ReactiFi: Reactive Programming of Wi-Fi Firmware on Mobile Devices

Artur Sterz1, Matthias Eichholz2, Ragnar Mogk3, Lars Baumgärtner4, Pablo Graubner5, Matthias Hollick6, Mira Mezini7, and Bernd Freisleben8

The Art, Science, and Engineering of Programming, 2021, Vol. 5, Issue 2, Article 4

Submission date: 2020-01-31
Publication date: 2020-11-02
DOI: https://doi.org/10.22152/programming-journal.org/2021/5/4
Full text: PDF

Abstract

Network programmability will be required to handle future increased network traffic and constantly changing application needs. However, there is currently no way of using a high-level, easy to use programming language to program Wi-Fi firmware. This impedes rapid prototyping and deployment of novel network services/applications and hinders continuous performance optimization in Wi-Fi networks, since expert knowledge is required for both the used hardware platforms and the Wi-Fi domain. In this paper, we present ReactiFi, a high-level reactive programming language to program Wi-Fi chips on mobile consumer devices. ReactiFi enables programmers to implement extensions of PHY, MAC, and IP layer mechanisms without requiring expert knowledge of Wi-Fi chips, allowing for novel applications and network protocols. ReactiFi programs are executed directly on the Wi-Fi chip, improving performance and power consumption compared to execution on the main CPU. ReactiFi is conceptually similar to functional reactive languages, but is dedicated to the domain-specific needs of Wi-Fi firmware. First, it handles low-level platform-specific details without interfering with the core functionality of Wi-Fi chips. Second, it supports static reasoning about memory usage of applications, which is important for typically memory-constrained Wi-Fi chips. Third, it limits dynamic changes of dependencies between computations to dynamic branching, in order to enable static reasoning about the order of computations. We evaluate ReactiFi empirically in two real-world case studies. Our results show that throughput, latency, and power consumption are significantly improved when executing applications on the Wi-Fi chip rather than in the operating system kernel or in user space. Moreover, we show that the high-level programming abstractions of ReactiFi have no performance overhead compared to manually written C code.