An App Performance Optimization Advisor for Mobile Device App Marketplaces

نویسندگان

  • Rubén Saborido
  • Foutse Khomh
  • Abram Hindle
  • Enrique Alba
چکیده

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 a set of metrics to optimize and metric values of apps. It solves an optimization problem and it generates optimal sets of apps. 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.

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عنوان ژورنال:
  • CoRR

دوره abs/1709.04916  شماره 

صفحات  -

تاریخ انتشار 2017