A First Look at Instant Service Consumption with Quick Apps on Mobile Devices

Mobile app ecosystem has gained giant success in providing services on mobile devices to facilitate almost all aspects in our daily life. However, the whole-package installation and dramatically increasing package size are now preventing users from trying more apps. To address the issue, many lightweight frameworks have emerged, enabling to provide the experience of instant service consumption where apps are of small size and no installation is needed to consuming services provided by the apps. In this paper, we conduct the first empirical study on instant service consumption on mobile devices. We focus on one of the most popular frameworks, quick apps, which are proposed and supported by nine mainstream mobile phone manufacturers in China. Quick apps are implemented with Web-based technologies, and run as native apps without the need of installation. We find that quick apps have much smaller size and only provide a limited set of services compared to their corresponding native apps. Then, we characterize the performance differences between quick apps and native apps in terms of launching time, data drain, and network connections, when the two kinds of apps provide the same services. Our observations reveal that quick apps perform better than native apps thanks to its much smaller size and less functionalities in a single page. Finally, we propose a machine learning based approach to helping developers construct the quick app from an existing native app.