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

• Published in: EURASIP journal on wireless communications and networking 2022-01, Vol.2022 (1), p.1-27, Article 5
• Main Authors: Nartey, Clement, Tchao, Eric Tutu, Gadze, James Dzisi, Yeboah-Akowuah, Bright, Nunoo-Mensah, Henry, Welte, Dominik, Sikora, Axel
• Format: Article
• Language: English
• Subjects: Blockchain; Cloud computing; Cloud storage; Communications Engineering; Computer architecture; Cryptography; Engineering; Evolutionary algorithms; Information Systems Applications (incl.Internet); Internet of Things; Multiple objective analysis; Mutation; Networks; Optimization algorithms; Particle swarm optimization; Scalability; Signal,Image and Speech Processing; Sorting algorithms; Storage
• ISSN: 1687-1499; 1687-1472; 1687-1499
• DOI: 10.1186/s13638-021-02074-3

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.