NDN 中边缘计算与缓存的联合优化

Translated title of the contribution: Joint optimization of edge computing and caching in NDN

Yu Zhang, Min Cheng

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Named data networking (NDN) is architecturally easier to integrate with edge computing as its routing is based on content names and its nodes have caching capabilities. Firstly, an integrated framework was proposed for implementing dynamic coordination of networking, computing and caching in NDN. Then, considering the variability of content popularity in different regions, a matrix factorization-based algorithm was proposed to predict local content popularity, and deep reinforcement learning was used to solve the the problem of joint optimization for computing and caching resource allocation and cache placement policy with the goal of maximizing system operating profit. Finally, the simulation environment was built in ndnSIM. The simulation results show that the proposed scheme has significant advantages in improving cache hit rate, reducing the average delay and the load on the remote servers.

Translated title of the contributionJoint optimization of edge computing and caching in NDN
Original languageChinese (Traditional)
Pages (from-to)164-175
Number of pages12
JournalTongxin Xuebao/Journal on Communications
Volume43
Issue number8
DOIs
Publication statusPublished - 25 Aug 2022

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