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BlockEdge

Authors :
Madhusanka Liyanage
Erkki Harjula
An Braeken
Tanesh Kumar
Ijaz Ahmad
Ahsan Manzoor
Muneeb Ejaz
Pawani Porambage
Mika Ylianttila
Digital Mathematics
Engineering Technology
Industrial Sciences and Technology
Source :
IEEE Access, Vol 8, Pp 154166-154185 (2020), Kumar, T, Harjula, E, Ejaz, M, Manzoor, A, Porambage, P, Ahmad, I, Liyanage, M, Braeken, A & Ylianttila, M 2020, ' BlockEdge : Blockchain-Edge Framework for Industrial IoT Networks ', IEEE Access, vol. 8, pp. 154166-154185 . https://doi.org/10.1109/ACCESS.2020.3017891
Publication Year :
2020
Publisher :
IEEE Institute of Electrical and Electronic Engineers, 2020.

Abstract

Industry 4.0 encompasses a promise of a new industrial revolution in terms of providing secure, intelligent, autonomous and self-adaptive industrial IoT (IIoT) networks. Key industrial applications and systems will be significantly more complex due to the involvement of the vast number of different devices and diverse nature of various stakeholders and service providers. These complex industrial processes, services and applications also have strict requirements in terms of performance — latency in particular — and resource-efficiency, together with high standards for security and trust. In this context, Blockchain and Edge Computing emerge as prominent technologies to address the mentioned essential requirements and to further strengthen the rise of the new era of digitization. The Edge computing paradigm ensures low latency services for IIoT applications while optimizing the network usage, whereas Blockchain provides a decentralized way for ensuring data integrity, trust and security. In this paper, we propose a “BlockEdge” framework that combines these two enabling technologies to address some of the critical issues faced by the current IIoT networks. We verify the feasibility of our approach by evaluating the performance and resource-efficiency of BlockEdge in terms of latency, power consumption and network usage, through simulations against non-Blockchain solution.

Details

Language :
English
ISSN :
21693536
Volume :
8
Database :
OpenAIRE
Journal :
IEEE Access
Accession number :
edsair.doi.dedup.....7e5d380dbce62907caff30885a4c2797