arXiv subjects

Koen Zandberg

Publications and source records attributed to Koen Zandberg.

7 recordsLinked to original sources

arXiv2025

Ariel OS: An Embedded Rust Operating System for Networked Sensors & Multi-Core Microcontrollers

Large swaths of low-level system software building blocks originally implemented in C/C++ are currently being swapped for equivalent rewrites in Rust, a relatively more secure and dependable programming language. So far, however, no embedded OS in Rust supports multicore preemptive scheduling on microcontrollers. In this paper, we thus fill this gap with a new operating system: Ariel OS. We describe its design, we provide the source code of its implementation, and we perform micro-benchmarks on the main 32-bit microcontroller architectures: ARM Cortex-M, RISC-V and Espressif Xtensa. We show how our scheduler takes advantage of several cores, while incurring only small overhead on single-core hardware. As such, Ariel OS provides a convenient embedded software platform for small networked devices, for both research and industry practitioners.

cs.OS↗

arXiv2024

Model CBOR Serialization for Federated Learning

The typical federated learning workflow requires communication between a central server and a large set of clients synchronizing model parameters between each other. The current frameworks use communication protocols not suitable for resource-constrained devices and are either hard to deploy or require high-throughput links not available on these devices. In this paper, we present a generic message framework using CBOR for communication with existing federated learning frameworks optimised for use with resource-constrained devices and low power and lossy network links. We evaluate the resulting message sizes against JSON serialized messages where compare both with model parameters resulting in optimal and worst case serialization length, and with a real-world LeNet-5 model. Our benchmarks show that with our approach, messages are up to 75 % smaller in size when compared to the JSON alternative.

cs.NI↗

arXiv2023

U-TOE: Universal TinyML On-board Evaluation Toolkit for Low-Power IoT

Results from the TinyML community demonstrate that, it is possible to execute machine learning models directly on the terminals themselves, even if these are small microcontroller-based devices. However, to date, practitioners in the domain lack convenient all-in-one toolkits to help them evaluate the feasibility of executing arbitrary models on arbitrary low-power IoT hardware. To this effect, we present in this paper U-TOE, a universal toolkit we designed to facilitate the task of IoT designers and researchers, by combining functionalities from a low-power embedded OS, a generic model transpiler and compiler, an integrated performance measurement module, and an open-access remote IoT testbed. We provide an open source implementation of U-TOE and we demonstrate its use to experimentally evaluate the performance of various models, on a wide variety of low-power IoT boards, based on popular microcontroller architectures. U-TOE allows easily reproducible and customizable comparative evaluation experiments on a wide variety of IoT hardware all-at-once. The availability of a toolkit such as U-TOE is desirable to accelerate research combining Artificial Intelligence and IoT towards fully exploiting the potential of edge computing.

cs.LG↗

arXiv2022

Femto-Containers: Lightweight Virtualization and Fault Isolation For Small Software Functions on Low-Power IoT Microcontrollers

Low-power operating system runtimes used on IoT microcontrollers typically provide rudimentary APIs, basic connectivity and, sometimes, a (secure) firmware update mechanism. In contrast, on less constrained hardware, networked software has entered the age of serverless, microservices and agility. With a view to bridge this gap, in the paper we design Femto-Containers, a new middleware runtime which can be embedded on heterogeneous low-power IoT devices. Femto-Containers enable the secure deployment, execution and isolation of small virtual software functions on low-power IoT devices, over the network. We implement Femto-Containers, and provide integration in RIOT, a popular open source IoT operating system. We then evaluate the performance of our implementation, which was formally verified for fault-isolation, guaranteeing that RIOT is shielded from logic loaded and executed in a Femto-Container. Our experiments on various popular microcontroller architectures (Arm Cortex-M, ESP32 and RISC-V) show that Femto-Containers offer an attractive trade-off in terms of memory footprint overhead, energy consumption, and security

cs.OS↗

arXiv2021

Femto-Containers: DevOps on Microcontrollers with Lightweight Virtualization & Isolation for IoT Software Modules

Development, deployment and maintenance of networked software has been revolutionized by DevOps, which have become essential to boost system software quality and to enable agile evolution. Meanwhile the Internet of Things (IoT) connects more and more devices which are not covered by DevOps tools: low-power, microcontroller-based devices. In this paper, we contribute to bridge this gap by designing Femto-Containers, a new architecture which enables containerization, virtualization and secure deployment of software modules embedded on microcontrollers over low-power networks. As proof-of-concept, we implemented and evaluated Femto-Containers on popular microcontroller architectures (Arm Cortex-M, ESP32 and RISC-V), using eBPF virtualization, and RIOT, a common operating system in this space. We show that Femto-Containers can virtualize and isolate multiple software modules, executed concurrently, with very small memory footprint overhead (below 10%) and very small startup time (tens of microseconds) compared to native code execution. We show that Femto-Containers can satisfy the constraints of both low-level debug logic inserted in a hot code path, and high-level business logic coded in a variety of common programming languages. Compared to prior work, Femto-Containers thus offer an attractive trade-off in terms of memory footprint, energy consumption, agility and security.

cs.SE↗

arXiv2021

Quantum-Resistant Security for Software Updates on Low-power Networked Embedded Devices

As the Internet of Things (IoT) rolls out today to devices whose lifetime may well exceed a decade, conservative threat models should consider attackers with access to quantum computing power. The SUIT standard (specified by the IETF) defines a security architecture for IoT software updates, standardizing the metadata and the cryptographic tools-namely, digital signatures and hash functions-that guarantee the legitimacy of software updates. While the performance of SUIT has previously been evaluated in the pre-quantum context, it has not yet been studied in a post-quantum context. Taking the open-source implementation of SUIT available in RIOT as a case study, we overview post-quantum considerations, and quantum-resistant digital signatures in particular, focusing on lowpower, microcontroller-based IoT devices which have stringent resource constraints in terms of memory, CPU, and energy consumption. We benchmark a selection of proposed post-quantum signature schemes (LMS, Falcon, and Dilithium) and compare them with current pre-quantum signature schemes (Ed25519 and ECDSA). Our benchmarks are carried out on a variety of IoT hardware including ARM Cortex-M, RISC-V, and Espressif (ESP32), which form the bulk of modern 32-bit microcontroller architectures. We interpret our benchmark results in the context of SUIT, and estimate the real-world impact of post-quantum alternatives for a range of typical software update categories. CCS CONCEPTS $\bullet$ Computer systems organization $\rightarrow$ Embedded systems.

cs.CR↗

arXiv2020

Minimal Virtual Machines on IoT Microcontrollers: The Case of Berkeley Packet Filters with rBPF

Virtual machines (VM) are widely used to host and isolate software modules. However, extremely small memory and low-energy budgets have so far prevented wide use of VMs on typical microcontroller-based IoT devices. In this paper, we explore the potential of two minimal VM approaches on such low-power hardware. We design rBPF, a register-based VM based on extended Berkeley Packet Filters (eBPF). We compare it with a stack-based VM based on WebAssembly (Wasm) adapted for embedded systems. We implement prototypes of each VM, hosted in the IoT operating system RIOT. We perform measurements on commercial off-the-shelf IoT hardware. Unsurprisingly, we observe that both Wasm and rBPF virtual machines yield execution time and memory overhead, compared to not using a VM. We show however that this execution time overhead is tolerable for low-throughput, low-energy IoT devices. We further show that, while using a VM based on Wasm entails doubling the memory budget for a simple networked IoT application using a 6LoWPAN/CoAP stack, using a VM based on rBPF requires only negligible memory overhead (less than 10% more memory). rBPF is thus a promising approach to host small software modules, isolated from OS software, and updatable on-demand, over low-power networks.

cs.NI↗