EDHOC is a lightweight authenticated key exchange protocol designed for constrained IoT devices. It currently supports asymmetric authentication, either using digital signatures or static Diffie-Hellman (DH) keys. Since many IoT deployments rely on Pre-Shared Keys (PSK) for authentication, a new PSK-based authentication method (EDHOC-PSK) is currently under standardization. This paper presents a symbolic analysis EDHOC-PSK (draft version 06) using SAPIC+, which compiles a single formal specification into multiple state-of-the-art verification tools, including Tamarin and ProVerif. Our model extends the typical Dolev-Yao (DY) adversary with additional capabilities, including leakage of ephemeral secrets, leakage of the long-term Pre-Shared Key leakage of the session key and a discrete-logarithm oracle. We verify the confidentiality, authentication, and key-agreement properties stated in the draft, and we refine the specification of identity protection by distinguishing anonymity and unlinkability. We show that EDHOC-PSK achieves anonymity for both parties against active attackers, while unlinkability holds only for the Initiator under passive attackers. Finally, we analyze a post-quantum Store-Now-Decrypt-Later (SNDL) adversary and find that all proven properties remain intact except Perfect Forward Secrecy (PFS), which cannot be preserved once DH secrets are recoverable.

Large-scale deployments of resource-constrained embedded devices require lightweight, self-contained hardware roots of trust that avoid long-term secret storage. Physically Unclonable Functions (PUFs) enable secure key extraction from intrinsic hardware variations without storing keys in non-volatile memory (NVM). SRAM PUFs leverage existing Static Random Access Memory (SRAM), but face reliability issues due to environmental noise. Existing solutions rely on complex error correction codes with NVM-stored helper data, or extensive SRAM measurements to pre-select stable cells. Eliminating NVM storage for helper data mitigates information leakage risks and manufacturing costs, offering a crucial benefit for resource-constrained devices lacking NVM. This paper presents a novel approach for stabilizing SRAM PUFs without NVM-stored helper data, using a simple decoder and few SRAM measurements, at the cost of increased SRAM size. We generate consistent On-Demand Helper Data (ODHD) temporarily stored in volatile memory and validate our method experimentally on real hardware. ODHD exposes a flexible trade-off between enrollment consistency, regeneration reliability, and SRAM size by varying a single enrollment threshold, a degree of freedom absent in the fixed Dark Bit approach. At the threshold-free operating point, ODHD achieves a key error rate of 8.2% for a 16-bit output, more than six times lower than Dark Bit’s 51.5%, using only 6 bytes of SRAM per 16-bit output, when ≈ 500 power cycles are used at every key derivation.

6TiSCH is a protocol stack designed for industrial IoT applications, offering high reliability and ultra-low power consumption through Time-Slotted Channel Hopping (TSCH). A fundamental requirement of 6TiSCH is to ensure stable and efficient network synchronization, especially during the joining phase when many devices are attempting to connect. The standard provides a wide range of synchronization configurations to accommodate diverse deployment environments. However, it does not provide guidelines for network administrators on how to select appropriate configurations for different applications. In addition, existing models and approaches primarily focus on optimizing the initial synchronization phase, without discussing how synchronization is maintained afterward. This paper introduces a synchronization model for 6TiSCH networks to fill these gaps, enabling administrators to easily evaluate synchronization performance across different configurations and adapt the following five parameters to specific network conditions: Enhanced Beacon (EB) interval, Keep-Alive (KA) period, number of neighbors, link quality, and slotframe duration. By comparing the model’s predictions with detailed synchronization process simulations, we demonstrate that our model achieves 92.3% accuracy within a ±10-second margin when predicting synchronization time in low-to medium-density network scenarios. We conducted an exhaustive simulation campaign to evaluate the model’s performance in predicting synchronization time, packet count, and energy consumption, using 3,125 network settings with 100 runs per setting. Based on the analysis, we provide recommended settings for EB interval and KA period under different traffic loads, as indicated by slotframe durations. These recommendations ensure reliable synchronization during the joining phase across diverse network deployments and environmental conditions.

The proliferation of Internet-of-Things (IoT) devices in critical infrastructure requires robust security mechanisms to verify device integrity and trustworthiness. Remote Attestation (RA) is a security mechanism for validating the software and hardware state of remote devices. Existing RA solutions for resource-constrained IoT devices lack comprehensive frameworks for secure attestation channels and focus primarily on local evidence generation without addressing end-to-end security. This paper introduces M-AuRA, a lightweight RA solution that fills these gaps by leveraging the newly standardized Ephemeral Diffie-Hellman over COSE (EDHOC) protocol. M-AuRA seamlessly integrates attestation with authentication, enabling both unilateral and mutual attestation modes while maintaining minimal resource overhead. Our framework specifies how to transport existing attestation mechanisms in parallel with secure communication establishment, providing a complete end-to-end security solution for IoT deployments. We demonstrate M-AuRA’s practicality through implementation on the nRF5340 microcontroller running at 64 MHz, evaluating performance across both software and hardware cryptographic back-ends. In mutual attestation mode, our implementation uses only 4,692 B RAM and 19,350 B flash memory, occupying 0.9% and 1.85% of available nRF5340 resources, respectively. The four-message EDHOC exchange (45 B, 65 B, 177 B and 120 B) enables mutual trustworthiness verification in 10.46 s using a software-based cryptographic back-end, or only 0.43 s with hardware acceleration, consuming 171.43 mC and 7.97 mC of charge, respectively.

Industrial low-power wireless sensor networks demand high reliability and adaptability to cope with dynamic environments and evolving network requirements. While the 6TiSCH protocol stack provides reliable low-power communication, the CoAP Management Interface (CORECONF) for runtime management remains underutilized. In this work, we implement CORECONF and introduce clustering as a practical use case. We implement a cluster formation mechanism aligned with the Routing Protocol for Low-Power and Lossy Networks (RPL) and adjust the TSCH channel-hopping sequence within the established clusters. Two use cases are presented. First, CORECONF is used to mitigate external Wi-Fi interference by forming a cluster with a modified channel set that excludes the affected frequencies. Second, CORECONF is employed to create a priority cluster of sensor nodes that require higher reliability and reduced latency, such as those monitoring critical infrastructure in industrial settings. Simulation results show significant improvements in latency, while practical experiments demonstrate a reduction in overall network charge consumption from approximately 50 mC per hour to 23 mC per hour, by adapting the channel set within the interference-affected cluster.

Swarm robotics focuses on designing and coordinating large groups of relatively simple robots to perform tasks in a decentralised and collective manner. The swarm provides a resilient and flexible solution for many applications. However, contemporary swarm robots have a significant power problem in that secondary (i.e. rechargeable) batteries are slow to charge and offer lifetimes of only a few years, increasing maintenance costs and pollution due to battery replacement. We imagine a different future, wherein battery-free robots powered by supercapacitors can be recharged in seconds, offer long-life autonomous operation and can rapidly pass charge between one another using trophallaxis. In pursuit of this vision, we contribute the CapBot, a battery-free swarm robot equipped with Mecanum wheels, a Cortex M4F application processor and Bluetooth Low Energy networking. The CapBot fully recharges in 16 s, offers 51 min of autonomous operation at top speed, and can transfer up to 50 % of its available charge to a peer via trophallaxis in under 20 s. The CapBot is fully open source and all software and hardware source is available online.

IEEE 802.15.4 is the core of multiple industrial standards such as WirelessHART, ISA100.11a, and 6TiSCH. It provides ultra-low-power operation and high reliability for battery-powered devices requiring a 5-10 year lifetime. However, due to its narrow frequency bandwidth, it is rarely used as a wireless ranging technique. Its low resolution in the time domain makes it difficult to precisely determine the arrival time of the signal, which is essential for Time-of-Flight ranging. Emerging approaches, such as WiFi fingerprinting, show promising localization performance by using learning methods to find the pattern mapping between signal characteristics and positions.This paper explores the potential of using learning approaches over IEEE 802.15.4 radios for ranging, based on RSSI and Round Trip Timing (RTT) samples. As a preprocessing step, groups of RTT samples are fed into a Gaussian Mixture Model (GMM), extracting two sets of features: the mean, variance, and weight of two distributions (line-of-sight and non-line-of-sight). Together with the mean and variance of the Received Signal Strength Indicator (RSSI) and RTT samples, 10 features are used as the input to a multilayer perceptron network to predict the distance between the requester and reflector.The approach has been evaluated using IEEE 802.15.4 devices in three different scenarios: an empty football field, an underground parking lot, and an office area. The results show that with dedicated models trained using datasets collected from each scenario, the ranging prediction errors of 0.25 meters, 0.42 meters, and 0.58 meters at 80% probability are achieved in these three scenarios, respectively. With a single model trained using a combined dataset from all three scenarios, prediction errors of 0.41 meters, 0.60 meters, and 0.97 meters at 80% probability are achieved.

Low-power wireless networks are increasingly deployed in Industrial Internet of Things (IIoT) environments to ensure reliable and secure operation of machinery. One of the key requirements for these networks is reliability, which hinges on the ability to continuously assess the network’s health a challenge addressed by Application Performance Monitoring (APM). Within APM, transmitting performance metrics, particularly in low-power networks, must be efficient to preserve battery life. This paper addresses various APM approaches, including In-band Network Telemetry (INT), which leverages multi-hop topologies to append telemetry data to existing packets. We propose HyPM, a novel hybrid method that combines active monitoring with INT to meet user requirements for telemetry scope and frequency while improving energy efficiency by $31 \%$. Simulations in the Contiki-NG network simulator demonstrate the superiority of HyPM in balancing energy consumption and data reporting accuracy.

Remote Attestation (RA) is a security process that verifies the integrity and trustworthiness of a remote device’s software and hardware. While RA for high-end devices is well-developed, RA in constrained IoT environments remains incomplete. Existing embedded RA mechanisms focus on local evidence generation and verification, but lack a complete process that includes a secure attestation channel. This paper introduces AuRA, a lightweight RA solution that builds upon the newly standardized Ephemeral Diffie-Hellman over COSE (EDHOC) protocol. AuRA specifies how to transport existing attestation mechanisms in parallel with network authentication. We evaluate AuRA on the nRF5340 microcontroller running at $\mathbf{6 4 ~ M H z}$. This implementation has a memory footprint of 6,665 B of RAM and 17,163 B of flash. The device completes Remote Attestation by exchanging three EDHOC messages with a verifier entity, of sizes $42 \mathrm{~B}, 59 \mathrm{~B}$ and 223 B. This allows the device to prove that it is running the right hardware and software in only 5.51 s, consuming as little as 88 mC of charge.

Bluetooth Low Energy and IEEE 802.15.4 are commonly used wireless communication protocols in IoT applications. Both operate in the 2.4 GHz ISM band, where their coexistence can lead to interference. We study the bit error rate (BER) under controlled timed interferences within the physical payload, varying interference power and frequency offsets. Measurements with a co-located software-defined-radio antenna are captured and shown to validate the experimental setup. IEEE 802.15.4 proves more robust to BLE interference than vice versa, consistent with results in literature. Interference at lower relative frequencies is found to have a greater impact on BER. Controlled interference causes persistent bit errors after it ends, suggesting receiver desynchronisation.

Industrial low-power wireless networks exhibit unique requirements in terms of reliability, battery lifetime and security. Time Synchronized Channel Hopping is a networking technique created to address these needs, which was standardized by working group IETF 6TiSCH. Analog Devices’ SmartMesh product lines have been the best-in-class TSCH implementation, exhibiting over 99.999% wire-like end-to-end reliability, a decade of battery lifetime, and certified security. With over 100,000 networks deployed, SmartMesh plays a market-leading role. Today, SmartMesh runs on the LTC5800, and often requires customers to drive it from a second external micro-controller, which increases cost. This paper introduces a port of SmartMesh to the MAX32655, a dual-core microcontroller and radio System on Chip: the RISC-V core runs the communication stack, the ARM Cortex-M4 core is left available to the customer. We show how that ARM Cortex-M4 core can run a MicroPython interpreter for faster prototyping and time-to-market. A simple script, designed to transmit packets over a SmartMesh network using MicroPython, requires only an additional 6 kB of RAM. Furthermore, by compiling this script into byte code, the processing time can be reduced to a quarter of its original duration.

Time synchronization is an important building block for deterministic low-power wireless networks such as IETF 6TiSCH. The synchronized nature of this class of networks can be used by the application running on it, including to start/stop actions in a coordinated fashion across different nodes. This is called "orchestration" in 6TiSCH parlance. This demo proposes to interpret this term literally, by turning each low-power wireless device into an embedded musician. The network of 20 of these wireless musicians deployed across the demo space becomes an embedded orchestra, which plays John Williams’ iconic orchestral arrangement of the Star Wars anthem.

SRAM Physically Unclonable Functions (PUFs) derive secret keys from start-up values for inherent security benefits but suffer from reliability issues due to bit flipping. We introduce the Threshold-based Majority Voting Scheme (TMVS), a lightweight method that eliminates noise and mitigates bias in SRAM PUFs while retaining the simplicity of majority voting decoders used by repetition codes, without the significant entropy loss that repetition codes incur under biased responses. TMVS runs entirely in software, requires no cell-level bit-error rate qualification or SRAM redesign, and avoids the complex decoders of heavy error correcting codes. We derive closed-form expressions for decoding-error probability and expected memory, validate them on experimental data, and present a security analysis that provides exact formulas for min-entropy and secrecy leakage due to helper data and bias, identifying conditions under which TMVS achieves zero secrecy leakage. On a large public dataset, TMVS shows near-zero cross-chip secrecy leakage and preserves average conditional min-entropy above 1 bit despite biased, spatially correlated SRAM statistics. Compared with prior work, TMVS offers the smallest decoding complexity at the cost of a larger PUF size. In a representative configuration, TMVS generates a 128-bit key with failure probability 9.15 · 10−6and zero secrecy leakage at a bit-flip probability of 10%, requiring only ∼ 248k clock cycles on a 32-bit ARM Cortex-M0. These results show that TMVS is practical and implementation-friendly for resource-constrained, low-power devices.

Bit errors in wireless communication predominantly stem from external interference as well as from multipath fading and attenuation. In order to tackle these harmful influences, the IEEE 802.15.4 standard includes time slotted channel hopping. We have collected packets containing bit errors from 200,000 packets generated in two different testbeds. We show that the channels used in IEEE 802.15.4 exhibit different error patterns typical for either external interference or multi-path fading and attenuation. These insights allow to detect, classify and quantify the presence of these phenomena. Furthermore, practical use cases for exploiting the knowledge on error patterns on a per-channel basis are presented. We propose to choose Forward Error Correction on a per channel basis and provide reference values in terms of code error correcting capability required to recover from 50% of the occurred packet errors on certain channels.

Reducing the number of bytes transmitted by a low-power wireless device greatly reduces its power consumption. While header compression is a well-studied topic with solutions such as SCHC that are well-established standards, very little work exists on compressing the payload. This is all the stranger that the payload typically contains more bytes than the headers. This demonstration introduces Dixy, a payload compression technique which can be used alongside SCHC. We implement SCHC and Dixy on the nRF52840, a popular micro-controller. We have them compress packets collected from a real-world deployment by startup company Falco. We show how the resulting joint header and payload compression reduces the number of bytes exchanged between two boards by 74%. The demonstration allows visitors to understand SCHC and Dixy, trigger packets being compressed and transmitted, and observe the number of bytes and the charge consumed with enabling header and/or payload compression.

Authenticated key exchange protocols play a crucial role in the communication security stack of an Internet-of-Things (IoT) device: they authenticate the communicating parties and establish a shared symmetric secret between them. Following a large debate in the community, the Internet Engineering Task Force (IETF) has recently standardized a new protocol called EDHOC for authenticated key exchange targeting IoT environments. The EDHOC protocol performs a compact Diffie-Hellman key exchange handshake, requiring several times less bytes-over-the-air than the de-facto solution used in the Internet, the (D)TLS protocol. In this paper, we study how this reduction in message size correlates with the usage of other scarce resources in IoT environments: time, energy, and memory. We evaluate EDHOC and DTLS with different authentication configurations over two IoT radio technologies. First, we measure the EDHOC and DTLS handshakes on constrained hardware over an IEEE 802.15.4 radio. We observe that EDHOC achieves ×6 to × 14 reduction in packet sizes, × 1.44 improvement in handshake duration and ×2.79 reduction in energy consumed. Next, we simulate time on air on LoRaWAN networks and find that, in the most restrictive configuration (SF = 12), DTLS uses at least × 7 more time on air than EDHOC. Finally, we measure flash memory and RAM usage, with the EDHOC implementation achieving a ×4 reduction in both.

This article presents a novel centrality-driven gateway designation framework for the improved real-time performance of low-power wireless sensor networks (WSNs) at system design time. We target time-synchronized channel hopping (TSCH) WSNs with centralized network management and multiple gateways with the objective of enhancing traffic schedulability by design . To this aim, we propose a novel network centrality metric termed minimal-overlap centrality that characterizes the overall number of path overlaps between all the active flows in the network when a given node is selected as gateway. The metric is used as a gateway designation criterion to elect as a gateway the node leading to the minimal number of overlaps. The method is then extended to multiple gateways with the aid of the unsupervised learning method of spectral clustering . Concretely, after a given number of clusters are identified, we use the new metric at each cluster to designate as cluster gateway the node with the least overall number of overlaps. Extensive simulations with random topologies under centralized earliest-deadline-first (EDF) scheduling and shortest-path routing suggest our approach is dominant over traditional centrality metrics from social network analysis, namely, eigenvector , closeness , betweenness , and degree . Notably, our approach reduces by up to 40% the worst-case end-to-end deadline misses achieved by classical centrality-driven gateway designation methods.

In this work we propose and demonstrate a protocol for a time synchronized channel hopping mesh network for wireless transceivers that use exclusively imprecise and inaccurate on-chip oscillators. This protocol is built on an IEEE 802.15.4 physical layer radio that enables interoperability with protocols such as 6TiSCH or Thread. A calibration-bootstrapped multi-hop mesh network is demonstrated with a single crystal-enabled node acting as the root. The protocol is designed to create a multi-hop mesh while compensating noisy and drifting oscillators and timers. With a 4 s synchronization period, an experimental implementation of the network maintains, in the worst case, 1.8 ms 3σ absolute time synchronization and 820 µs 3σ hop-to-hop synchronization across four hops, under ambient environmental conditions. The resistance to environmental variation is tested by varying one node's supply voltage. With time and frequency feedback from received packets, the node maintains this synchronization with a supply variation of 2.5 mV/s, which is equivalent to a temperature variation of 10°C/min with a packet rate of 0.5 Hz.

Satellite technology offers exciting new opportunities for IoT applications. This poster shows the performance one may expect using Kinéis – a leading operator – as a representative example. We use an implementation we provide as open-source for repeatability, and measure an end-to-end latency of 45 min, a battery lifetime of 1,000 packet when using a pair of AA batteries, and an end-to-end reliability of 23%/54%/99% when using 1/10/18 repetitions.

A growing range of networked embedded devices are moving away from batteries and towards super-capacitor charge storage. However, mobile robots remain largely dependent upon batteries with slow recharge cycles and limited lifetimes. In this demonstration paper, we introduce a novel battery-free platform for swarm robotics which features: 24 minutes of operation running at its top speed of 1.24 km/h, a carrying capacity of over 2.5kg, full recharge cycles of under 12 seconds and rapid peer-to-peer charge transfer or trophallaxis in the field. This is supported by an nRF52840 Cortex-M4F equipped with BLE/ANT/802.15.4 transceiver. Notably, while the autonomy of FreeBots is limited compared to battery-powered robots, their operational vs charging duty-cycle is significantly higher at over 99%.

The single-chip micro-mote (SC$\mu \text{M}$) is a$2\times 3$mm2single-chip crystal-free mote-on-chip. SC$\mu \text{M}$implements the IEEE802.15.4 and BLE standards and can communicate with off-the-shelf radios compliant to those standards. SC$\mu \text{M}$exclusively uses on-chip oscillators, including a 2.4-GHz LC oscillator to synthesize the communication frequency, and a 2-MHz RC oscillator to clock the chip rate. The challenge is that the LC oscillator drifts at 2100 ppm over a temperature range of 45 °C, far from the 40-ppm maximum drift mandated by the IEEE802.15.4 standard. While one-shot calibration is possible, any temperature change causes IEEE802.15.4 communication to fail. This article describes a continuous calibration approach for SC$\mu \text{M}$to adapt the tuning of its oscillators as the temperature changes. Experimental results show that it allows SC$\mu \text{M}$to keep communicating with an IEEE802.15.4 radio even under the extreme condition of using a hair dryer to heat up the chip at 3 °C/min. Under these conditions, the drift of the LC oscillator stays within the ±40-ppm limit over 94% of the time. Similarly, the drift of the 2-MHz RC oscillator stays within ±1000 ppm limit 99.98% of the time.

Data gathering systems in the Industrial IoT require an end-to-end latency as low as 1 s with coverage of a few hundred meters. The 6TiSCH standard is well suited for these types of applications. A 6TiSCH network is a multihop wireless IPv6 network which uses time-slotted channel hopping (TSCH). TSCH is a medium access mode of IEEE802.15.4 which provides deterministic properties, and increases robustness against external interference and multipath fading. A key component of TSCH is its scheduling function that builds the communication schedule, which greatly impacts network performance. Although there are several proposed TSCH scheduling solutions in the literature, most of them are not directly applicable to 6TiSCH for real-world deployments because they fail to take into consideration the dynamics of a network. Some of them assume afixedrouting topology, which does not match 6TiSCH where the routing topology dynamically changes with the radio environment. In this article, we propose a full-featured 6TiSCH scheduling function called YSF, that autonomously takes into account all aspects of network dynamics, including the network formation phase and parent switching. YSF aims at minimizing latency and maximizing reliability for data gathering applications. We evaluate YSF by simulation, and compare it to MSF, the state-of-art scheduling function being standardized by the IETF 6TiSCH working group.

Historically, the study of mountain hydrology and the water cycle has been largely observational, with meteorological forcing and hydrological variables extrapolated from a few infrequent manual measurements. Recent developments in the Internet of Things (IoT) technology are revolutionizing the field of mountain hydrology. Low-power wireless sensor networks can now generate denser data in real time and for a fraction of the cost of labor-intensive manual measurement campaigns. The American River Hydrological Observatory (ARHO) project has deployed 13 low-power wireless IoT networks throughout the American River basin to monitor California’s snowpack. The networks feature a total of 945 environmental sensors, each reporting a reading every 15 min. The data reported is made available to the scientific community minutes after it is generated. This article provides an in-depth technical description of the ARHO project. It details the requirements and different technical options, describes the technology deployed today, and discusses the challenges associated with large-scale environmental monitoring in extreme conditions.

One of the most fundamental capabilities of swarm robotics is their ability to cooperate. This implies that swarm robots must exchange information with each other or with a centralized controller. However, this communication is often assumed to be perfect, an assumption that does not reflect real-world conditions, where impairments can affect the Packet Delivery Ratio (PDR) over wireless links. One essential application of swarm robotic cooperation is exploration and mapping in a timely and accurate manner. This paper studies how communication impairments can have a drastic impact on the performance of robotic swarms in critical missions such as exploration. We use an improved version of the Atlas algorithm to simulate the effect of various PDRs on the exploration mission execution performance, with the key indicator being mapping completion time. Our results show that the time it takes to complete area exploration increases exponentially as the PDR decreases linearly. Based on our results, we emphasise the importance of considering methods that minimize the delay caused by lossy communication when designing and implementing algorithms for robotic swarm exploration.

Wireless sensor networking is a key enabler of Industrial IoT. IETF (Internet Engineering Task Force) has standardized a protocol suite called 6TiSCH (IPv6 over the TSCH mode of IEEE802.15.4e). 6TiSCH builds an IPv6 multi-hop wireless network with the IEEE802.15.4 radio, which achieves low energy consumption and high reliability. Although network formation time is one of key performance indicators of wireless sensor networks, it has not been studied well with 6TiSCH standard protocols such as MSF (6TiSCH Minimal Scheduling Function) and CoJP (Constrained Join Protocol). In this paper, we propose a scheduling function called SF-Fastboot which shortens network formation time of 6TiSCH. We evaluate SF-Fastboot by simulation comparing with MSF, the state-of-the-art scheduling function. The simulation shows SF-Fastboot reduces network formation time by 41 % – 80 %.

We envision swarms of mm-scale micro-robots to be able to carry out critical missions such as exploration and mapping for hazard detection and search and rescue. These missions share the need to reach full coverage of the explorable space and build a complete map of the environment. To minimize completion time, robots in the swarm must be able to exchange information about the environment with each other. However, communication between swarm members is often assumed to be perfect, an assumption that does not reflect real-world conditions, where impairments can affect the Packet Delivery Ratio (PDR) of the wireless links. This paper studies how communication impairments can have a drastic impact on the performance of a robotic swarm. We present Atlas 2.0, an exploration algorithm that natively takes packet loss into account. We simulate the effect of various PDRs on robotic swarm exploration and mapping in three different scenarios. Our results show that the time it takes to complete the mapping mission increases significantly as the PDR decreases: on average, halving the PDR triples the time it takes to complete mapping. We emphasise the importance of considering methods to compensate for the delay caused by lossy communication when designing and implementing algorithms for robotics swarm coordination.

The single-chip micro mote (SC$\mu \text{M}$) is a crystal-free single-chip mote that brings us one step closer to the Smart Dust vision, in particular, as it can communicate with off-the-shelf IEEE802.15.4 and Bluetooth low energy devices. However, before it can be part of such networks, the crystal-free SC$\mu \text{M}$chip needs to be able to accurately tune its communication frequency to synchronize to the network. This is a challenge since its onboard RC and LC-based resonating circuits have a drift rate that can be three orders of magnitude worse than crystal-based oscillators typically used in today’s radios. This article introduces QuickCal, a solution that allows an SC$\mu \text{M}$chip to self-calibrate against off-the-shelf devices dedicated to assisting with its calibration. We show that an SC$\mu \text{M}$chip can self-calibrate against this QuickCal Box in fewer than 3 min. We further validate that once it has self-calibrated, an SC$\mu \text{M}$chip can reliably communicate with off-the-shelf IEEE802.15.4 devices. Finally, we demonstrate a heterogeneous network—composed of an SC$\mu \text{M}$chip and an OpenMote device—implementing a full 6TiSCH Industrial IoT protocol stack, which uses time synchronization and channel hopping. This is the first time that a crystal-free radio is participating in a channel-hopping-enabled TSCH network.

Existing methods for wireless-sensor network (WSN) topology optimization employ simplifying assumptions of a fixed communication radius between network nodes, which is ill-suited for IoT networks deployed in complex terrain. This article proposes a data-driven approach to WSN topology optimization, employing a Bayesian link classifier trained on LIDAR-derived terrain characteristics and anin-situsurvey of link quality. The classifier is trained to predict where good network links (packet-delivery ratio, PDR>0.5) are likely to form in a region given complex terrain attributes. Then, given numerous candidate wireless node placements throughout the domain, the classifier is used to construct an undirected weighted graph of the potential connectivity across the domain. Edge weights in the connectivity graph are proportional to the probability of forming a good link between the nodes. A novel modified cycle-union (MCyU) algorithm for generating a 2-vertex-connected, Steiner minimal network is then applied to the undirected weighted graph of potential network element placements. This ensures a survivable network design, while maximizing the probability of good links within the final network. The total number and spatial distribution of network elements produced by the algorithm is compared to an existing WSN, deployed for environmental monitoring in remote regions. In addition, the MCyU algorithm has been evaluated in three graph test cases to compare with state-of-the-art solutions, where MCyU outperforms in terms of weight minimization and computation time.

Exploration and mapping is a fundamental capability of a swarm of robots: robots enter an unknown area, explore it, and collectively build a map of it. This capability is important regardless of whether the robots are crawling, flying, or swimming. Existing exploration and mapping algorithms tend to either be inefficient, or rely on having a dense swarm of robots. This paper introduces Atlas, an exploration and mapping algorithm for sparse swarms of robots, which completes a full exploration even in the extreme case of a single robot. We develop an open-source simulator and show that Atlas outperforms the state-of-the-art in terms of exploration speed and completeness of the resulting map.

Short development cycles, application-field diversity, and requirements on network size or reliability put an ever increasing strain on Internet of Things (IoT) application developers. Real-time embedded operating systems (RTOS) aim to provide a key set of features, abstractions and services that enable faster development. To fulfill the promise of wire-like communication reliability, wireless standards such as WirelessHART, ISA100.11a and 6TiSCH have been developed and are used in the industry. Keeping these networks synchronized requires precise timing information from the underlying hardware. However, the hardware abstractions of an RTOS do come with an overhead, and the question arises on how these abstractions impact the performance of a complex network stack. To study this, we integrated Open-WSN, a standards-compliant open-source implementation of the 6TiSCH network stack, with RIOT, a prominent open-source RTOS. We compare the minimalistic "bare metal" approach of OpenWSN with RIOT's full-fledged RTOS environment. We study the impact on network performance, power consumption and real-time application properties. On the one hand, we show that using RIOT to execute a 6TiSCH stack does not degrade power consumption or network performance. On the other hand, we demonstrate how RIOT brings improvements on the time it takes to execute application tasks.

The convergence of operational and information technologies in the industry requires a new generation of IP-compliant communication protocols that can meet the industrial performance requirements while facilitating the integration with novel web-based supervisory control and data acquisition (SCADA) systems. For more than a decade, the industry has relied on time-slotted channel hopping (TSCH) communication technology to meet these performance requirements through standards such as WirelessHART and ISA100.11a. TSCH-based networks have proven to yield over 99.999% end-to-end reliability, supporting flow isolation and QoS management while ensuring over a decade of battery lifetime. However, these technologies were designed to address the factory use cases of a decade ago, not considering IP compliance or standardized network management and resource orchestration as a must. The Internet Engineering Task Force (IETF) and the 6TiSCH working group (WG) have been actively working on this challenge by designing protocols to bridge the performance of industrial solutions with IP-compliant networks. The effort has resulted in 6TiSCH, a set of specifications that define the IPv6 control plane to manage and orchestrate a TSCH network. 6TiSCH provides the missing elements for zero-configuration TSCH network bootstrap, efficient network access authentication, and distributed and modular scheduling mechanisms. As a cross-layer effort, 6TiSCH leverages and integrates other IETF specifications and the WG has also driven the definition of novel specifications in other IETF WGs. An ultimate goal of this effort is the definition of a fully functional architecture where a combination of IETF protocols enables the envisioned convergence on top of the IEEE industrial standard. This paper introduces the work done by the 6TiSCH WG at IETF, evaluates the performance of the reference implementation, and discusses the 6TiSCH software ecosystem.

Internet of Things (IoT) in agriculture applications have evolved to solve several relevant problems from producers. Here, we describe a component of an IoT-enabled frost prediction system. We follow current approaches for prediction that use machine learning algorithms trained by past readings of temperature and humidity sensors to predict future temperatures. However, contrary to current approaches, we assume that the surrounding thermodynamical conditions are informative for prediction. For that, a model was developed for each location, including in its training information of sensor readings of all other locations, autonomously selecting the most relevant ones (algorithm dependent). We evaluated our approach by training regression and classification models using several machine learning algorithms, many already proposed in the literature for the frost prediction problem, over data from five meteorological stations spread along the Mendoza Province of Argentina. Given the scarcity of frost events, data was augmented using the synthetic minority oversampling technique (SMOTE). The experimental results show that selecting the most relevant neighbors and training the models with SMOTE reduces the prediction errors of both regression predictors for all five locations, increases the performance of Random Forest classification predictors for four locations while keeping it unchanged for the remaining one, and produces inconclusive results for logistic regression predictor. These results demonstrate the main claim of these works: that thermodynamic information of neighboring locations can be informative for improving both regression and classification predictions, but also are good enough to suggest that the present approach is a valid and useful resource for decision makers and producers.

Recent standardization activities bring high Quality of Service (QoS) and predictability to Internet of Things (IoT), which are “going industrial”. Critical applications such as industrial process control, smart grid or vehicle automation require deterministic transmissions with properties such as on-time data deliveries and end-to-end reliability close to 100%. Traditional radio technologies based on collision detection and retransmission introduce unpredictable delays, and can not ensure reliable delivery within a narrowly bounded time. This paper proposes to exploit spatial diversity and packet redundancy to compensate for the inherently lossy wireless medium. We introduce “Leapfrog Collaboration”, a communication mechanism which takes advantage of communication overhearing, and in which parallel transmissions over two paths are scheduled. Promiscuous listening between the paths enables nodes to possibly overhear transmissions on the other. We evaluate the delay and jitter of the communication by simulation using Contiki OS and show that Leapfrog Collaboration outperforms the default retransmission-based approach of IEEE802.15.4-TSCH by up to 28% and 54%, respectively, while providing high network reliability.

6TiSCH is a technology being standardized at the IETF which brings determinism to low-power wireless communication. In a 6TiSCH network, all communication is orchestrated by a communication schedule. This paper explores the applicability of this new technology to control systems. In particular, we apply it to the inverted pendulum, a canonical control system in which a cart moves along a track to keep a pendulum — which naturally falls over — upright. This paper presents the first characterization and implementation of a closed-loop wireless feedback control network using completely standards-compliant IEEE802.15.4 TSCH technology. First, we implement a control loop in OpenWSN and experimentally evaluate the performance of the network by varying the radio duty cycle, number of hops, and introducing controlled external interference. We show that 100% reliability can be achieved while maintaining latencies well below the critical delay of the system. Second, we use the network on an inverted pendulum system and show that angular deviations from the upright position do not exceed 3 degrees, even in a multi-hop setup. Finally, we discuss the results in detail, and advocate for a co-design of the controller and the networking system.

The 6TiSCH working group is standardizing the low-power wireless protocol stack for the Industrial IoT. The default scheduling function (SF0) standardized by 6TiSCH uses simple random slot selection. This paper proposes the Low Latency Scheduling Function (LLSF), a new scheduling function which daisy-chains timeslots rather than picking them randomly. We implement LLSF in OpenWSN and evaluate its performance experimentally. LLSF yields 82.8% lower end-to-end latency ona 5-hop path than SF0, at no extra costs.

This paper introduces SOL, which is both an efficient data representation for sensor measurements and network statistics, and a complete low-power wireless sensor management system that builds around it. A SOL system consists of multiple low-power wireless mesh networks in which motes connected to sensors and actuators send data to a single server. It offers multi-tier data replication and the associated data recovery. SOL is used in 3 pilot deployments for micro-climate monitoring, building automation and agriculture applications. In conjunction with Metronome Systems' NeoMote and Manager devices, SOL is a turn-key ready-to-deploy end-to-end system.

In 2013, 85% of the peach production in the Mendoza region (Argentina) was lost because of frost. In a couple of hours, farmers can lose everything. Handling a frost event is possible, but it is hard to predict when it is going to happen. The goal of the PEACH project is to predict frost events by analyzing measurements from sensors deployed around an orchard. This demo provides an overview of the complete solution we designed and deployed: the low-power wireless network and the back-end system. The low-power wireless network is composed entirely of commercial off-the-shelf devices. We develop a methodology for deploying the network and present the open-source tools to assist with the deployment, and to monitor the network. The deployed low-power wireless mesh network, built around SmartMesh IP, is 100% reliable, with end-to-end latency below 2 s, and over 3 years of battery lifetime.

The Industrial Internet of Things (IIoT) vision relies on reliable low-power wireless technologies and a complete standardized protocol stack that brings Internet connectivity to constrained end devices. Currently IEEE802.15.4-2015 TSCH provides reliability over low-power wireless technologies and the IETF has defined a protocol stack that is suitable to constrained devices. Open-source initiatives contributing to the development of network stacks for embedded devices, and the availability of open hardware platforms that facilitate prototyping IIoT applications contributes to the adoption of IIoT technologies. To realize the IIoT vision, this demo presents the Open- WSN and OpenMote projects, which provide both an open-source software implementation of the IEEE low-power wireless technologies and the IETF protocol stack, and an open-source hardware platform that meets the requirements to prototype IIoT applications.

Experimental research in low-power wireless networking lacks a reference benchmark. While other communities such as databases or machine learning have standardized benchmarks, our community still uses ad-hoc setups for its experiments and struggles to provide a fair comparison between communication protocols. Reasons for this include the diversity of network scenarios and the stochastic nature of wireless experiments. Leveraging on the excellent testbeds and tools that have been built to support experimental validation, we make the case for a reference benchmark to promote a fair comparison and reproducibility of results. This abstract describes early design elements and a benchmarking methodology with the goal to gather feedback from the community rather than propose a definite solution.

Industrial control systems have traditionally been built around dedicated wired solutions. The requirements of flexibility, mobility, and cost have created a strong push toward wireless solutions, preferably solutions requiring low power. Simultaneously, the increased need for interoperability and integration with the wider Internet made a transition to IP-based communication unavoidable. Following these trends, we survey 6TiSCH, the emerging family of standards for IP-based industrial communication over low-power and lossy networks. We describe the state of the standardization work, the major issues being discussed, and open questions recently identified. Based on extensive first-hand experience, we discuss challenges in implementation of this new wave of standards. Lessons learned are highlighted from four popular open-source implementations of these standards: OpenWSN, Contiki, RIOT, and TinyOS. We outline major requirements, present insights from early interoperability testing and performance evaluations, and provide guidelines for chip manufacturers and implementers.

One fundamental component of the IPv6 protocol suite, the Neighbor Discovery (ND) protocol, is undergoing a major evolution to adapt to the needs of mobile and low-power devices. The traditional model of multicast-based advertisements is being extended with a registration mechanism that exhibits a number of interesting properties. This paper explores how this new model, called Efficient-ND or Wireless ND (WiND), can be used as an open abstraction for any IPv6 mesh network, and can enable the interconnection of multiple such meshes over a federating backbone, effectively forming what the IETF refers to as a “MultiLink subnet”. A method based on IPv6-ND proxy operation is demonstrated on a prototype based on existing industrial-class systems.

Time Synchronized Channel Hopping (TSCH) is a technique that enables ultra reliable and ultra low-power wireless multi-hop networks, and in which communication is orchestrated by a schedule. When building that schedule, one can cleanly trade off between latency, power consumption, throughput, and reliability. TSCH technology is commonplace in industrial applications, with increasing momentum to apply it to other application domains. This paper is the first to present a model that estimates the performance of a complete network. This model is applied to SmartMesh IP, a commercial TSCH product. The parameters of different classes of use cases for low-power mesh networks are presented, and the estimation model is used to evaluate the applicability of TSCH technology to those cases. This paper indicates how TSCH networks can be used in a wide range of applications: from urban applications which require a decade of battery lifetime, to high-density smart building networks with tens of nodes in the same radio space, and to deep multi-hop networks in an industrial setting.

The Datagram Transport Layer Security (DTLS) protocol is the IETF standard for securing the Internet of Things. The Constrained Application Protocol, ZigBee IP, and Lightweight Machine-to-Machine (LWM2M) mandate its use for securing application traffic. There has been much debate in both the standardization and research communities on the applicability of DTLS to constrained environments. The main concerns are the communication overhead and latency of the DTLS handshake, and the memory footprint of a DTLS implementation. This paper provides a thorough performance evaluation of DTLS in different duty-cycled networks through real-world experimentation, emulation and analysis. In particular, we measure the duration of the DTLS handshake when using three duty cycling link-layer protocols: preamble-sampling, the IEEE 802.15.4 beacon-enabled mode and the IEEE 802.15.4e Time Slotted Channel Hopping mode. The reported results demonstrate surprisingly poor performance of DTLS in radio duty-cycled networks. Because a DTLS client and a server exchange more than 10 signaling packets, the DTLS handshake takes between a handful of seconds and several tens of seconds, with similar results for different duty cycling protocols. Moreover, because of their limited memory, typical constrained nodes can only maintain 3–5 simultaneous DTLS sessions, which highlights the need for using DTLS parsimoniously.

Time slotted operation is a well-proven approach to achieve highly reliable low-power networking through scheduling and channel hopping. It is, however, difficult to apply time slotting to dynamic networks as envisioned in the Internet of Things. Commonly, these applications do not have pre-defined periodic traffic patterns and nodes can be added or removed dynamically.

Industrial low-power wireless mesh networks are shifting towards time-synchronized medium access control (MAC) protocols which are able to yield over 99.9% end-to-end reliability and radio duty cycles well below 1%. In these networks, motes use time slots to communicate, and neighbor motes maintain their clocks' alignment, typically within 1 ms. Temperature, supply voltage, and fabrication differences cause the motes' clocks to drift with respect to one another. Neighbor motes need to re-synchronize periodically through pairwise communication. This period is typically determined a priori, based on the worst case drift. In this paper, we propose a novel technique which measures and models the relative clock drift between neighbor motes, thereby reducing the effective drift rate. Instead of resynchronizing at a preset rate, neighbor motes resynchronize only when needed. This reduces the minimum achievable duty cycle of an idle network by a factor of 10, which in turn lowers the mote power consumption and extends the network lifetime. This Adaptive Synchronization is implemented as part of IEEE802.15.4e in the OpenWSN protocol stack and is validated through extensive experimentation.

This paper presents one possible approach to Signalized Left Turn Assist at intersections. A sensing platform is designed to detect the presence of cars by measuring the deflection of the magnetic field when driving by. This platform is tested experimentally under different conditions. A threshold detection algorithm is designed to determine whether a car is passing in front of the sensor. The algorithm is first run off-board using a set of previously collected magnetometer measurements, before being implemented and run on-board the platform. We show how this detection algorithm performs better as the sensor is placed close to the traffic flow and we discuss how such sensors can be networked together to form a smart intersection.

Reducing the time the radio is on in wireless devices results in lower power consumption, so sending the same data in fewer bytes can greatly extend the lifetime of a network. In this paper, we explore the use of protocol-agnostic packet compression, a technique orthogonal to current explicit compaction techniques. Because it functions as a transparent layer inside a communication stack and makes no assumption about the specific protocols used, it is generic enough to be used on multiple technologies. Compression is performed by identifying patterns in recent packets and replacing those patterns with bit flags in the transmitted packet. We present the results of compressing actual packet traces collected from several commercial networks using this algorithm and discuss the resource trade-offs of the algorithm. Results indicate compression ratios between 40% and 80%, yielding predicted energy savings of 30-70% in a typical time- synchronized network.

Having a wake-up receiver constantly listening is often seen as a replacement for running a duty- cycled medium access control protocol on a commercial low-power radio chip. Wake-up receivers do offer a better latency while consuming negligible power. Recent wake-up receivers show an impressively low power consumption of 52μW, but at the cost of a sensitivity of -72dBm, 20-30dB higher than the sensitivity of a commercial radio chip. This difference in sensitivity causes the wake-up receiver to have a much smaller communication range than the commercially available low power radio. In practice, this translates into requiring a denser deployment, or having to add an external power amplifier. This paper discusses the applicability of wake-up receivers in low-power wireless multihop networks. We show how, at available sensitivity levels, a wake-up receiver helps reducing the power consumption, but also requires a dramatically higher design or deployment cost.

Wireless communication between a pair of nodes can suffer from self interference arising from multipath propagation reflecting off obstacles in the environment. In the event of a deep fade, caused by destructive interference, no signal power is seen at the receiver, and so communication fails. Multipath fading can be overcome by shifting the location of one node, or by switching the communication carrier frequency. The effects of such actions can be characterized by the coherence length (L) and coherence bandwidth (B), respectively, given as the amount of shift necessary to transition from a deep fade to a region of average signal strength. Experimental results for a representative 2.4GHz wireless link indicate L = 5.5cm and B can vary from 5MHz at long ranges up to 15MHz for short links. For wireless sensor networks (WSNs), typically operating under the IEEE802.15.4 standard, multipath effects are therefore best handled by a channel hopping scheme in which successive communication attempts are widely spread across available carrier frequencies.

Reducing the number of transmitted bytes in a wireless sensor network reduces the time the radio is on, resulting in a significant increase in battery lifetime. Toward this end we have developed a compression technique that is independent of the protocols used in the network, acts as a transparent layer, and consumes minimal computing resources. Patterns in recent packets are identified and replaced in the transmitted packet by bit flags. This algorithm was tested on packet traces collected from commercial wireless sensor networks for 40-80% compression, yielding comparable energy savings in a time-synchronized network.

IETF ROLL has recently proposed gradient routing as a fundamental building block for data collection in Wireless Sensor Networks. This paper seconds this choice by presenting an implementation of gradient routing on current hardware, and by showing experimentally that gradient routing is robust against topological changes. To stress its self-healing quality, we design and implement a complete communication stack in which neighbor tables are built in a purely reactive fashion. We quantify the resulting topological changes, and show how gradient routing elegantly handles these dynamics. This paper presents, to the best of our knowledge, the first experimental study on gradient routing as advocated by IETF ROLL.

Wireless Sensor Networks have inherent constraints such as available bandwidth and energy. Communication protocols applying to those kind of networks need to be localized and distributed. When such a protocol needs to discriminate between several neighbor nodes (for example, the node with most remaining energy), an efficient approach is to ask the neighbors to encode information in backoff timers (in our example, the consumed energy), and respond to a question after having waited for the resulting duration. The node which answers first is elected. Whereas this technique is stateless and efficient, its inherent drawback is that response messages can collide. This paper addresses this issue by proposing a backoff function to alleviate this problem. Analytical results are presented, and confirmed using extensive simulations.

Geographic-based routing techniques are promising for wireless sensor networks, which suffer from severe energy constraints and a low throughput nature. In its simplest form, greedy geographic forwarding faces the problem of a low delivery ratio. Other protocols use the right hand rule to guarantee delivery. They nevertheless assume nodes know their exact position, whereas positioning systems offer only limited accuracy. In this paper, we propose to use path-recording mechanisms, where nodes append their identifier to the header of the message, together with geographic forwarding. While yielding a comparable number of hops for a message to reach destination than existing routing protocols with guaranteed delivery, this technique offers guaranteed delivery regardless of the positioning accuracy. This makes path-recording particularly suitable for real-world wireless sensor network implementations.

For low-energy, low-throughput Wireless Sensor Networks, geographic forwarding avoids creating and maintaining a structure using clustering or gradient construction. Yet, geographic forwarding assumes position-awareness, which may be not realistic. In this paper, we propose to use virtual coordinates. Each node determines its [x,y] position in a virtual space based on a random or pseudo-random process. It uses these coordinates to route information with geographical-inspired routing protocols. Extensive simulation shows that this approach can be very efficient for low-throughput WSN.

Wireless sensor networks (WSNs) have witnessed a tremendous upsurge in recent years, both in academia and industry; this is mainly attributed to their unprecedented operating conditions and a variety of commercially viable applications. Because of their dependence on scarce battery power, communication protocols need to be energy efficient. However, finding the optimal solution is challenging as it needs to consider the whole communication stack at once. In this paper, we propose an approach that aims at optimizing jointly L2 (link) and L3 (routing) protocols. We design 1-hopMAC, a communication architecture grouping MAC and routing layers which avoids 1-hop neighborhood knowledge. 1-hopMAC can be combined, among others, with a geographic or gradient based routing protocols. We present an analytical study of energy consumption to point out the optimal configuration of 1-hopMAC

Many wireless sensor network applications are emerging nowadays. For critical, safety related applications, the network needs to provide bounded transmission delays. Hard real-time guarantees need therefore to be given by wireless sensor network communication protocols. In this paper, we propose a new hard real-time MAC protocol, and we give the time constraints that can be reached.