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

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. ACM CCS 2012Software and its engineering → Domain specific languages;

Trampoline variables: a general method for state accumulation in reactive programming

“…CFRP [43], Elm [16], Frenetic [20], Flask [28], FRPNow [45], FrTime [13], Gavial [37], Hae [50], Hokko [36], Midair [30], ReactiFi [42], REScala [38], and SFRP [10]. feedback Given a signal function (i.e., a reactive program) of type SF (𝑎, 𝑐) (𝑏, 𝑐) (where (𝑎, 𝑐) is the input type and (𝑏, 𝑐) the output type) and an initial value 𝑣, creates a new signal function of type SF 𝑎 𝑏 which contains the original signal function, connecting the output of type 𝑐 to the input of type 𝑐 with an implicit one-turn delay (i.e.…”