Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud

Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning i...

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Autores principales:	Abdullah Lakhan, Jin Li, Tor Morten Groenli, Ali Hassan Sodhro, Nawaz Ali Zardari, Ali Shariq Imran, Orawit Thinnukool, Pattaraporn Khuwuthyakorn
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	failure dynamic application partitioning task scheduling offloading energy consumption MD5 Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/1960a61d64714afe8fd5433fb1f1251e
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spelling	oai:doaj.org-article:1960a61d64714afe8fd5433fb1f1251e2021-11-25T17:24:44ZDynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud10.3390/electronics102227972079-9292https://doaj.org/article/1960a61d64714afe8fd5433fb1f1251e2021-11-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/22/2797https://doaj.org/toc/2079-9292Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.Abdullah LakhanJin LiTor Morten GroenliAli Hassan SodhroNawaz Ali ZardariAli Shariq ImranOrawit ThinnukoolPattaraporn KhuwuthyakornMDPI AGarticlefailuredynamic application partitioningtask schedulingoffloadingenergy consumptionMD5ElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2797, p 2797 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	failure dynamic application partitioning task scheduling offloading energy consumption MD5 Electronics TK7800-8360
spellingShingle	failure dynamic application partitioning task scheduling offloading energy consumption MD5 Electronics TK7800-8360 Abdullah Lakhan Jin Li Tor Morten Groenli Ali Hassan Sodhro Nawaz Ali Zardari Ali Shariq Imran Orawit Thinnukool Pattaraporn Khuwuthyakorn Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
description	Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.
format	article
author	Abdullah Lakhan Jin Li Tor Morten Groenli Ali Hassan Sodhro Nawaz Ali Zardari Ali Shariq Imran Orawit Thinnukool Pattaraporn Khuwuthyakorn
author_facet	Abdullah Lakhan Jin Li Tor Morten Groenli Ali Hassan Sodhro Nawaz Ali Zardari Ali Shariq Imran Orawit Thinnukool Pattaraporn Khuwuthyakorn
author_sort	Abdullah Lakhan
title	Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
title_short	Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
title_full	Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
title_fullStr	Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
title_full_unstemmed	Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud
title_sort	dynamic application partitioning and task-scheduling secure schemes for biosensor healthcare workload in mobile edge cloud
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1960a61d64714afe8fd5433fb1f1251e
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Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud

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