Consensus Mechanism of IoT Based on Blockchain Technology
Applying blockchain technology to the Internet of Things (IoT) remains a huge challenge. To meet the actual needs of IoT, a lightweight and high-throughput consensus mechanism, combined with blockchain technology, is proposed in this study. Blockchain nodes use the Diffie–Hellman algorithm for key n...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/8846429 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832560124946808832 |
|---|---|
| author | Yue Wu Liangtu Song Lei Liu Jincheng Li Xuefei Li Linli Zhou |
| author_facet | Yue Wu Liangtu Song Lei Liu Jincheng Li Xuefei Li Linli Zhou |
| author_sort | Yue Wu |
| collection | DOAJ |
| description | Applying blockchain technology to the Internet of Things (IoT) remains a huge challenge. To meet the actual needs of IoT, a lightweight and high-throughput consensus mechanism, combined with blockchain technology, is proposed in this study. Blockchain nodes use the Diffie–Hellman algorithm for key negotiation. Sensors and blockchain nodes can use the shared key to generate HMAC (Hash-based Message Authentication Code) signatures for sensor-aware transactions and use the Verifiable Random Function to implement block nodes. Offline fast election, which is the node that wins the election, becomes the block node. Machine learning methods are also introduced to identify or remove outliers in the sensor data before such data are uploaded to the chain. Experimental results show that the system throughput synchronously increases as the test load increases. Moreover, when the test load is 800 tps, the system throughput reaches the maximum, close to 600 tps. When the test load exceeds 800 tps, the actual system throughput starts to drop, and approximately 90% of transactions have a delay time within 5000 ms. This method can be used in a lightweight IoT system. |
| format | Article |
| id | doaj-art-96c88b6bfc4645439694e3e58898f4a0 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-96c88b6bfc4645439694e3e58898f4a02025-02-03T01:28:18ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/88464298846429Consensus Mechanism of IoT Based on Blockchain TechnologyYue Wu0Liangtu Song1Lei Liu2Jincheng Li3Xuefei Li4Linli Zhou5Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, ChinaInstitute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, ChinaInstitute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, ChinaInstitute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, ChinaInstitute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, ChinaInstitute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, ChinaApplying blockchain technology to the Internet of Things (IoT) remains a huge challenge. To meet the actual needs of IoT, a lightweight and high-throughput consensus mechanism, combined with blockchain technology, is proposed in this study. Blockchain nodes use the Diffie–Hellman algorithm for key negotiation. Sensors and blockchain nodes can use the shared key to generate HMAC (Hash-based Message Authentication Code) signatures for sensor-aware transactions and use the Verifiable Random Function to implement block nodes. Offline fast election, which is the node that wins the election, becomes the block node. Machine learning methods are also introduced to identify or remove outliers in the sensor data before such data are uploaded to the chain. Experimental results show that the system throughput synchronously increases as the test load increases. Moreover, when the test load is 800 tps, the system throughput reaches the maximum, close to 600 tps. When the test load exceeds 800 tps, the actual system throughput starts to drop, and approximately 90% of transactions have a delay time within 5000 ms. This method can be used in a lightweight IoT system.http://dx.doi.org/10.1155/2020/8846429 |
| spellingShingle | Yue Wu Liangtu Song Lei Liu Jincheng Li Xuefei Li Linli Zhou Consensus Mechanism of IoT Based on Blockchain Technology Shock and Vibration |
| title | Consensus Mechanism of IoT Based on Blockchain Technology |
| title_full | Consensus Mechanism of IoT Based on Blockchain Technology |
| title_fullStr | Consensus Mechanism of IoT Based on Blockchain Technology |
| title_full_unstemmed | Consensus Mechanism of IoT Based on Blockchain Technology |
| title_short | Consensus Mechanism of IoT Based on Blockchain Technology |
| title_sort | consensus mechanism of iot based on blockchain technology |
| url | http://dx.doi.org/10.1155/2020/8846429 |
| work_keys_str_mv | AT yuewu consensusmechanismofiotbasedonblockchaintechnology AT liangtusong consensusmechanismofiotbasedonblockchaintechnology AT leiliu consensusmechanismofiotbasedonblockchaintechnology AT jinchengli consensusmechanismofiotbasedonblockchaintechnology AT xuefeili consensusmechanismofiotbasedonblockchaintechnology AT linlizhou consensusmechanismofiotbasedonblockchaintechnology |