SDSL-Mobile: Enabling space-efficient data structures for mobile applications

This paper presents the process and results of porting the Succinct Data Structure Library 2.0 (SDSL-lite), a robust and well-established open-source C++11 library, to Android platforms. The resulting library, called SDSL-Mobile, implements space-efficient data structures, including wavelet trees, compressed suffix arrays, and bit vectors, which are essential for handling large datasets in domains such as bioinformatics and information retrieval. Although originally designed for desktop environments, the library is extended to Android using the Android Native Development Kit (NDK) to enable integration into mobile platforms. Functionality is evaluated by implementing wavelet forests within an Android application, and performance is compared against a desktop implementation. The results demonstrate the feasibility of deploying succinct data structures on mobile devices, highlighting new possibilities for advanced data processing in resource-constrained environments.

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Publication Details

Journal
SoftwareX
Published
2025-06-24
DOI
https://doi.org/10.1016/j.softx.2025.102234
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
0.00

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article

SDSL-Mobile: Enabling space-efficient data structures for mobile applications

Alexander Barquero, Christina Boucher, Mattia Prosperi, Aaron Hong et al.
SoftwareX
Algorithms and Data Compression
article

SDSL-Mobile: Enabling space-efficient data structures for mobile applications

Alexander Barquero, Christina Boucher, Mattia Prosperi, Aaron Hong, Anisha Ashok Wadhwani, Jaimé Ruiz, Tyler Pencinger
article en

Abstract

This paper presents the process and results of porting the Succinct Data Structure Library 2.0 (SDSL-lite), a robust and well-established open-source C++11 library, to Android platforms. The resulting library, called SDSL-Mobile, implements space-efficient data structures, including wavelet trees, compressed suffix arrays, and bit vectors, which are essential for handling large datasets in domains such as bioinformatics and information retrieval. Although originally designed for desktop environments, the library is extended to Android using the Android Native Development Kit (NDK) to enable integration into mobile platforms. Functionality is evaluated by implementing wavelet forests within an Android application, and performance is compared against a desktop implementation. The results demonstrate the feasibility of deploying succinct data structures on mobile devices, highlighting new possibilities for advanced data processing in resource-constrained environments.

SoftwareXVol. 31
University of Florida Health (US), University of Florida Health Science Center (US), Florida College (US)
National Science Foundation
Openalex Percentile: Top 93%
Algorithms and Data Compression
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