The real-time data processing framework for blockchain and edge computing
The rapid growth of IoT has increased the demand for large-scale data processing. However, traditional centralized methods struggle with real-time requirements and data security. This paper introduces VCD-TSNet, a novel real-time IoT data processing framework that combines blockchain and edge comput...
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| Published in: | Alexandria engineering journal Vol. 120; pp. 50 - 61 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.05.2025
Elsevier |
| Subjects: | |
| ISSN: | 1110-0168 |
| Online Access: | Get full text |
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| Summary: | The rapid growth of IoT has increased the demand for large-scale data processing. However, traditional centralized methods struggle with real-time requirements and data security. This paper introduces VCD-TSNet, a novel real-time IoT data processing framework that combines blockchain and edge computing. By integrating deep learning models like VGG, ConvLSTM, and DNN, VCD-TSNet effectively performs spatial feature extraction, temporal modeling, and decision-making, while using blockchain to ensure data integrity and privacy. Experimental results demonstrate that VCD-TSNet outperforms baseline models in classification accuracy, prediction precision, and real-time performance. For instance, on the BoT-IoT dataset, the classification accuracy reaches 97.5%, throughput increases to 920 TPS, and response time stays below 85 ms. This study validates the model’s effectiveness and highlights its potential in large-scale IoT environments, offering efficient, secure solutions for real-time data processing. It also provides insights for future improvements in frameworks that combine edge computing with blockchain. |
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| ISSN: | 1110-0168 |
| DOI: | 10.1016/j.aej.2025.01.092 |