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Blockchain-IoT peer device storage optimization using an advanced time-variant multi-objective particle swarm optimization algorithm

Authors
  • Nartey, Clement1, 2
  • Tchao, Eric Tutu2
  • Gadze, James Dzisi2
  • Yeboah-Akowuah, Bright2
  • Nunoo-Mensah, Henry2
  • Welte, Dominik3
  • Sikora, Axel3
  • 1 Carinthia University of Applied Sciences, Carinthia, Austria , Carinthia (Austria)
  • 2 Kwame Nkrumah University of Science and Technology, Kumasi, Ghana , Kumasi (Ghana)
  • 3 Offenburg University of Applied Sciences, Offenburg, Germany , Offenburg (Germany)
Type
Published Article
Journal
EURASIP Journal on Wireless Communications and Networking
Publisher
Springer Science and Business Media LLC
Publication Date
Jan 04, 2022
Volume
2022
Issue
1
Identifiers
DOI: 10.1186/s13638-021-02074-3
Source
Springer Nature
Keywords
Disciplines
  • Research
License
Green

Abstract

The integration of Internet of Things devices onto the Blockchain implies an increase in the transactions that occur on the Blockchain, thus increasing the storage requirements. A solution approach is to leverage cloud resources for storing blocks within the chain. The paper, therefore, proposes two solutions to this problem. The first being an improved hybrid architecture design which uses containerization to create a side chain on a fog node for the devices connected to it and an Advanced Time-variant Multi-objective Particle Swarm Optimization Algorithm (AT-MOPSO) for determining the optimal number of blocks that should be transferred to the cloud for storage. This algorithm uses time-variant weights for the velocity of the particle swarm optimization and the non-dominated sorting and mutation schemes from NSGA-III. The proposed algorithm was compared with results from the original MOPSO algorithm, the Strength Pareto Evolutionary Algorithm (SPEA-II), and the Pareto Envelope-based Selection Algorithm with region-based selection (PESA-II), and NSGA-III. The proposed AT-MOPSO showed better results than the aforementioned MOPSO algorithms in cloud storage cost and query probability optimization. Importantly, AT-MOPSO achieved 52% energy efficiency compared to NSGA-III. To show how this algorithm can be applied to a real-world Blockchain system, the BISS industrial Blockchain architecture was adapted and modified to show how the AT-MOPSO can be used with existing Blockchain systems and the benefits it provides.

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