Blockchain technology and application : an overview
- Authors: Dong, Shi , Abbas, Khushnood , Li, Meixi , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article
- Relation: PeerJ Computer Science Vol. 9, no. (2023), p.
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- Description: In recent years, with the rise of digital currency, its underlying technology, blockchain, has become increasingly well-known. This technology has several key characteristics, including decentralization, time-stamped data, consensus mechanism, traceability, programmability, security, and credibility, and block data is essentially tamper-proof. Due to these characteristics, blockchain can address the shortcomings of traditional financial institutions. As a result, this emerging technology has garnered significant attention from financial intermediaries, technology-based companies, and government agencies. This article offers an overview of the fundamentals of blockchain technology and its various applications. The introduction defines blockchain and explains its fundamental working principles, emphasizing features such as decentralization, immutability, and transparency. The article then traces the evolution of blockchain, from its inception in cryptocurrency to its development as a versatile tool with diverse potential applications. The main body of the article explores fundamentals of block chain systems, its limitations, various applications, applicability etc. Finally, the study concludes by discussing the present state of blockchain technology and its future potential, as well as the challenges that must be surmounted to unlock its full potential. © Copyright 2023 Dong et al
Quantum particle swarm optimization for task offloading in mobile edge computing
- Authors: Dong, Shi , Xia, Yuanjun , Kamruzzaman, Joarder
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 19, no. 8 (2023), p. 9113-9122
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- Description: Mobile edge computing (MEC) deploys servers on the edge of the mobile network to reduce the data transmission delay between servers and mobile devices, and can meet the computing demand of mobile computing tasks. It alleviates the problem of computing power and delay requirements of mobile computing tasks and reduces the energy consumption of mobile devices. However, the MEC server has limited computing and storage resources and mobile network bandwidth, making it impossible to offload all mobile computing tasks to MEC servers for processing. Therefore, MEC needs to reasonably offload and schedule mobile computing tasks, to achieve efficient utilization of server resources. To solve the above-mentioned problems, in this article, the task offloading problem is formulated as an optimization problem, and particle swarm optimization (PSO) and quantum PSO based task offloading strategies are proposed. Extensive simulation results show that the proposed algorithm can significantly reduce the system energy consumption, task completion time, and running time compared with recent advanced strategies, namely ant colony optimization, multiagent deep deterministic policy gradients, deep meta reinforcement learning-based offloading, iterative proximal algorithm, and parallel random forest. © 2005-2012 IEEE.