.2024.9010033
Goel GChaturvedi A(2024)Multi-Objective Load-balancing Strategy for Fog-driven Patient-Centric Smart Healthcare System in a Smart CityEngineering, Technology & Applied Science Research10.48084/etasr.774914:4(16011-16019)Online publication date: 2-Aug-2024
https://doi.org/10.48084/etasr.7749
Nawaz AIqbal WAltaf AAlmjally AAlSagri HAlabdullah B(2024) CATcAFSMs : Context‐based adaptive trust calculation for attack detection in fog computing based smart medical systems Expert Systems10.1111/exsy.13687Online publication date: 15-Aug-2024
https://doi.org/10.1111/exsy.13687
Show More Cited By

Index Terms

Cloud-Fog Interoperability in IoT-enabled Healthcare Solutions
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
2. Networks
  1. Network properties
    1. Network reliability

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ICDCN '18: Proceedings of the 19th International Conference on Distributed Computing and Networking

January 2018

494 pages

ISBN:9781450363723

DOI:10.1145/3154273

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 04 January 2018

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ICDCN '18: 19th International Conference on Distributed Computing and Networking

January 4 - 7, 2018

Varanasi, India

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Cited By

Du HLiu MLiu NLi DLi WXu L(2025)Scheduling of Low-Latency Medical Services in Healthcare Cloud with Deep Reinforcement LearningTsinghua Science and Technology10.26599/TST.2024.901003330:1(100-111)Online publication date: Feb-2025
https://doi.org/10.26599/TST.2024.9010033
Goel GChaturvedi A(2024)Multi-Objective Load-balancing Strategy for Fog-driven Patient-Centric Smart Healthcare System in a Smart CityEngineering, Technology & Applied Science Research10.48084/etasr.774914:4(16011-16019)Online publication date: 2-Aug-2024
https://doi.org/10.48084/etasr.7749
Nawaz AIqbal WAltaf AAlmjally AAlSagri HAlabdullah B(2024) CATcAFSMs : Context‐based adaptive trust calculation for attack detection in fog computing based smart medical systems Expert Systems10.1111/exsy.13687Online publication date: 15-Aug-2024
https://doi.org/10.1111/exsy.13687
Bebortta SSekhar Tripathy STripathy N(2024)PriorHealth: A Priority-Aware Task Scheduling Framework for Managing Healthcare Data in Fog Computing Applications2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)10.1109/IDCIoT59759.2024.10467807(586-591)Online publication date: 4-Jan-2024
https://doi.org/10.1109/IDCIoT59759.2024.10467807
Khan MGupta DSaini S(2024)Cloud Collaboration Using Fog Computing2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO61523.2024.10522356(1-5)Online publication date: 14-Mar-2024
https://doi.org/10.1109/ICRITO61523.2024.10522356
Rao Polamuri SNalla LMadhuri AKalagara SSubrahmanyam BAparna P(2024)Analyse The Energy Consumption by Integrating the IOT and Pattern Recognition Technique2024 2nd International Conference on Disruptive Technologies (ICDT)10.1109/ICDT61202.2024.10489265(607-610)Online publication date: 15-Mar-2024
https://doi.org/10.1109/ICDT61202.2024.10489265
Walia GKumar MGill S(2024)AI-Empowered Fog/Edge Resource Management for IoT Applications: A Comprehensive Review, Research Challenges, and Future PerspectivesIEEE Communications Surveys & Tutorials10.1109/COMST.2023.333801526:1(619-669)Online publication date: Sep-2025
https://doi.org/10.1109/COMST.2023.3338015
Louta MBanti KKarampelia I(2024)Emerging Technologies for Sustainable Agriculture: The Power of Humans and the Way AheadIEEE Access10.1109/ACCESS.2024.342840112(98492-98529)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3428401
Khater HSallabi FSerhani MBarka EShuaib KTariq AKhayat M(2024)Empowering Healthcare With Cyber-Physical System—A Systematic Literature ReviewIEEE Access10.1109/ACCESS.2024.340737612(83952-83993)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3407376
Usman MRehman AMasood SKhan TQadir J(2024)Intelligent healthcare system for IoMT-integrated sonography: Leveraging multi-scale self-guided attention networks and dynamic self-distillationInternet of Things10.1016/j.iot.2024.10106525(101065)Online publication date: Apr-2024
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