Analyzing and Disentangling Interleaved Interrupt-driven IoT Programs

TL;DR

This paper introduces a formal definition and a real-time, efficient algorithm for identifying Interrupt Procedure Instances (IPIs) in IoT Wireless Sensor Network programs, enabling better analysis of their complex concurrent behaviors.

Contribution

It presents the first formal definition of IPIs and a generic, correct, and efficient algorithm for their real-time identification in WSN programs.

Findings

The proposed algorithm is more efficient than existing methods in time and space.

The algorithm provides a foundation for IPI-based analysis of WSN programs.

Theoretical and empirical validation confirms the algorithm's effectiveness.

Abstract

In the Internet of Things (IoT) community, Wireless Sensor Network (WSN) is a key technique to enable ubiquitous sensing of environments and provide reliable services to applications. WSN programs, typically interrupt-driven, implement the functionalities via the collaboration of Interrupt Procedure Instances (IPIs, namely executions of interrupt processing logic). However, due to the complicated concurrency model of WSN programs, the IPIs are interleaved intricately and the program behaviours are hard to predicate from the source codes. Thus, to improve the software quality of WSN programs, it is significant to disentangle the interleaved executions and develop various IPI-based program analysis techniques, including offline and online ones. As the common foundation of those techniques, a generic efficient and real-time algorithm to identify IPIs is urgently desired. However, the existing instance-identification approach cannot satisfy the desires. In this paper, we first formally define the concept of IPI. Next, we propose a generic IPI-identification algorithm, and prove its correctness, real-time and efficiency. We also conduct comparison experiments to illustrate that our algorithm is more efficient than the existing one in terms of both time and space. As the theoretical analyses and empirical studies exhibit, our algorithm provides the groundwork for IPI-based analyses of WSN programs in IoT environment.