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The Journal of Supercomputing

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09-05-2023

Composition of caching and classification in edge computing based on quality optimization for SDN-based IoT healthcare solutions

Authors: Seyedeh Shabnam Jazaeri, Parvaneh Asghari, Sam Jabbehdari, Hamid Haj Seyyed Javadi

Published in: The Journal of Supercomputing | Issue 15/2023

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Abstract

This paper proposes a novel approach that uses a spectral clustering method to cluster patients with e-health IoT devices based on their similarity and distance and connect each cluster to an SDN edge node for efficient caching. The proposed MFO-Edge Caching algorithm is considered for selecting the near-optimal data options for caching based on considered criteria and improving QoS. Experimental results demonstrate that the proposed approach outperforms other methods in terms of performance, achieving decrease in average time between data retrieval delays and the cache hit rate of 76%. Emergency and on-demand requests are prioritized for caching response packets, while periodic requests have a lower cache hit ratio of 35%. The approach shows improvement in performance compared to other methods, highlighting the effectiveness of SDN-Edge caching and clustering for optimizing e-health network resources.

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Title: Composition of caching and classification in edge computing based on quality optimization for SDN-based IoT healthcare solutions
Authors: Seyedeh Shabnam Jazaeri
Parvaneh Asghari
Sam Jabbehdari
Hamid Haj Seyyed Javadi
Publication date: 09-05-2023
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 15/2023
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-023-05332-x

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