{"title":"一种改进概率缓存的网络状态递归估计","authors":"Munehiro Namba","doi":"10.1109/SOCPAR.2015.7492819","DOIUrl":null,"url":null,"abstract":"There is a trend to introduce content caches as an inherent capacity of network device, such as routers, for improving the efficiency of content distribution and reducing network traffic. In this paper, we discuss the network state estimation in probabilistic caching based on a study with Bayesian inference, and propose a recursive estimation method for potentially improving the performance of adaptation to time-varying network state.","PeriodicalId":409493,"journal":{"name":"2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR)","volume":"249 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A recursive estimation of network state for improving probabilistic caching\",\"authors\":\"Munehiro Namba\",\"doi\":\"10.1109/SOCPAR.2015.7492819\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is a trend to introduce content caches as an inherent capacity of network device, such as routers, for improving the efficiency of content distribution and reducing network traffic. In this paper, we discuss the network state estimation in probabilistic caching based on a study with Bayesian inference, and propose a recursive estimation method for potentially improving the performance of adaptation to time-varying network state.\",\"PeriodicalId\":409493,\"journal\":{\"name\":\"2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR)\",\"volume\":\"249 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOCPAR.2015.7492819\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOCPAR.2015.7492819","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A recursive estimation of network state for improving probabilistic caching
There is a trend to introduce content caches as an inherent capacity of network device, such as routers, for improving the efficiency of content distribution and reducing network traffic. In this paper, we discuss the network state estimation in probabilistic caching based on a study with Bayesian inference, and propose a recursive estimation method for potentially improving the performance of adaptation to time-varying network state.