Leveraging Program Analysis to Reduce User-Perceived Latency in Mobile Applications

TL;DR

This paper introduces PALOMA, a client-centric method that uses program analysis to prefetch HTTP requests in Android apps, significantly reducing network latency and improving user experience.

Contribution

PALOMA employs string and callback control-flow analysis to automatically instrument apps for effective prefetching, a novel approach in reducing mobile network latency.

Findings

PALOMA reduces HTTP request latency by several hundred milliseconds.

It is effective on both benchmark and real-world Android applications.

Significant runtime savings are achieved through prefetching.

Abstract

Reducing network latency in mobile applications is an effective way of improving the mobile user experience and has tangible economic benefits. This paper presents PALOMA, a novel client-centric technique for reducing the network latency by prefetching HTTP requests in Android apps. Our work leverages string analysis and callback control-flow analysis to automatically instrument apps using PALOMA's rigorous formulation of scenarios that address "what" and "when" to prefetch. PALOMA has been shown to incur significant runtime savings (several hundred milliseconds per prefetchable HTTP request), both when applied on a reusable evaluation benchmark we have developed and on real applications