{"title":"利用移动性预测来实现移动性和流行度缓存以及DASH适应","authors":"V. Siris, Xenofon Vasilakos, D. Dimopoulos","doi":"10.1109/WoWMoM.2016.7523523","DOIUrl":null,"url":null,"abstract":"We present our recent work investigating how mobility prediction can be exploited for improving the performance of mobile users in two directions: proactive caching requested content close to the network attachment points where a mobile has a high probability to connect to and DASH (Dynamic Adaptive Streaming over HTTP) video quality adaptation. For proactive caching we discuss a new model to proactively cache content based on both mobility prediction and content popularity. An important feature of the model is that it dynamically adapts caching decisions to the relative importance of the two factors. For DASH adaptation we discuss a procedure that exploits mobility and throughput prediction to select the quality levels of video segments requested by a DASH player in order to achieve improved QoE, in terms of both high video quality and few video quality switches.","PeriodicalId":187747,"journal":{"name":"2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Exploiting mobility prediction for mobility & popularity caching and DASH adaptation\",\"authors\":\"V. Siris, Xenofon Vasilakos, D. Dimopoulos\",\"doi\":\"10.1109/WoWMoM.2016.7523523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present our recent work investigating how mobility prediction can be exploited for improving the performance of mobile users in two directions: proactive caching requested content close to the network attachment points where a mobile has a high probability to connect to and DASH (Dynamic Adaptive Streaming over HTTP) video quality adaptation. For proactive caching we discuss a new model to proactively cache content based on both mobility prediction and content popularity. An important feature of the model is that it dynamically adapts caching decisions to the relative importance of the two factors. For DASH adaptation we discuss a procedure that exploits mobility and throughput prediction to select the quality levels of video segments requested by a DASH player in order to achieve improved QoE, in terms of both high video quality and few video quality switches.\",\"PeriodicalId\":187747,\"journal\":{\"name\":\"2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WoWMoM.2016.7523523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WoWMoM.2016.7523523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploiting mobility prediction for mobility & popularity caching and DASH adaptation
We present our recent work investigating how mobility prediction can be exploited for improving the performance of mobile users in two directions: proactive caching requested content close to the network attachment points where a mobile has a high probability to connect to and DASH (Dynamic Adaptive Streaming over HTTP) video quality adaptation. For proactive caching we discuss a new model to proactively cache content based on both mobility prediction and content popularity. An important feature of the model is that it dynamically adapts caching decisions to the relative importance of the two factors. For DASH adaptation we discuss a procedure that exploits mobility and throughput prediction to select the quality levels of video segments requested by a DASH player in order to achieve improved QoE, in terms of both high video quality and few video quality switches.