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Dynamic application...
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Lakhan, AbdullahKristiania University College
(author)
Dynamic application partitioning and task-scheduling secure schemes for biosensor healthcare workload in mobile edge cloud
- Article/chapterEnglish2021
Publisher, publication year, extent ...
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2021-11-15
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MDPI AG,2021
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29
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electronicrdacarrier
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LIBRIS-ID:oai:researchportal.hkr.se/admin:publications/a40524b6-650b-431f-b906-242cd8c36bfc
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oai:researchportal.hkr.se/admin:publications/a40524b6-650b-431f-b906-242cd8c36bfcURI
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https://doi.org/10.3390/electronics10222797DOI
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
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Funding Information: Funding: This work is financially supported by the Research grant of PIFI 2020 (2020VBC0002), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (SIAT,CAS), Shenzhen, China. Also, this work is partially supported by Chiang Mai University and the college of arts, media and technology. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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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 nodesin 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.
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Li, JinBeijing Jiaotong University
(author)
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Groenli, Tor MortenKristiania University College
(author)
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Hassan Sodhro, AliDepartment of Computer Science,Research environment of Computer science,Faculty of Natural Science,Avdelningen för datavetenskap,Fakulteten för naturvetenskap,Chinese Academy of Sciences(Swepub:hkr)www.hkr.se/en/s2312
(author)
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Zardari, Nawaz AliUniversiti Teknologi Malaysia
(author)
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Imran, Ali ShariqNorwegian University of Science and Technology
(author)
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Thinnukool, OrawitChiang Mai University
(author)
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Khuwuthyakorn, PattarapornChiang Mai University
(author)
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Kristiania University CollegeBeijing Jiaotong University
(creator_code:org_t)
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In:Electronics: MDPI AG10:22, s. 1-302079-9292
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