Chameleon: A Self-adaptive cache strategy under the ever-changing access frequency in edge network

Pengmiao Li, Yuchao Zhang, Wendong Wang, Weiliang Meng, Yi Zheng, Ke Xu, Zhili Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

In recent years, with the maturity of 5G and Internet of Things technologies, the number of mobile applications and the amount of data access have increased explosively. However, the frequency of these accesses varies considerably at different times of the day, requiring different caching strategies in those limited-capacity edge servers. Existing caching strategies perform well when the access frequency is stable. However, they ignore the time-varying characteristics of user access frequency in different periods, resulting in a low hit rate in ever-changing frequency scenarios. To improve the hit rate in such scenarios, we propose a cache replacement policy called Chameleon, which consists of two components, AutoFre, and Crates. AutoFre is an admission algorithm that predicts the future access frequency category and calculates the admission thresholds based on the prediction result. While Crates is an eviction algorithm, it selects the contents evicted by designing a customized principal component analysis algorithm. We conduct a series of experiments with real application traces from ChuangCache. The trace has 9,839,213 user accesses in 48 h. The results demonstrate that Chameleon reaches about 98% in caching hit rate and outperforms SecondHit-Crates algorithm about 8% in frequency-changing edge networks.

Original languageEnglish (US)
Pages (from-to)301-310
Number of pages10
JournalComputer Communications
Volume194
DOIs
StatePublished - Oct 1 2022

Bibliographical note

Funding Information:
The work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 62172054 , BUPT-ChuangCache Joint Laboratory under B2020009 , the Key Project of Beijing Natural Science Foundation under M21030 , the NSFC under Grant 62072047 , and the National Key R&D Program of China under Grant 2019YFB1802603 . The work of Pengmiao Li was supported in part by the BUPT Excellent Ph.D. Students Foundation under CX2019134 .

Funding Information:
The work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 62172054, BUPT-ChuangCache Joint Laboratoryunder B2020009, the Key Project of Beijing Natural Science Foundation under M21030, the NSFC under Grant 62072047, and the National Key R&D Program of China under Grant 2019YFB1802603. The work of Pengmiao Li was supported in part by the BUPT Excellent Ph.D. Students Foundation under CX2019134.

Publisher Copyright:
© 2022 Elsevier B.V.

Keywords

  • Access frequency
  • Cache admission
  • Cache eviction
  • Edge caching
  • Hit rate

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