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Utilization of mobile edge computing on the Internet of Medical Things: A survey
Faculty
Computer Science
Year:
2023
Type of Publication:
ZU Hosted
Pages:
473-485
Authors:
Khalied Mohamed Hosny
Staff Zu Site
Abstract In Staff Site
Journal:
ICT Express Elsevier
Volume:
9
Keywords :
Utilization , mobile edge computing , , Internet , Medical
Abstract:
Internet of Things (IoT) enables different smart environment objects to communicate without involving humans. Recently, IoT has started a new challenge within the healthcare sector called the Internet of Medical Things (IoMT). The huge amounts of data generated by IoMT entities need to be analyzed in real-time to improve the performance and quality of service of the IoMT applications. Mobile Edge Computing-enabled 5G system is shown as a successful paradigm to address such an obstacle. Numerous frameworks are introduced in literature based on this idea. This paper presents a thorough discussion of MEC-based IoMT healthcare systems.
Author Related Publications
Khalied Mohamed Hosny, "SEMANTIC REPRESENTATION OF MUSIC DATABASE USING NEW ONTOLOGY-BASED SYSTEM", Journal of Theoretical and Applied Information Technology, 2020
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Khalied Mohamed Hosny, "Building a New Semantic Social Network Using Semantic Web-Based Techniques", ِASPG, 2021
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Khalied Mohamed Hosny, "New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework", IEEE, 2022
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Khalied Mohamed Hosny, "Fast computation of accurate Zernike moments", Springer, 2008
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Khalied Mohamed Hosny, "Accurate Computation of QPCET for Color Images in Different Coordinate Systems", SPIE, 2017
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Department Related Publications
Walid Ibrahim Ibrahim Khedr, "Ad-hoc on Demand Authentication Chain Protocol - An Authentication Protocol for Ad-Hoc Networks", Institute for Systems and Technologies of Information, Control and Communication, 2015
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Khalied Mohamed Hosny, "Robust Color Image Hashing Using Quaternion Polar Complex Exponential Transform for Image Authentication", Springer, 2018
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Ehab Roshdy Mohamed, "Efficient compression of volumetric medical images using Legendre moments and differential evolution", Springer, 2020
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Asmaa Mohamed Khalid Mohamed Abbas, "Efficient compression of volumetric medical images using Legendre moments and differential evolution", Springer, 2020
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Khalied Mohamed Hosny, "Efficient compression of volumetric medical images using Legendre moments and differential evolution", Springer, 2020
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