CacheBoost: Harnessing Machine Learning for Peak Cache Performance

DOI

10.2991/978-94-6463-482-2_2How to use a DOI?

Keywords

Block cache model; vector Cache model; Beladys optimal algorithm; KNN; logistic regression

Abstract

This research investigates the integration of machine learning (ML) models into cache management systems to enhance overall performance. Two distinct strategies, the Block Cache model and Vector Cache model, are implemented, each incorporating widely used cache replacement policies—Least Recently Used (LRU) and Least Frequently Used (LFU). Furthermore, three ML models—Logistic Regression, KNearest Neighbors (KNN), and Neural Network—are integrated into these cache systems. The primary goal is to improve the cache hit rate by combining ML models with Belady’s Optimal algorithm. The performance of the five cache models is assessed using key metrics such as cache hit rate, miss rate, and eviction rate. A comparative analysis is undertaken to gauge the effectiveness of each approach and the influence of various ML models on cache performance. This study aims to provide valuable insights into the complex interaction between traditional cache replacement policies and advanced ML techniques, offering a nuanced understanding of the potential enhancements in cache hit rates achieved through machine learning integration. The findings and observations contribute to the ongoing exploration of cache optimization, guiding future developments to enhance system performance.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Sharath Kumar Jagannathan
AU  - Maheswari Raja
AU  - P. Vijaya
AU  - Reena Abraham
PY  - 2024
DA  - 2024/08/23
TI  - CacheBoost: Harnessing Machine Learning for Peak Cache Performance
BT  - Proceedings of the 2nd International Conference on Innovation in Information Technology and Business (ICIITB 2024)
PB  - Atlantis Press
SP  - 5
EP  - 21
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-482-2_2
DO  - 10.2991/978-94-6463-482-2_2
ID  - Jagannathan2024
ER  -