基于压缩感知的5G物联网视频流流量预测

2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC) Pub Date : 2019-06-24 DOI:10.1109/IWCMC.2019.8766662

Shuangli Wu, Wei Mao, Tao Hong, Cong Liu, M. Kadoch

{"title":"基于压缩感知的5G物联网视频流流量预测","authors":"Shuangli Wu, Wei Mao, Tao Hong, Cong Liu, M. Kadoch","doi":"10.1109/IWCMC.2019.8766662","DOIUrl":null,"url":null,"abstract":"Nowadays, IoT video applications are in a sharp rise, various real-time video streaming of video surveillance systems transmitted via Internet are widely investigated. The real-time video surveillance can actively monitor and detect the abnormal events in time. In 5G HetNets, we specifically develop a compressed sensing based linear predictor to predict the traffic load at the next moment. The results justify that our proposed method can forecast the traffic load and improve system performance.","PeriodicalId":363800,"journal":{"name":"2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Compressed Sensing Based Traffic Prediction For 5G HetNet IoT Video Streaming\",\"authors\":\"Shuangli Wu, Wei Mao, Tao Hong, Cong Liu, M. Kadoch\",\"doi\":\"10.1109/IWCMC.2019.8766662\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, IoT video applications are in a sharp rise, various real-time video streaming of video surveillance systems transmitted via Internet are widely investigated. The real-time video surveillance can actively monitor and detect the abnormal events in time. In 5G HetNets, we specifically develop a compressed sensing based linear predictor to predict the traffic load at the next moment. The results justify that our proposed method can forecast the traffic load and improve system performance.\",\"PeriodicalId\":363800,\"journal\":{\"name\":\"2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWCMC.2019.8766662\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWCMC.2019.8766662","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 9

摘要

如今，物联网视频应用急剧兴起，通过互联网传输的视频监控系统的各种实时视频流被广泛研究。实时视频监控能够主动监控并及时发现异常事件。在5G HetNets中，我们专门开发了一种基于压缩感知的线性预测器来预测下一刻的流量负载。结果表明，该方法可以有效地预测流量负荷，提高系统性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Compressed Sensing Based Traffic Prediction For 5G HetNet IoT Video Streaming

Nowadays, IoT video applications are in a sharp rise, various real-time video streaming of video surveillance systems transmitted via Internet are widely investigated. The real-time video surveillance can actively monitor and detect the abnormal events in time. In 5G HetNets, we specifically develop a compressed sensing based linear predictor to predict the traffic load at the next moment. The results justify that our proposed method can forecast the traffic load and improve system performance.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC)

自引率

0.00%

发文量