Tackling Mobile Traffic Critical Path Analysis With Passive and Active Measurements

Abstract

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.