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dc.contributor.authorPlageras, Andreas P.-
dc.contributor.authorPsannis, Kostas E.-
dc.date.accessioned2023-11-01T10:54:20Z-
dc.date.available2023-11-01T10:54:20Z-
dc.date.issued2022-12-
dc.identifier10.1016/j.vrih.2022.07.005en_US
dc.identifier.issn2096-5796en_US
dc.identifier.urihttps://doi.org/10.1016/j.vrih.2022.07.005en_US
dc.identifier.urihttps://ruomo.lib.uom.gr/handle/7000/1638-
dc.description.abstractAll recent technological findings can be collectively used to strengthen the industrial Internet of things (IIoT) sector. The novel technology of multi-access edge computing or mobile edge computing (MEC) and digital twins have advanced rapidly in the industry. MEC is the middle layer between mobile devices and the cloud, and it provides scalability, reliability, security, efficient control, and storage of resources. Digital twins form a communication model that enhances the entire system by improving latency, overhead, and energy consumption. Methods The main focus in this study is the biggest challenges that researchers in the field of IIoT have to overcome to obtain a more efficient communication environment in terms of technology integration, efficient energy and data delivery, storage spaces, security, and real-time control and analysis. Thus, a distributed system is established in a local network, in which several functions operate. In addition, an MEC-based framework is proposed to reduce traffic and latency by merging the processing of data generated by IIoT devices at the edge of the network. The critical parts of the proposed IIoT system are evaluated by using emulation software. Results The results show that data delivery and offloading are performed more efficiently, energy consumption and processing are improved, and security, complexity, control, and reliability are enhanced. Conclusions The proposed framework and application provide authentication and integrity to end users and IoT devices.en_US
dc.language.isoenen_US
dc.sourceVirtual Reality & Intelligent Hardwareen_US
dc.subjectFRASCATI::Natural sciences::Computer and information sciencesen_US
dc.subject.otherDigital twinsen_US
dc.subject.otherEnergy efficiencyen_US
dc.subject.otherIIoTen_US
dc.subject.otherLoad balanceen_US
dc.subject.otherMCCen_US
dc.subject.otherMECen_US
dc.subject.otherProtocolsen_US
dc.titleDigital Twins and Multi-Access Edge Computing for IIoTen_US
dc.typeArticleen_US
dc.contributor.departmentΤμήμα Εφαρμοσμένης Πληροφορικήςen_US
local.identifier.volume4en_US
local.identifier.issue6en_US
local.identifier.firstpage521en_US
local.identifier.lastpage534en_US
Εμφανίζεται στις Συλλογές: Τμήμα Εφαρμοσμένης Πληροφορικής

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