Overview of Embedded Rust Operating Systems and Frameworks.

Embedded Operating Systems (OSs) are often developed in the C programming language. Developers justify this choice by the performance that can be achieved, the low memory footprint, and the ease of mapping hardware to software, as well as the strong adoption by industry of this programming language. The downside is that C is prone to security vulnerabilities unknowingly introduced by the software developer. Examples of such vulnerabilities are use-after-free, and buffer overflows. Like C, Rust is a compiled programming language that guarantees memory safety at compile time by adhering to a set of rules. There already exist a few OSs and frameworks that are entirely written in Rust, targeting sensor nodes. In this work, we give an overview of these OSs and frameworks and compare them on the basis of the features they provide, such as application isolation, scheduling, inter-process communication, and networking. Furthermore, we compare the OSs on the basis of the performance they provide, such as cycles and memory usage.

Armed with Faster Crypto: Optimizing Elliptic Curve Cryptography for ARM Processors.

Elliptic curve cryptography is a widely deployed technology for securing digital communication. It is the basis of many cryptographic primitives such as key agreement protocols, digital signatures, and zero-knowledge proofs. Fast elliptic curve cryptography relies on heavily optimised modular arithmetic operations, which are often tailored to specific micro-architectures. In this article, we study and evaluate optimisations of the popular elliptic curve Curve25519 for ARM processors. We specifically target the ARM NEON single instruction, multiple data (SIMD) architecture, which is a popular architecture for modern smartphones. We introduce a novel representation for 128-bit NEON SIMD vectors, optimised for SIMD parallelisation, to accelerate elliptic curve operations significantly. Leveraging this representation, we implement an extended twisted Edwards curve Curve25519 back-end within the popular Rust library "curve25519-dalek". We extensively evaluate our implementation across multiple ARM devices using both cryptographic benchmarks and the benchmark suite available for the Signal protocol. Our findings demonstrate a substantial back-end speed-up of at least 20% for ARM NEON, along with a noteworthy speed improvement of at least 15% for benchmarked Signal functions.

Evaluation of 6LoWPAN Generic Header Compression in the Context of a RPL Network.

The Internet of Things (IoT) facilitates the integration of diverse devices, leading to the formation of networks such as Low-power Wireless Personal Area Networks (LoWPANs). These networks have inherent constraints that make header and payload compression an attractive solution to optimise communication. In this work, we evaluate the performance of Generic Header Compression (6LoWPAN-GHC), defined in RFC 7400, for IEEE 802.15.4-based networks running the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). Through simulation and real-device experiments, we study the impact of 6LoWPAN-GHC on energy consumption and delays and investigate for which scenarios 6LoWPAN-GHC is beneficial. We show that all RPL control packets are compressible by 6LoWPAN-GHC, which reduces their transmission delay and as such their vulnerability to interference. However, for the devices under study transmitting at 250 kbit/s, the energy gain obtained from sending a compressed packet is outweighed by the energy needed to compress it. The use of 6LoWPAN-GHC causes an energy increase of between 2% and 26%, depending on the RPL packet type. When the range is more important than the bandwidth and a sub-GHz band is used at 10 kbit/s, an energy gain of 11% to 29% can be obtained, depending on the type of RPL control packet.

Traffic Aware Scheduler for Time-Slotted Channel-Hopping-Based IPv6 Wireless Sensor Networks.

Wireless sensor networks (WSNs) are becoming increasingly prevalent in numerous fields. Industrial applications and natural-disaster-detection systems need fast and reliable data transmission, and in several cases, they need to be able to cope with changing traffic conditions. Thus, time-slotted channel hopping (TSCH) offers high reliability and efficient power management at the medium access control (MAC) level; TSCH considers two dimensions, time and frequency when allocating communication resources. However, the scheduler, which decides where in time and frequency these communication resources are allotted, is not part of the standard. Orchestra has been proposed as a scheduler which allocates the communication resources based on information collected through the IPv6 routing protocol for low-power and lossy networks (RPL). Orchestra is a very elegant solution, but does not adapt to high traffic. This research aims to build an Orchestra-based scheduler for applications with unpredictable traffic bursts. The implemented scheduler allocates resources based on traffic congestion measured for the children of the root and RPL subtree size of the same nodes. The performance analysis of the proposed scheduler shows lower latency and higher packet delivery ratio (PDR) compared to Orchestra during bursts, with negligible impact outside them.

Flexible and Efficient Security Framework for Many-to-Many Communication in a Publish/Subscribe Architecture.

Message Queuing Telemetry Transport (MQTT) is a lightweight publish/subscribe protocol, which is currently one of the most popular application protocols in Internet of Things (IoT) thanks to its simplicity in use and its scalability. The secured version, MQTTS, which combines MQTT with the Transport Layer Security (TLS) protocol, has several shortcomings. It only offers one-to-one security, supports a limited number of security features and has high computation and communication costs. In this paper, we propose a flexible and lightweight security solution to be integrated in MQTT, addressing many-to-many communication, which reduces the communication overhead by 80% and the computational overhead by 40% for the setup of a secure connection on the client side.

Symmetric-Key-Based Authentication among the Nodes in a Wireless Sensor and Actuator Network.

To enable today's industrial automation, a significant number of sensors and actuators are required. In order to obtain trust and isolate faults in the data collected by this network, protection against authenticity fraud and nonrepudiation is essential. In this paper, we propose a very efficient symmetric-key-based security mechanism to establish authentication and nonrepudiation among all the nodes including the gateway in a distributed cooperative network, without communicating additional security parameters to establish different types of session keys. The solution also offers confidentiality and anonymity in case there are no malicious nodes. If at most one of the nodes is compromised, authentication and nonrepudiation still remain valid. Even if more nodes get compromised, the impact is limited. Therefore, the proposed method drastically differs from the classical group key management schemes, where one compromised node completely breaks the system. The proposed method is mainly based on a hash chain with multiple outputs defined at the gateway and shared with the other nodes in the network.

Time-Slotted Spreading Factor Hopping for Mitigating Blind Spots in LoRa-Based Networks.

It has been demonstrated that LoRa-based wide area networks (WANs) can cover extended areas under harsh propagation conditions. Traditional LoRaWAN solutions based on single-hop access face important drawbacks related to the presence of blind spots. This paper aims to tackle blind spots and performance issues by using a relaying approach. Many researchers investigating multi-hop solutions consider a fixed spreading factor (SF). This simplifies synchronization and association processes, but does not take advantage of the orthogonality between the virtual channels (i.e., frequency, SF) that help to mitigate blind spots. This paper proposes a time-slotted spreading factor hopping (TSSFH) mechanism that combines virtual channels and time slots into a frame structure. Pseudo-random scheduling is used inside blind spots, which simplifies the end-devices' communication process and network organization. The results show how collisions decrease inside blind spots when more communication opportunities become available as more relaying nodes can be listening in different cells (i.e., frequency, SF-offset, time-offset). This has a direct impact on the collision-free packet delivery ratio (PDR) metric, which improves when more listening windows are opened, at the expense of faster battery depletion.

Experimental Analysis of the Application of Serverless Computing to IoT Platforms.

Serverless computing, especially implemented through Function-as-a-Service (FaaS) platforms, has recently been gaining popularity as an application deployment model in which functions are automatically instantiated when called and scaled when needed. When a warm start deployment mode is used, the FaaS platform gives users the perception of constantly available resources. Conversely, when a cold start mode is used, containers running the application's modules are automatically destroyed when the application has been executed. The latter can lead to considerable resource and cost savings. In this paper, we explore the suitability of both modes for deploying Internet of Things (IoT) applications considering a low resources testbed comparable to an edge node. We discuss the implementation and the experimental analysis of an IoT serverless platform that includes typical IoT service elements. A performance study in terms of resource consumption and latency is presented for the warm and cold start deployment mode, and implemented using OpenFaaS, a well-known open-source FaaS framework which allows to test a cold start deployment with precise inactivity time setup thanks to its flexibility. This experimental analysis allows to evaluate the aptness of the two deployment modes under different operating conditions: Exploiting OpenFaaS minimum inactivity time setup, we find that the cold start mode can be convenient in order to save edge nodes limited resources, but only if the data transmission period is significantly higher than the time needed to trigger containers shutdown.

Time Slotted Channel Hopping and ContikiMAC for IPv6 Multicast-Enabled Wireless Sensor Networks.

Smart buildings benefit from IEEE 802.15.4e time slotted channel hopping (TSCH) medium access for creating reliable and power aware wireless sensor and actuator networks (WSANs). As in these networks, sensors are supposed to communicate to each other and with actuators, IPv6 multicast forwarding is seen as a valuable means to reduce traffic. A promising approach to multicast, based on the Routing Protocol for Low Power and Lossy Networks (RPL) is Bidirectional Multicast RPL Forwarding (BMRF). This paper aimed to analyze the performance of BMRF over TSCH. The authors investigated how an adequate TSCH scheduler can help to achieve a requested quality of service (QoS). A theoretical model for the delay and energy consumption of BMRF over TSCH is presented. Next, BMRF's link layer (LL) unicast and LL broadcast forwarding modes were analyzed on restricted and realistic topologies. On topologies with increased interference, BMRF's LL broadcast on top of TSCH causes high energy consumption, mainly because of the amount of energy needed to run the schedule, but it significantly improves packet delivery ratio and delay compared to ContikiMAC under the same conditions. In most cases, the LL unicast was found to outperform the LL broadcast, but the latter can be beneficial to certain applications, especially those sensitive to delays.

XCycles Backprojection Acoustic Super-Resolution.

The computer vision community has paid much attention to the development of visible image super-resolution (SR) using deep neural networks (DNNs) and has achieved impressive results. The advancement of non-visible light sensors, such as acoustic imaging sensors, has attracted much attention, as they allow people to visualize the intensity of sound waves beyond the visible spectrum. However, because of the limitations imposed on acquiring acoustic data, new methods for improving the resolution of the acoustic images are necessary. At this time, there is no acoustic imaging dataset designed for the SR problem. This work proposed a novel backprojection model architecture for the acoustic image super-resolution problem, together with Acoustic Map Imaging VUB-ULB Dataset (AMIVU). The dataset provides large simulated and real captured images at different resolutions. The proposed XCycles BackProjection model (XCBP), in contrast to the feedforward model approach, fully uses the iterative correction procedure in each cycle to reconstruct the residual error correction for the encoded features in both low- and high-resolution space. The proposed approach was evaluated on the dataset and showed high outperformance compared to the classical interpolation operators and to the recent feedforward state-of-the-art models. It also contributed to a drastically reduced sub-sampling error produced during the data acquisition.

An Ultrasonic Multiple-Access Ranging Core Based on Frequency Shift Keying Towards Indoor Localization.

This paper describes a new approach and implementation methodology for indoor ranging based on the time difference of arrival using code division multiple access with ultrasound signals. A novel implementation based on a field programmable gate array using finite impulse response filters and an optimized correlation demodulator implementation for ultrasound orthogonal signals is developed. Orthogonal codes are modulated onto ultrasound signals using frequency shift keying with carrier frequencies of 24.5 kHz and 26 kHz. This implementation enhances the possibilities for real-time, embedded and low-power tracking of several simultaneous transmitters. Due to the high degree of parallelism offered by field programmable gate arrays, up to four transmitters can be tracked simultaneously. The implementation requires at most 30% of the available logic gates of a Spartan-6 XC6SLX45 device and is evaluated on accuracy and precision through several ranging topologies. In the first topology, the distance between one transmitter and one receiver is evaluated. Afterwards, ranging analyses are applied between two simultaneous transmitters and one receiver. Ultimately, the position of the receiver against four transmitters using trilateration is also demonstrated. Results show enhanced distance measurements with distances ranging from a few centimeters up to 17 m, while keeping a centimeter-level accuracy.

SoundCompass: a distributed MEMS microphone array-based sensor for sound source localization.

Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass's hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field.

Active self-testing noise measurement sensors for large-scale environmental sensor networks.

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10.

Using sound-taste correspondences to enhance the subjective value of tasting experiences.

The soundscapes of those places where we eat and drink can influence our perception of taste. Here, we investigated whether contextual sound would enhance the subjective value of a tasting experience. The customers in a chocolate shop were invited to take part in an experiment in which they had to evaluate a chocolate's taste while listening to an auditory stimulus. Four different conditions were presented in a between-participants design. Envisioning a more ecological approach, a pre-recorded piece of popular music and the shop's own soundscape were used as the sonic stimuli. The results revealed that not only did the customers report having a significantly better tasting experience when the sounds were presented as part of the food's identity, but they were also willing to pay significantly more for the experience. The method outlined here paves a new approach to dealing with the design of multisensory tasting experiences, and gastronomic situations.