Decentralized AI-Based Task Distribution on Blockchain for Cloud Industrial Internet of Things

【Author】 Javadpour, Amir; Sangaiah, Arun Kumar; Zhang, Weizhe; Vidyarthi, Ankit; Ahmadi, Hamidreza

【Source】JOURNAL OF GRID COMPUTING

【影响因子】4.674

【Abstract】This study presents an environmentally friendly mechanism for task distribution designed explicitly for blockchain Proof of Authority (POA) consensus. This approach facilitates the selection of virtual machines for tasks such as data processing, transaction verification, and adding new blocks to the blockchain. Given the current lack of effective methods for integrating POA blockchain into the Cloud Industrial Internet of Things (CIIoT) due to their inefficiency and low throughput, we propose a novel algorithm that employs the Dynamic Voltage and Frequency Scaling (DVFS) technique, replacing the periodic transaction authentication process among validator candidates. Managing computer power consumption becomes a critical concern, especially within the Internet of Things ecosystem, where device power is constrained, and transaction scalability is crucial. Virtual machines must validate transactions (tasks) within specific time frames and deadlines. The DVFS technique efficiently reduces power consumption by intelligently scheduling and allocating tasks to virtual machines. Furthermore, we leverage artificial intelligence and neural networks to match tasks with suitable virtual machines. The simulation results demonstrate that our proposed approach harnesses migration and DVFS strategies to optimize virtual machine utilization, resulting in decreased energy and power consumption compared to non-DVFS methods. This achievement marks a significant stride towards seamlessly integrating blockchain and IoT, establishing an ecologically sustainable network. Our approach boasts additional benefits, including decentralization, enhanced data quality, and heightened security. We analyze simulation runtime and energy consumption in a comprehensive evaluation against existing techniques such as WPEG, IRMBBC, and BEMEC. The findings underscore the efficiency of our technique (LBDVFSb) across both criteria.

【Keywords】Blockchain; Improving resources; Internet of Things; Decentralized; DVFS; Industrial Internet of Things

【发表时间】2024 MAR

【收录时间】2024-03-04

【文献类型】实验仿真

【主题类别】

区块链应用-实体经济-工业互联网