Runtime control for application failure prevention in resource-constrained devices

Sammanfattning: In the last decades, there has been a growing interest towards new use cases in the Internet of Things (IoT) domain, such as extended reality glasses, unmanned aerial vehicles (UAVs), and autonomous driving. The technological advancement observed in such scenarios has also been enabled by the increasing capabilities of small form factor devices. Although such devices allow to achieve remarkable computing performance with relatively low energy consumption, these are often used in contexts in which the trade-offs between power consumption and application performance play a key role (e.g., battery powered systems). Furthermore, if such trade-offs are not carefully set, the performance degradation can lead to system failure. The work proposed in this thesis aims at investigating this type of problems, and to propose a runtime model and controller pair based on the joint optimization of the platform and application parameters to reduce the likelihood of system failure. The proposed architecture is evaluated in a UAV emulated environment, in which the used platform embeds hardware features comparable to the ones of a drone, while the localization and mapping application executed on such device makes use of real-world visual-inertial datasets. The proposed runtime model-controller solution relies on the monitoring of the platform CPU peaks for identifying application failure. It has also been empirically demonstrated that the model-controller can substantially decrease the number of failures and, in specific scenarios, improve localization accuracy and power consumption even compared to the optimal static parameter configurations. Moreover, the solution has been proven to be simple and generalizable in scenarios characterized by different levels of concurrency, and in the datasets tested.