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A Proximal Algorithm for Fork-Choice in Distributed Ledger Technology for Context-Based Clustering on Edge Computing
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.ORCID iD: 0000-0001-5924-5457
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.ORCID iD: 0000-0002-1101-3793
2020 (English)In: Engineering Proceedings, E-ISSN 2673-4591, Vol. 2, no 1, article id 92Article in journal (Refereed) Published
Abstract [en]

The major challenges of operating data-intensive of Distributed Ledger Technology (DLT) are 1) To reach consensus on the main chain is a set of validators cast public votes to decide on which blocks to finalize and 2) scalability on how to increasing the number of chains which will be running in parallel. In this paper, we introduce a new proximal algorithm that scales DLT in a large scale IoT devices network. We discuss how the algorithm benefits the integrating DLT in IoT by using edge computing technology, taking the scalability and heterogeneous capability of IoT devices into consideration. IoT devices are clustered dynamically into groups based on various proximity context information. A cluster head is used to bridge the IoT devices with the DLT network where the smart contract is deployed. In this way, the security of the IoT is improved and the scalability and latency are solved. We elaborate our mechanism and discuss issues that should be considered and implemented when using the proposed algorithm even we show its behaves when varying parameters like latency or when clustering.

Place, publisher, year, edition, pages
2020. Vol. 2, no 1, article id 92
Keywords [en]
Distributed Ledger Technology, Blockchain, Internet of Things(IoT), Edge Computing, IoT Security
National Category
Computer Engineering
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-188850DOI: 10.3390/ecsa-7-08261Scopus ID: 2-s2.0-85145394734OAI: oai:DiVA.org:su-188850DiVA, id: diva2:1517274
Conference
7th Electronic Conference on Sensors and Applications, 15–30 November, 2020.
Available from: 2021-01-13 Created: 2021-01-13 Last updated: 2025-04-07Bibliographically approved

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Rahmani, RahimFirouzi, RaminAlam, Mahbub Ul

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