Restricted Boltzmann machine Assisted Secure Serverless Edge System for Internet of Medical Things

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10251455" target="_blank" >RIV/61989100:27240/23:10251455 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85131740372&origin=resultslist&sort=plf-f" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85131740372&origin=resultslist&sort=plf-f</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/JBHI.2022.3178660" target="_blank" >10.1109/JBHI.2022.3178660</a>

Result language
angličtina
Original language name
Restricted Boltzmann machine Assisted Secure Serverless Edge System for Internet of Medical Things
Original language description
The Internet of things (IoT) is a network of technologies that support a wide variety of healthcare workflow applications to facilitate users' obtaining real-time healthcare services. Many patients and doctors' hospitals use different healthcare services to monitor their healthcare and save their records on the servers. Healthcare sensors are widely linked to the outside world for different disease classifications and questions. These applications are extraordinarily dynamic and use mobile devices to roam several locales. However, healthcare apps confront two significant challenges: data privacy and the cost of application execution services. This work presents the mobility-aware security dynamic service composition (MSDSC) algorithmic framework for workflow healthcare based on serverless, serverless, and restricted Boltzmann machine mechanisms. The study suggests the stochastic deep neural network trains probabilistic models at each phase of the process, including service composition, task sequencing, security, and scheduling. The experimental setup and findings revealed that the developed system-based methods outperform traditional methods by 25% in terms of safety and 35% in application cost. IEEE
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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