RT Journal Article
T1 An app performance optimization advisor for mobile device app marketplaces
A1 Saborido Infantes, Rubén
A1 Hindle, Abram
A1 Alba, Enrique
K1 Optimización
K1 Toma de decisiones multicriterio
AB On mobile phones, users and developers use apps official marketplaces serving as repositories of apps. The Google Play Store and Apple Store are the official marketplaces of Android and Apple products which offer more than a million apps. Although both repositories offer description of apps, information concerning performance is not available. Due to the constrained hardware of mobile devices, users and developers have to meticulously manage the resources available and they should be given access to performance information about apps. Even if this information was available, the selection of apps would still depend on user preferences and it would require a huge cognitive effort to make optimal decisions. Considering this fact we propose APOA, a recommendation system which can be implemented in any marketplace for helping users and developers to compare apps in terms of performance. APOA uses as input metric values of apps and a set of metrics to optimize. It solves an optimization problem and it generates optimal sets of apps for different user's context. We show how APOA works over an Android case study. Out of 140 apps, we define typical usage scenarios and we collect measurements of power, CPU, memory, and network usages to demonstrate the benefit of using APOA.
PB Elsevier
YR 2018
FD 2018
LK https://hdl.handle.net/10630/34136
UL https://hdl.handle.net/10630/34136
LA eng
NO Saborido, R., Khomh, F., Hindle, A., & Alba, E. (2018). An app performance optimization advisor for mobile device app marketplaces. Sustainable Computing Informatics And Systems, 19, 29-42. https://doi.org/10.1016/j.suscom.2018.05.008
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026