Research on Q-learning based rate control approach for HTTP adaptive streaming
HTTP adaptive streaming (HAS) has become the standard for adaptive video streaming service.In changing network environments,current hardcoded-based rate adaptation algorithm was less flexible,and it is insufficient to consider the quality of experience (QoE).To optimize the QoE of users,a rate contr...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-09-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017178/ |
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| _version_ | 1850095803612266496 |
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| author | Li-rong XIONG Jing-zhi LEI Xin JIN |
| author_facet | Li-rong XIONG Jing-zhi LEI Xin JIN |
| author_sort | Li-rong XIONG |
| collection | DOAJ |
| description | HTTP adaptive streaming (HAS) has become the standard for adaptive video streaming service.In changing network environments,current hardcoded-based rate adaptation algorithm was less flexible,and it is insufficient to consider the quality of experience (QoE).To optimize the QoE of users,a rate control approach based on Q-learning strategy was proposed.the client environments of HTTP adaptive video streaming was modeled and the state transition rule was defined.Three parameters related to QoE were quantified and a novel reward function was constructed.The experiments were employed by the Q-learning rate control approach in two typical HAS algorithms.The experiments show the rate control approach can enhance the stability of rate switching in HAS clients. |
| format | Article |
| id | doaj-art-181d99d8485646f79da3a03fbaf0bde6 |
| institution | DOAJ |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-09-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-181d99d8485646f79da3a03fbaf0bde62025-08-20T02:41:21ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-09-0138182459711963Research on Q-learning based rate control approach for HTTP adaptive streamingLi-rong XIONGJing-zhi LEIXin JINHTTP adaptive streaming (HAS) has become the standard for adaptive video streaming service.In changing network environments,current hardcoded-based rate adaptation algorithm was less flexible,and it is insufficient to consider the quality of experience (QoE).To optimize the QoE of users,a rate control approach based on Q-learning strategy was proposed.the client environments of HTTP adaptive video streaming was modeled and the state transition rule was defined.Three parameters related to QoE were quantified and a novel reward function was constructed.The experiments were employed by the Q-learning rate control approach in two typical HAS algorithms.The experiments show the rate control approach can enhance the stability of rate switching in HAS clients.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017178/HTTP adaptive streaminghardcodedQ-learningrate controlstability |
| spellingShingle | Li-rong XIONG Jing-zhi LEI Xin JIN Research on Q-learning based rate control approach for HTTP adaptive streaming Tongxin xuebao HTTP adaptive streaming hardcoded Q-learning rate control stability |
| title | Research on Q-learning based rate control approach for HTTP adaptive streaming |
| title_full | Research on Q-learning based rate control approach for HTTP adaptive streaming |
| title_fullStr | Research on Q-learning based rate control approach for HTTP adaptive streaming |
| title_full_unstemmed | Research on Q-learning based rate control approach for HTTP adaptive streaming |
| title_short | Research on Q-learning based rate control approach for HTTP adaptive streaming |
| title_sort | research on q learning based rate control approach for http adaptive streaming |
| topic | HTTP adaptive streaming hardcoded Q-learning rate control stability |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017178/ |
| work_keys_str_mv | AT lirongxiong researchonqlearningbasedratecontrolapproachforhttpadaptivestreaming AT jingzhilei researchonqlearningbasedratecontrolapproachforhttpadaptivestreaming AT xinjin researchonqlearningbasedratecontrolapproachforhttpadaptivestreaming |