【Author】
Sasikumar, A.; Ravi, Logesh; Kotecha, Ketan; Saini, Jatinderkumar R. R.; Varadarajan, Vijayakumar; Subramaniyaswamy, V.
【Source】COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
【Abstract】In recent years, the Internet of Things (IoT) has been industrializing in various real-world applications, including smart industry and smart grids, to make human existence more reliable. An overwhelming volume of sensing data is produced from numerous sensor devices as the Industrial IoT (IIoT) becomes more industrialized. Artificial Intelligence (AI) plays a vital part in big data analyses as a powerful analytic tool that provides flexible and reliable information insights in real-time. However, there are some difficulties in designing and developing a useful big data analysis tool using machine learning, such as a centralized approach, security, privacy, resource limitations, and a lack of sufficient training data. On the other hand, Blockchain promotes a decentralized architecture for IIoT applications. It encourages the secure data exchange and resources among the various nodes of the IoT network, removing centralized control and overcoming the industry's current challenges. Our proposed approach goal is to design and implement a consensus mechanism that incorporates Blockchain and AI to allow successful big data analysis. This work presents an improved Delegated Proof of Stake (DPoS) algorithm-based IIoT network that combines Blockchain and AI for real-time data transmission. To accelerate IIoT block generation, nodes use an improved DPoS to reach a consensus for selecting delegates and store block information in the trading node. The proposed approach is evaluated regarding energy consumption and transaction efficiency compared with the exciting consensus mechanism. The evaluation results reveal that the proposed consensus algorithm reduces energy consumption and addresses current security issues.
【标题】可持续的智能工业：人工智能驱动的工业物联网的安全和节能的共识机制
【摘要】近年来，物联网（IoT）在各种现实世界的应用中不断工业化，包括智能工业和智能电网，使人类的生存更加可靠。随着工业物联网（IIoT）越来越工业化，大量的传感数据从众多传感设备中产生。人工智能（AI）作为一种强大的分析工具，在大数据分析中起着至关重要的作用，可以实时提供灵活可靠的信息洞察力。然而，在设计和开发使用机器学习的有用的大数据分析工具方面存在一些困难，如集中式方法、安全、隐私、资源限制和缺乏足够的训练数据。另一方面，区块链提倡IIoT应用的去中心化架构。它鼓励物联网网络的各个节点之间的安全数据交换和资源，消除集中控制，克服行业当前的挑战。我们提出的方法目标是设计和实施一个融合了区块链和人工智能的共识机制，以实现成功的大数据分析。这项工作提出了一个改进的基于委托股权证明（DPoS）算法的IIoT网络，它结合了区块链和人工智能，用于实时数据传输。为了加速IIoT区块的生成，节点使用改进的DPoS来达成选择代表的共识，并在交易节点中存储区块信息。与激动人心的共识机制相比，所提出的方法在能耗和交易效率方面进行了评估。评估结果显示，拟议的共识算法减少了能源消耗，并解决了当前的安全问题。
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