Android Local Data Storage for Enhanced Quality of Experience: Performance Benchmark of Different Approaches on a Transactional Application
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Date
2022
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Abstract
Mobile applications are one of the commonly used tools for human robot interaction recently as a result of technological development in this area. These applications interact with human by the data processed and presented with a user interface. Hence, the data processing is one of the major factors that affect the quick responsiveness of the application and the quality of experience (QoE) of end-users. Local data storage is utilized to retrieve the data not only for offline mode but also to achieve it faster. However, there are different approaches for local storage and they affect the QoE in a different way with respect to the data being processed. In this study, a performance benchmark is conducted among the major local storage approaches including file system storage, SQLite database and shared preferences. For this purpose, a set of experiments is conducted by considering different data characteristics for storage. The storing and retrieving time of the data is taken into account for the evaluation of end-user's QoE. As a result of the evaluation, the superiority and inferiority of different approaches against the data characteristic are discussed. © 2022 IEEE.
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Keywords
Benchmarking , Data handling , Digital storage , Man machine systems , Quality of service , Robot programming , User interfaces , Android programming , Data characteristics , Data storage , End-users , Humans-robot interactions , Local data , Local data storage , Performance , Quality of experience , Sqlite , Human robot interaction