A smart cache content update policy based on deep reinforcement learning

A smart cache content update policy based on deep reinforcement learning

This paper proposes a DRL-based cache content update policy in the cache-enabled network to improve the cache hit ratio and reduce the average latency. In contrast to the existing policies, a more practical cache scenario is considered in this work, in which the content requests vary by both time an...

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Bibliographic Details
Main Authors: Li, Lincan, Kwong, Chiew Foong, Liu, Qianyu, Wang, Jing
Format: Article
Language:English
Published: Hindawi Limited 2020
Subjects:
cache; deep reinforcement learning (DRL); deep Q-learning network (DQN); content update; cache hit ratio; average latency; spatiotemporally varying
Online Access:https://eprints.nottingham.ac.uk/64083/

Internet

https://eprints.nottingham.ac.uk/64083/

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