Out-of-Things Debugging: A Live Debugging Approach for Internet of Things

Abstract

Context Internet of Things (IoT) has become an important kind of distributed systems thanks to the wide-spread of cheap embedded devices equipped with different networking technologies. Although ubiquitous, developing IoT systems remains challenging. Inquiry A recent field study with IoT developers identifies debugging as one of the main challenges faced when developing IoT systems. This comes from the lack of debugging tools taking into account the unique properties of IoT systems such as non-deterministic data, and hardware restricted devices. On the one hand, offline debuggers allow developers to analyse post-failure recorded program information, but impose too much overhead on the devices while generating such information. Furthermore, the analysis process is also time-consuming and might miss contextual information relevant to find the root cause of bugs. On the other hand, online debuggers do allow debugging a program upon a failure while providing contextual information (e.g., stack trace). In particular, remote online debuggers enable debugging of devices without physical access to them. However, they experience debugging interference due to network delays which complicates bug reproducibility, and have limited support for dynamic software updates on remote devices. Approach This paper proposes out-of-things debugging, an online debugging approach especially designed for IoT systems. The debugger is always-on as it ensures constant availability to for instance debug post-deployment situations. Upon a failure or breakpoint, out-of-things debugging moves the state of a deployed application to the developer's machine. Developers can then debug the application locally by applying operations (e.g., step commands) to the retrieved state. Once debugging is finished, developers can commit bug fixes to the device through live update capabilities. Finally, by means of a fine-grained flexible interface for accessing remote resources, developers have full control over the debugging overhead imposed on the device, and the access to device hardware resources (e.g., sensors) needed during local debugging. Knowledge Out-of-things debugging maintains good properties of remote debugging as it does not require physical access to the device to debug it, while reducing debugging interference since there are no network delays on operations (e.g., stepping) issued on the debugger since those happen locally. Furthermore, device resources are only accessed when requested by the user which further mitigates overhead and opens avenues for mocking or simulation of non-accessed resources. Grounding We implemented an out-of-things debugger as an extension to a WebAssembly Virtual Machine and benchmarked its suitability for IoT. In particular, we compared our solution to remote debugging alternatives based on metrics such as network overhead, memory usage, scalability, and usability in production settings. From the benchmarks, we conclude that our debugger exhibits competitive performance in addition to confining overhead without sacri...

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“…It discusses features of WOOD such as capturing, moving and reconstructing debugging sessions, and updating live code. Similar work on "out-of-things" debugging is demonstrated in [65] to recognize the debugging as a major challenge for IoT developers due to unique properties such as non-deterministic data and hardware restrictions. Out-of-things debugging is always-on and works by transferring the state of a failing application to the developer's machine.…”

“…Traditional offline debugging techniques such as logs and dumps are unsuitable for IoT due to their overhead on devices and their inability to capture contextual information to identify the source of bugs. In [64], the authors discussed the extension of the WARDuino IoT platform with an online debugging tool called WOOD, designed to overcome the challenges of debugging IoT applications. Online debugging seems more fitting for IoT, as it allows remote debugging; however, it faces issues such as the probe effect, non-reproducibility, and high latency.…”