An SDN-enabled fog computing framework for wban applications in the healthcare sector

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10254922" target="_blank" >RIV/61989100:27240/24:10254922 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S254266052400088X?via%3Dihub#sec0011" target="_blank" >https://www.sciencedirect.com/science/article/pii/S254266052400088X?via%3Dihub#sec0011</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.iot.2024.101150" target="_blank" >10.1016/j.iot.2024.101150</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An SDN-enabled fog computing framework for wban applications in the healthcare sector

Popis výsledku v původním jazyce

For healthcare systems utilizing Wireless Body Area Networks (WBANs), maintaining the network&apos;s diverse Quality of Service (QoS) metrics necessitates effective communication among Fog Computing resources. While fog nodes efficiently handle local requests with substantial processing resources, it is crucial to acknowledge the unpredictable availability of these nodes, potentially resulting in a decline in system performance. This study explores a software-defined fog architecture supporting different healthcare applications in Internet of Things (IoT) environment to ensure consistent specialized medical care amidst evolving health issues. Even minor delays, packet losses, or network overhead could adversely affect patient health. The article establishes a mathematical foundation based on transmitted and sensed data, ensuring each fog node executes an ideal quantity of processes. This study formulates an optimization problem to maximize the utility of fog nodes, leveraging the Lagrangian approach and Karush-Kuhn-Tucker conditions to streamline and resolve the optimization problem. Performance analysis demonstrates a significant reduction in delays by approximately 38 %, 29 %, and 32 %, along with energy savings of roughly 26.89 %, 12.16 %, and 22.50 %, compared to benchmark approaches. This study holds promise in healthcare, cloud-fog simulation, and WBANs, emphasizing the critical need for swift and accurate data processing. (C) 2024 Elsevier B.V.

Název v anglickém jazyce

An SDN-enabled fog computing framework for wban applications in the healthcare sector

Popis výsledku anglicky

For healthcare systems utilizing Wireless Body Area Networks (WBANs), maintaining the network&apos;s diverse Quality of Service (QoS) metrics necessitates effective communication among Fog Computing resources. While fog nodes efficiently handle local requests with substantial processing resources, it is crucial to acknowledge the unpredictable availability of these nodes, potentially resulting in a decline in system performance. This study explores a software-defined fog architecture supporting different healthcare applications in Internet of Things (IoT) environment to ensure consistent specialized medical care amidst evolving health issues. Even minor delays, packet losses, or network overhead could adversely affect patient health. The article establishes a mathematical foundation based on transmitted and sensed data, ensuring each fog node executes an ideal quantity of processes. This study formulates an optimization problem to maximize the utility of fog nodes, leveraging the Lagrangian approach and Karush-Kuhn-Tucker conditions to streamline and resolve the optimization problem. Performance analysis demonstrates a significant reduction in delays by approximately 38 %, 29 %, and 32 %, along with energy savings of roughly 26.89 %, 12.16 %, and 22.50 %, compared to benchmark approaches. This study holds promise in healthcare, cloud-fog simulation, and WBANs, emphasizing the critical need for swift and accurate data processing. (C) 2024 Elsevier B.V.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Internet of Things

ISSN

2543-1536

e-ISSN

2542-6605

Svazek periodika

26

Číslo periodika v rámci svazku

101150

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

15

Strana od-do

—

Kód UT WoS článku

001224457800001

EID výsledku v databázi Scopus

2-s2.0-85187383792