内容分发网络——网络成本和缓存命中率优化的q -学习方法

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) Pub Date : 2020-08-30 DOI:10.1109/CCECE47787.2020.9255813

Diego Felix de Almeida, Jason Yen, Michal Aibin

{"title":"内容分发网络——网络成本和缓存命中率优化的q -学习方法","authors":"Diego Felix de Almeida, Jason Yen, Michal Aibin","doi":"10.1109/CCECE47787.2020.9255813","DOIUrl":null,"url":null,"abstract":"With an increasing demand for web content delivery, it is necessary to optimize the CAPEX and OPEX costs of the Content Delivery Networks. Ideally, all web content to be requested should be stored in local cache nodes at all times. However, the content demand varies across space and time. In this paper, we propose a Content Delivery Network model that allows us to choose the best trade-off between costs and cache hit ratio.","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Content Delivery Networks - Q-Learning Approach for Optimization of the Network Cost and the Cache Hit Ratio\",\"authors\":\"Diego Felix de Almeida, Jason Yen, Michal Aibin\",\"doi\":\"10.1109/CCECE47787.2020.9255813\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With an increasing demand for web content delivery, it is necessary to optimize the CAPEX and OPEX costs of the Content Delivery Networks. Ideally, all web content to be requested should be stored in local cache nodes at all times. However, the content demand varies across space and time. In this paper, we propose a Content Delivery Network model that allows us to choose the best trade-off between costs and cache hit ratio.\",\"PeriodicalId\":296506,\"journal\":{\"name\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE47787.2020.9255813\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE47787.2020.9255813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

随着网络内容交付需求的增加，有必要优化内容交付网络的资本支出和运营成本。理想情况下，所有被请求的web内容应该始终存储在本地缓存节点中。然而，内容需求因时空而异。在本文中，我们提出了一个内容交付网络模型，该模型允许我们在成本和缓存命中率之间做出最佳权衡。

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

Content Delivery Networks - Q-Learning Approach for Optimization of the Network Cost and the Cache Hit Ratio

With an increasing demand for web content delivery, it is necessary to optimize the CAPEX and OPEX costs of the Content Delivery Networks. Ideally, all web content to be requested should be stored in local cache nodes at all times. However, the content demand varies across space and time. In this paper, we propose a Content Delivery Network model that allows us to choose the best trade-off between costs and cache hit ratio.

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

2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

自引率

0.00%

发文量