Optimizing Memory Usage in Android Smartphones: A Comparative Analysis of Data Structures Across Different Hardware Architectures

Lucia Nugraheni Harnaningrum; Pius Dian Widi Anggoro; Asyahri Hadi Nasyuha; Muchamad Mafmudin; Akbar Wijaya

doi:10.3991/ijim.v19i15.55713

Authors

Lucia Nugraheni Harnaningrum Digital Teknologi Indonesia University, Yogyakarta, Indonesia https://orcid.org/0009-0008-6432-3585
Pius Dian Widi Anggoro Digital Teknologi Indonesia University, Yogyakarta, Indonesia https://orcid.org/0009-0008-9816-958X
Asyahri Hadi Nasyuha Digital Teknologi Indonesia University, Yogyakarta, Indonesia https://orcid.org/0000-0002-9633-5571
Muchamad Mafmudin Digital Teknologi Indonesia University, Yogyakarta, Indonesia
Akbar Wijaya Digital Teknologi Indonesia University, Yogyakarta, Indonesia

DOI:

https://doi.org/10.3991/ijim.v19i15.55713

Keywords:

Memory Optimization, Android Smartphones, Data Structures, Hardware Architectures, Mobile Performance

Abstract

Efficient memory management is a critical factor in enhancing the performance of mobile applications, particularly in resource-constrained environments. This study comprehensively evaluates memory consumption across various data structures on Android smartphones with different hardware architectures, including Snapdragon 732G, Snapdragon 805, and Dimensity 9300. The analysis employs statistical metrics such as standard deviation, minimum, median, and maximum memory usage to assess different data structures’ efficiency. Empirical results demonstrate that primitive data structures exhibit significantly lower memory overhead than more complex structures such as LinkedList and ArrayList, which tend to increase memory fragmentation and garbage collection (GC) overhead. A significant change is the testing of the Primitive Array data structure with API 30 to API 33, which experienced a decrease in memory usage of almost 61%. These findings offer valuable insights for Android developers, enabling them to make informed decisions in selecting optimal data structures to enhance memory efficiency, reduce application latency, and improve overall user experience.