Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine Learning
With the development of wireless networking technology, current Internet-of-Things (IoT) devices are equipped with multiple network access interfaces. Multipath TCP (MPTCP) technology can improve the throughput of data transmission. However, traditional MPTCP path management may cause problems such...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/22/6573 |
| _version_ | 1797547620070064128 |
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| author | Ruiwen Ji Yuanlong Cao Xiaotian Fan Yirui Jiang Gang Lei Yong Ma |
| author_facet | Ruiwen Ji Yuanlong Cao Xiaotian Fan Yirui Jiang Gang Lei Yong Ma |
| author_sort | Ruiwen Ji |
| collection | DOAJ |
| description | With the development of wireless networking technology, current Internet-of-Things (IoT) devices are equipped with multiple network access interfaces. Multipath TCP (MPTCP) technology can improve the throughput of data transmission. However, traditional MPTCP path management may cause problems such as data confusion and even buffer blockage, which severely reduces transmission performance. This research introduces machine learning algorithms into MPTCP path management, and proposes an automatic learning selection path mechanism based on MPTCP (ALPS-MPTCP), which can adaptively select some high-quality paths and transmit data at the same time. This paper designs a simulation experiment that compares the performance of four machine learning algorithms in judging path quality. The experimental results show that, considering the running time and accuracy, the random forest algorithm has the best performance in judging path quality. |
| first_indexed | 2024-03-10T14:46:39Z |
| format | Article |
| id | doaj.art-440846f13bf44164bc662cfd6354c411 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T14:46:39Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-440846f13bf44164bc662cfd6354c4112023-11-20T21:19:51ZengMDPI AGSensors1424-82202020-11-012022657310.3390/s20226573Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine LearningRuiwen Ji0Yuanlong Cao1Xiaotian Fan2Yirui Jiang3Gang Lei4Yong Ma5School of Software, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Software, Jiangxi Normal University, Nanchang 330022, ChinaDepartment of Computer Science and Engineering, University of Bologna, 40126 Bologna BO, ItalySchool of Software, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Software, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, ChinaWith the development of wireless networking technology, current Internet-of-Things (IoT) devices are equipped with multiple network access interfaces. Multipath TCP (MPTCP) technology can improve the throughput of data transmission. However, traditional MPTCP path management may cause problems such as data confusion and even buffer blockage, which severely reduces transmission performance. This research introduces machine learning algorithms into MPTCP path management, and proposes an automatic learning selection path mechanism based on MPTCP (ALPS-MPTCP), which can adaptively select some high-quality paths and transmit data at the same time. This paper designs a simulation experiment that compares the performance of four machine learning algorithms in judging path quality. The experimental results show that, considering the running time and accuracy, the random forest algorithm has the best performance in judging path quality.https://www.mdpi.com/1424-8220/20/22/6573IoT communicationmultipath TCPpath managementmachine learning |
| spellingShingle | Ruiwen Ji Yuanlong Cao Xiaotian Fan Yirui Jiang Gang Lei Yong Ma Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine Learning Sensors IoT communication multipath TCP path management machine learning |
| title | Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine Learning |
| title_full | Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine Learning |
| title_fullStr | Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine Learning |
| title_full_unstemmed | Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine Learning |
| title_short | Multipath TCP-Based IoT Communication Evaluation: From the Perspective of Multipath Management with Machine Learning |
| title_sort | multipath tcp based iot communication evaluation from the perspective of multipath management with machine learning |
| topic | IoT communication multipath TCP path management machine learning |
| url | https://www.mdpi.com/1424-8220/20/22/6573 |
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