arXiv subjects

Leandro Lanzieri

Publications and source records attributed to Leandro Lanzieri.

7 recordsLinked to original sources

arXiv2026

Ageing Monitoring for Commercial Microcontrollers Based on Timing Windows

Microcontrollers are increasingly present in embedded deployments and dependable systems, for which malfunctions due to hardware ageing can have severe impact. The lack of deployable techniques for ageing monitoring on these devices has spread the application of guard bands to prevent timing errors due to degradation. Applying this static technique can limit performance and lead to sudden failures as devices age. In this paper, we follow a software-based self-testing approach to design monitoring of hardware degradation for microcontrollers. Deployable in the field, our technique leverages timing windows of variable lengths to determine the maximum operational frequency of the devices. We empirically validate the method on real hardware and find that it consistently detects temperature-induced degradations in maximum operating frequency of up to 13.79 % across devices for 60 {\deg}C temperature increase.

cs.AR↗

arXiv2024

Switching Frequency as FPGA Monitor: Studying Degradation and Ageing Prognosis at Large Scale

The growing deployment of unhardened embedded devices in critical systems demands the monitoring of hardware ageing as part of predictive maintenance. In this paper, we study degradation on a large deployment of 298 naturally aged FPGAs operating in the European XFEL particle accelerator. We base our statistical analyses on 280 days of in-field measurements and find a generalized and continuous degradation of the switching frequency across all devices with a median value of 0.064%. The large scale of this study allows us to localize areas of the deployed FPGAs that are highly impacted by degradation. Moreover, by training machine learning models on the collected data, we are able to forecast future trends of frequency degradation with horizons of 60 days and relative errors as little as 0.002% over an evaluation period of 100 days.

cs.AR↗

arXiv2024

Studying the Degradation of Propagation Delay on FPGAs at the European XFEL

An increasing number of unhardened commercial-off-the-shelf embedded devices are deployed under harsh operating conditions and in highly-dependable systems. Due to the mechanisms of hardware degradation that affect these devices, ageing detection and monitoring are crucial to prevent critical failures. In this paper, we empirically study the propagation delay of 298 naturally-aged FPGA devices that are deployed in the European XFEL particle accelerator. Based on in-field measurements, we find that operational devices show significantly slower switching frequencies than unused chips, and that increased gamma and neutron radiation doses correlate with increased hardware degradation. Furthermore, we demonstrate the feasibility of developing machine learning models that estimate the switching frequencies of the devices based on historical and environmental data.

cs.AR↗

arXiv2023

Ageing Analysis of Embedded SRAM on a Large-Scale Testbed Using Machine Learning

Ageing detection and failure prediction are essential in many Internet of Things (IoT) deployments, which operate huge quantities of embedded devices unattended in the field for years. In this paper, we present a large-scale empirical analysis of natural SRAM wear-out using 154 boards from a general-purpose testbed. Starting from SRAM initialization bias, which each node can easily collect at startup, we apply various metrics for feature extraction and experiment with common machine learning methods to predict the age of operation for this node. Our findings indicate that even though ageing impacts are subtle, our indicators can well estimate usage times with an $R^2$ score of 0.77 and a mean error of 24% using regressors, and with an F1 score above 0.6 for classifiers applying a six-months resolution.

cs.AR↗

arXiv2023

A Review of Techniques for Ageing Detection and Monitoring on Embedded Systems

Embedded digital devices are progressively deployed in dependable or safety-critical systems. These devices undergo significant hardware ageing, particularly in harsh environments. This increases their likelihood of failure. It is crucial to understand ageing processes and to detect hardware degradation early for guaranteeing system dependability. In this survey, we review the core ageing mechanisms, identify and categorize general working principles of ageing detection and monitoring techniques for Commercial-Off-The-Shelf (COTS) components that are prevalent in embedded systems: Field Programmable Gate Arrays (FPGAs), microcontrollers, System-on-Chips (SoCs), and their power supplies. From our review, we find that online techniques are more widely applied on FPGAs than on other components, and see a rising trend towards machine learning application for analysing hardware ageing. Based on the reviewed literature, we identify research opportunities and potential directions of interest in the field. With this work, we intend to facilitate future research by systematically presenting all main approaches in a concise way.

cs.AR↗

arXiv2022

Usable Security for an IoT OS: Integrating the Zoo of Embedded Crypto Components Below a Common API

IoT devices differ widely in crypto-supporting hardware, ranging from no hardware support to powerful accelerators supporting numerous of operations including protected key storage. An operating system should provide uniform access to these heterogeneous hardware features, which is a particular challenge in the resource constrained IoT. Effective security is tied to the usability of cryptographic interfaces. A thoughtful API design is challenging, and it is beneficial to re-use such an interface and to share the knowledge of programming embedded security widely. In this paper, we integrate an emerging cryptographic interface into usable system-level calls for the IoT operating system RIOT, which runs on more than 240 platforms. This interface supports ID-based key handling to access key material in protected storage without exposing it to anyone. Our design foresees hardware acceleration on all available variants; our implementation integrates diverse cryptographic hardware and software backends via the uniform interface. Our performance measurements show that the overhead of the uniform API with integrated key management is negligible compared to the individual crypto operation. Our approach enhances the usability, portability, and flexibility of cryptographic support in the IoT.

cs.CR↗

arXiv2022

Secure and Authorized Client-to-Client Communication for LwM2M

Constrained devices on the Internet of Things (IoT) continuously produce and consume data. LwM2M manages millions of these devices in a server-centric architecture, which challenges edge networks with expensive uplinks and time-sensitive use cases. In this paper, we contribute two LwM2M extensions to enable client-to-client (C2C) communication: (i) an authorization mechanism for clients, and (ii) an extended management interface to allow secure C2C access to resources. We analyse the security properties of the proposed extensions and show that they are compliant with LwM2M security requirements. Our performance evaluation on off-the-shelf IoT hardware shows that C2C communication outperforms server-centric deployments. First, LwM2M deployments with edge C2C communication yield a ~90% faster notification delivery and ~8x greater throughput compared to common server-centric scenarios, while keeping a small memory overhead of ~8%. Second, in server-centric communication, the delivery rate degrades when resource update intervals drop below 100 ms.

cs.NI↗