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

被引：2
|
作者：
de Almeida, Diego Felix [1 ]
Yen, Jason [1 ]
Aibin, Michal [1 ]
机构：
[1] British Columbia Inst Technol, Dept Comp, Vancouver, BC, Canada
来源：
2020 IEEE CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE) | 2020年
关键词：
content delivery networks; q-learning; caching;
D O I：
10.1109/ccece47787.2020.9255813
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
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页数：5
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