Research and application of traffic engineering algorithm based on deep learning
With the development and application of 5G network, the amount of traffic in network increased rapidly, which caused the lack of bandwidth resource.In order to improve the utilization of network resource and satisfy the critical user requirement for QoS (quality of service), a novel traffic engineer...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2021-02-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021027/ |
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| _version_ | 1841529073212325888 |
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| author | Daoyun HU Jin QI Qianchun LU Feng LI Hongqiang FANG |
| author_facet | Daoyun HU Jin QI Qianchun LU Feng LI Hongqiang FANG |
| author_sort | Daoyun HU |
| collection | DOAJ |
| description | With the development and application of 5G network, the amount of traffic in network increased rapidly, which caused the lack of bandwidth resource.In order to improve the utilization of network resource and satisfy the critical user requirement for QoS (quality of service), a novel traffic engineering algorithm based on deep learning in SDN was proposed.At last, simulation results show that the proposed algorithm not only can calculate an efficient path for service in real time, but also can improve the QoS and the utilization of network resource, as well as reduce network congestion. |
| format | Article |
| id | doaj-art-1c65d536b6834b1b808587273503dad7 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2021-02-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-1c65d536b6834b1b808587273503dad72025-01-15T03:25:52ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012021-02-013710711459806872Research and application of traffic engineering algorithm based on deep learningDaoyun HUJin QIQianchun LUFeng LIHongqiang FANGWith the development and application of 5G network, the amount of traffic in network increased rapidly, which caused the lack of bandwidth resource.In order to improve the utilization of network resource and satisfy the critical user requirement for QoS (quality of service), a novel traffic engineering algorithm based on deep learning in SDN was proposed.At last, simulation results show that the proposed algorithm not only can calculate an efficient path for service in real time, but also can improve the QoS and the utilization of network resource, as well as reduce network congestion.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021027/SDNtraffic engineeringdeep learningQoS |
| spellingShingle | Daoyun HU Jin QI Qianchun LU Feng LI Hongqiang FANG Research and application of traffic engineering algorithm based on deep learning Dianxin kexue SDN traffic engineering deep learning QoS |
| title | Research and application of traffic engineering algorithm based on deep learning |
| title_full | Research and application of traffic engineering algorithm based on deep learning |
| title_fullStr | Research and application of traffic engineering algorithm based on deep learning |
| title_full_unstemmed | Research and application of traffic engineering algorithm based on deep learning |
| title_short | Research and application of traffic engineering algorithm based on deep learning |
| title_sort | research and application of traffic engineering algorithm based on deep learning |
| topic | SDN traffic engineering deep learning QoS |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021027/ |
| work_keys_str_mv | AT daoyunhu researchandapplicationoftrafficengineeringalgorithmbasedondeeplearning AT jinqi researchandapplicationoftrafficengineeringalgorithmbasedondeeplearning AT qianchunlu researchandapplicationoftrafficengineeringalgorithmbasedondeeplearning AT fengli researchandapplicationoftrafficengineeringalgorithmbasedondeeplearning AT hongqiangfang researchandapplicationoftrafficengineeringalgorithmbasedondeeplearning |