CACHE DATA REPLACEMENT POLICY BASED ON RECENTLY USED ACCESS DATA AND EUCLIDEAN DISTANCE

Mulki Indana Zulfa; Muhammad Syaiful Aliim; Ari Fadli; Waleed Ali

doi:10.52436/1.jutif.2023.4.4.1244

Mulki Indana Zulfa Electrical Engineering Department, Engineering Faculty, Universitas Jenderal Soedirman, Indonesia
Muhammad Syaiful Aliim Electrical Engineering Department, Engineering Faculty, Universitas Jenderal Soedirman, Indonesia
Ari Fadli Computer Science Department, Mathematics and Natural Sciences Faculty, Universitas Gadjah Mada, Indonesia
Waleed Ali Information Technology Department, King Abdulaziz University, Saudi Arabia

DOI: https://doi.org/10.52436/1.jutif.2023.4.4.1244

Keywords: application level caching, in memory database, hit ratio, relational database, web application

Abstract

Data access management in web-based applications that use relational databases must be well thought out because the data continues to grow every day. The Relational Database Management System (RDBMS) has a relatively slow access speed because the data is stored on disk. This causes problems with decreased database server performance and slow response times. One strategy to overcome this is to implement caching at the application level. This paper proposed SIMGD framework that models Application Level Caching (ALC) to speed up relational data access in web applications. The ALC strategy maps each controller and model that has access to the database into a node-data in the in-Memory Database (IMDB). Not all node-data can be included in IMDB due to limited capacity. Therefore, the SIMGD framework uses the Euclidean distance calculation method for each node-data with its top access data as a cache replacement policy. Node-data with Euclidean distance closer to their top access data have a high priority to be maintained in the caching server. Simulation results show at the 25KB cache configuration, the SIMGD framework excels in achieving hit ratios compared to the LRU algorithm of 6.46% and 6.01%, respectively.

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