  Critical Path Analysis (CPA) studies the delivery of webpages to identify
page resources, their interrelations, as well as their impact on the page
loading latency. Despite CPA being a generic methodology, its mechanisms have
been applied only to browsers and web traffic, but those do not directly apply
to study generic mobile apps. Likewise, web browsing represents only a small
fraction of the overall mobile traffic. In this paper, we take a first step
towards filling this gap by exploring how CPA can be performed for generic
mobile applications. We propose Mobile Critical Path Analysis (MCPA), a
methodology based on passive and active network measurements that is applicable
to a broad set of apps to expose a fine-grained view of their traffic dynamics.
We validate MCPA on popular apps across different categories and usage
scenarios. We show that MCPA can identify user interactions with mobile apps
only based on traffic monitoring, and the relevant network activities that are
bottlenecks. Overall, we observe that apps spend 60% of time and 84% of bytes
on critical traffic on average, corresponding to +22% time and +13% bytes than
what observed for browsing.
