Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution.
With the continuous development of 5G network, how to further improve the routing and transmission efficiency of electric power IoT has become a popular research at present. Facing the current problems of high data transmission delay, low efficiency, and large task volume in the electric power IoT,...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0314253 |
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| _version_ | 1823856858117439488 |
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| author | Qi Jin |
| author_facet | Qi Jin |
| author_sort | Qi Jin |
| collection | DOAJ |
| description | With the continuous development of 5G network, how to further improve the routing and transmission efficiency of electric power IoT has become a popular research at present. Facing the current problems of high data transmission delay, low efficiency, and large task volume in the electric power IoT, this research combines software-defined networking to design a multi-path low-latency routing and transmission model under the concept of task allocation. First, the grid data communication network model and network slicing technology in 5G power IoT are introduced. On this basis, considering the data transmission in the core network in the power IoT, a multi-path low-latency routing optimization transmission model based on software-defined network task allocation is designed by combining the software-defined network controller and task allocation concept. The results indicated that the average delay of the designed model is only 15.78ms when the transmission task size is 10KB and 23.38ms when the transmission task size is 50KB. In addition, the designed model was able to achieve a throughput of 298bps in the local area network and the lowest jitter and packet loss in the wide area network, which are 0.13ms and 0.001%. It can be concluded that the constructed multi-path low-latency routing and transmission model can not only provide theoretical guidance for the optimization of data transmission in the power IoT, but also lay the foundation for the in-depth application and development of software-defined networking in the power IoT and other fields. |
| format | Article |
| id | doaj-art-ce1ce9cb7c39468890eb50d31344d127 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-ce1ce9cb7c39468890eb50d31344d1272025-02-12T05:31:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031425310.1371/journal.pone.0314253Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution.Qi JinWith the continuous development of 5G network, how to further improve the routing and transmission efficiency of electric power IoT has become a popular research at present. Facing the current problems of high data transmission delay, low efficiency, and large task volume in the electric power IoT, this research combines software-defined networking to design a multi-path low-latency routing and transmission model under the concept of task allocation. First, the grid data communication network model and network slicing technology in 5G power IoT are introduced. On this basis, considering the data transmission in the core network in the power IoT, a multi-path low-latency routing optimization transmission model based on software-defined network task allocation is designed by combining the software-defined network controller and task allocation concept. The results indicated that the average delay of the designed model is only 15.78ms when the transmission task size is 10KB and 23.38ms when the transmission task size is 50KB. In addition, the designed model was able to achieve a throughput of 298bps in the local area network and the lowest jitter and packet loss in the wide area network, which are 0.13ms and 0.001%. It can be concluded that the constructed multi-path low-latency routing and transmission model can not only provide theoretical guidance for the optimization of data transmission in the power IoT, but also lay the foundation for the in-depth application and development of software-defined networking in the power IoT and other fields.https://doi.org/10.1371/journal.pone.0314253 |
| spellingShingle | Qi Jin Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. PLoS ONE |
| title | Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. |
| title_full | Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. |
| title_fullStr | Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. |
| title_full_unstemmed | Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. |
| title_short | Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. |
| title_sort | optimized transmission of multi path low latency routing for electricity internet of things based on sdn task distribution |
| url | https://doi.org/10.1371/journal.pone.0314253 |
| work_keys_str_mv | AT qijin optimizedtransmissionofmultipathlowlatencyroutingforelectricityinternetofthingsbasedonsdntaskdistribution |