International audience

Delivering downlink ACKs to Class A LoRaWAN devices via LEO satellite constellations requires predicting end-to-end propagation delays of 10–500 ms to hit a 1-second receive window, a timing challenge absent from terrestrial schedulers. We present DORSAL, the first Mixed-Integer Linear Programming (MILP) scheduler for downlink delivery in direct-to-satellite LoRaWAN networks. It introduces theDownlink Arrival Receive-window Timing (DART)as the central constraint to jointly optimize gateway selection and packet injection timing across ISL-capable and bent-pipe architectures. Evaluation on a Walker 5×5 polar constellation (25 satellites, 650 km) and a commercial ground station network yields five results: (i) DART infeasibility blocks 73% of bent-pipe deliveries regardless of scheduler quality: DART-unaware approaches collapse from 93% nominal to only 20% real delivery; (ii) ISL routing raises %ACK by +67.4 pp over bent-pipe (91.6% vs. 24.2% atnGS=3 ground stations, ISM band) by eliminating the three-way simultaneous-visibility constraint, with 73% of ACKs delivered via ≥ 2-hop paths; (iii) ISL %ACK is nearly flat acrossnGS∈ {3, 6, 12} ground stations (91.6%–92.7%), showing that a minimal threestation polar network captures the full scheduling benefit of an ISL-equipped constellation; (iv) ISL hardware speed has negligible impact up to 300 ms/hop: %ACK is flat from 0 to 300 ms, then degrades in two discrete steps (−5.3 pp at 500 ms, −2 pp at 700 ms) as successive hop-count tiers lose causal injection feasibility; and (v) the MILP solves to proven optimality within seconds for up to 103devices, confirming that the sparse conflict-graph structure keeps the problem tractable at realistic IoT subscriber counts.

Long-Range (LoRa) is one of the main modulation techniques used for Low Power Wide Area Networks (LPWANs). Recently, it has been extended from the sub-GHz band to the 2.4 GHz Industrial, Scientific, and Medical (ISM) band, enabling the construction of a LPWAN that benefits from global interoperability without duty-cycle limitations. However, the coexistence of LoRa with the other wireless technologies of the 2.4 GHz ISM band is a challenging question. In this article, we make the first performance evaluation of the interference between LoRa and Wireless Fidelity (Wi-Fi) transmissions, by analyzing multiple parameters: LoRa channel occupancy, deployment topology, LoRa physical layer parameters, and the frequency channels used. We also perform simulations to extend our experimental results to other configurations. The performance evaluation is achieved using a generic methodology that can be applied to other wireless technologies. Finally, we provide recommendations for the use and deployment of LoRa that will improve its coexistence with Wi-Fi.

LoRaWAN is a widely used wireless communication standard for the Internet of Things that enables the collection of measurement data from numerous monitoring applications (such as smart metering, pollution, and asset tracking). Most research work has been focused on the performance of LoRaWAN as a function of the uplink traffic, as this is the most common scenario. Nevertheless, downlink traffic is a fundamental building block of the LoRaWAN standard, and a crucial part of applications such as smart healthcare, where reliability is extremely important. In this paper, we study the impact of the downlink traffic and different scheduling policies on the performance of LoRaWAN. We investigate: (i) the impact of an optimal schedule for the downlink traffic, (ii) the choice of the physical layer parameters used to send downlinks to end-devices during the second reception window, and (iii) the choice of the gateway that sends the downlinks. Our results show that even when using an optimal schedule, the presence of downlink traffic reduces the capacity of a LoRaWAN network up to 20%. The most limiting factor is the gateway, due to its duty cycle and half-duplex characteristics.

This work focuses on managing upstream traffic in multigateway Low-Power Wide Area Networks (LPWANs) to support efficient traffic from thousands of nodes. As LP-WANs face challenges such as increased collision probability and network saturation due to node densification, our research introduces a distributed and probabilistic traffic control protocol. This protocol aims to effectively manage network traffic, reduce collisions, and mitigate saturation issues, ensuring better performance and scalability in densely populated IoT environments. The protocol enables nodes to dynamically adapt their traffic to meet application needs, such as transmitting a defined number of measurements (K) within a designated time frame. This adjustment remains unaffected by the node count and network topology, focusing instead on the feedback message's destination to the network nodes, which is crucial for dynamically adapting traffic intensity and reducing collisions. We explore two feedback transmission strategies: a synchronous one, where all gateways transmit feedback simultaneously to all nodes, and a round-robin one, where one gateway at a time sends feedback to nodes within its coverage area. Based on simulation results, our evaluated strategies achieve substantial performance improvements over the Baseline LoRaWAN. Specifically, they demonstrate a network lifetime increase of up to 93.12 %, a success rate increase of up to 96.34 %, and a packet delivery ratio increase of up to 14.97 %. These findings highlight significant enhancements in both efficiency and reliability compared to traditional LoRaWanconfigurations.

Wi-Fi is a standard off-the-shelf solution for industrial robotics. The IEEE 802.11ax amendment extends it to support the 6 GHz band, 160 MHz bandwidth and bit-rates up to 9.6 Gbps. In this article, we evaluate the performance of Wi-Fi 6 compared to Wi-Fi 5 and Wi-Fi 4. We select 9 physical layers (PHYs) representing different Wi-Fi generations and we evaluate their performance in an industrial shipyard in the presence of high radio frequency interference and metallic obstructions. We deploy setup of a robotic station (STA) and a controller STA with three applications running in parallel: a robotic STA is sending a high throughput stream to a controller, a Robotic Operating System (ROS) application is sending time-critical control commands to the robotic STA, Precision Time Protocol (PTP) keeps synchronizing the clocks between both STAs. We evaluate the performance in terms of three Key Performance Indicators (KPIs): streaming throughput, IP-level delay using PTP, and Application-level delay of ROS control packets. The networks are run in: Short range Line of Sight (LoS), Medium range LoS, Long range None-LoS (NLoS), and Long range mixed settings. We note that depending on the PHY configuration, an older Wi-Fi generation may outperform Wi-Fi 6. We further observe trade-offs between the different PHYs: wide channel PHYs (e.g. 160 MHz) had best throughput reaching up to 900 Mbps while PHYs while 80 MHz or 20 MHz bandwidth achieved as low as 9 ms delay. This motivates further research in multi-PHY adaptation for KPIs specific to industrial robotics.1

LoRa® and LoRaWAN are one of the most common wireless technologies used today in the Internet of Things. If until now LoRa was strictly used in sub-GHz bands, a new version has been released for the 2.4 GHz band that does not have any duty cycle restrictions and that allows the use of higher datarates, which opens the door to the deployment of new applications (such as asset tracking or indoor localization). In this paper, we present the first extensive evaluation of LoRa 2.4 GHz in a typical indoor environment, both in the presence and lack of human and WiFi activities. We run an exhaustive evaluation of all 128 possible combinations of the different LoRa physical parameters (spreading factor, bandwidth and coding rate) and we show that despite the use of higher frequency, LoRa is capable of maintaining a good connectivity throughout the building, similar to what was observed in sub-GHz bands. Still, some configurations were clearly affected by the daily life activities in the building during the working hours of weekdays.

Data collected from mobile phones or from motion detection sensors are regularly used as a proxy for user presence in networking studies. However, little attention was paid to the actual accuracy of these data sources, which present certain biases, in capturing actual human presence in a given geographical area. In this work, we conduct the first comparison between mobile phone data collected by an operator and human presence data collected by motion detection sensors in the same geographical area. Through a detailed spatio-temporal analysis, we show that a significant correlation exists between the two datasets, which can be seen as a cross validation of the two data sources. However, we also detect some significant differences at certain times and places, raising questions regarding the data used in certain studies in the literature. For example, we notice that the most important daily mobility peaks detected in mobile phone data are not actually detected by on ground sensors, or that the end of the work-day activities in the considered area is not synchronised between the two data sources. Our results allow to distinguish the metrics and the scenarios where user presence information is confirmed by both mobile phone and sensor data.

LoRaWAN is a major player for IoT data collection in large areas. In such networks, the uplink is mainly used, especially for data transmission, whereas the downlink is used for control purposes, including physical layer configuration, over the air activation and acknowledgments. In most studies of the LoRaWAN capacity, the uplink and the downlink are supposed to be orthogonal. This assumption seems acceptable and correct because the LoRa physical layer uses an inverse modulation for the uplink and the downlink. In this work, we use a real testbed composed of software-defined radio (USRPs, GNU Radio) to show that this assumption is wrong: the frame delivery rate decreases by up to 20% when simultaneous transmissions occur between the uplink and the downlink. As far as we know, it is the first time that this result is shown.

Direct-to-Satellite-IoT (DtS-IoT) is a promising approach for data transfer to/from IoT devices in remote areas where deploying terrestrial infrastructure is not appealing or feasible. In this context, Low-Earth Orbit (LEO) satellites can serve as passing-by IoT gateways to which devices can offload buffered data to. However, transmission distance and orbital dynamics, combined with highly constrained devices on the ground makes DtS-IoT a very challenging problem. In fact, existing IoT medium access control protocols, negotiations schemes, etc. need to be revised and/or extended to scale up to these challenging conditions. The intricate time-dynamic aspects of DtS-IoT networks require of adequate simulation environments to assess the expected performance of enabling technologies. To make up for the lack of such tools, we present a novel event-driven open-source end-to-end simulation tool coined FLoRaSAT. The simulator leverages Omnet++ and includes a benchmarking DtS-IoT scenario comprising 16 cross-linked LEO satellites and 1500 IoT nodes on the surface. Satellites and devices are connected using the standard LoRaWAN Low-Power Wide Area (LPWAN) protocol (Class A and B). FLoRaSAT allows the easy implementation and study of DtS-IoT radio access and core network protocols, and we take advantage of this flexibility to investigate expected network metrics and non-intuitive phenomena emerging from the resulting multi-gateway setup.

Modern protocols for wireless sensor networks efficiently support multi-hop upward traffic from many sensors to a collection point, a key functionality enabling monitoring applications. However, the ever-evolving scenarios involving low-power wireless devices increasingly require support also for downward traffic, e.g., enabling a controller to issue actuation commands based on the monitored data. The IETF Routing Protocol for Low-power and Lossy Networks (RPL) is among the few tackling both traffic patterns. Unfortunately, its support for downward traffic is significantly unreliable and inefficient compared to its upward counterpart. We tackle this problem by extending RPL with mechanisms inspired by opposed, yet complementary, principles. At one extreme, we retain the route-based operation of RPL and devise techniques allowed by the standard but commonly neglected by popular implementations. At the other extreme, we rely on flooding as the main networking primitive. Inspired by these principles, we define three base mechanisms, integrate them in a popular RPL implementation, analyze their individual and combined performance, and elicit the resulting tradeoffs in scalability, reliability, and energy consumption. The evaluation relies on simulation, using both real-world topologies from a smart city scenario and synthetic grid ones, as well as on testbed experiments validating our findings from simulation. Results show that the combination of all three mechanisms into a novel protocol, T-RPL (i) yields high reliability, close to the one of flooding, (ii) with a low energy consumption, similar to route-based approaches, and (iii) improves remarkably the scalability of RPL with respect to downward traffic.

The devices composing Wireless Sensor Networks (WSN) are very limited in terms of memory, processing power and battery. RPL has emerged as the de facto routing standard in low-power and lossy networks. While most of the proposals focus on minimizing the global energy consumption, we aim here at designing an energy-balancing routing protocol: each node should efficiently consume the same quantity of energy to improve the network lifetime. To this end, we exploit an Expected Lifetime metric, denoting the residual time of the nodes (time until the node will run out of energy). We propose mechanisms to detect the energy-bottleneck nodes and to spread the traffic load uniformly among them. While RPL constructs a Destination-Oriented Directed Acyclic Graph (DODAG) structure, it only implements single path. We propose here to exploit its natural multipath structure. This multipath approach helps reducing the number of DODAG reconstructions that leads to instabilities and convergence problems. Simulations highlight we improve both the routing reliability and the network lifetime.

RPL, the IPv6 Routing Protocol for Low-Power and Lossy Networks, supports both upward and downward traffic. The latter is fundamental for actuation, for queries, and for any bidirectional protocol such as TCP, yet its support is compromised by memory limitation in the nodes. In RPL storing mode, nodes store routing entries for each destination in their sub-graph, limiting the size of the network, and often leading to unreachable nodes and protocol failures. We propose here D-RPL, a mechanism that overcomes the scalability limitation by mending storing mode forwarding with multicast-based dissemination. Our modification has minimal impact on code size and memory usage. D-RPL is activated only when memory limits are reached, and affects only the portion of the traffic and the segments of the network that have exceeded memory limits. We evaluate our solution using Cooja emulation over different synthetic topologies, showing a six-fold improvement in scalability.

The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is one of the emerging routing standards for multihop Wireless Sensor Networks (WSN). RPL is based on the construction of a Destination-Oriented Directed Acyclic Graph (DODAG), which offers a loop-free topology to route data packets. While several routing metrics have been proposed in the literature, it is unclear how they perform with RPL. In this paper, we analyze the impact of different PHY and MAC metrics on the stability and efficiency of RPL. We highlight the fact that realistic conditions lead to instabilities and oscillations in the routing structure. While minimizing the hop length leads to a stable but poor routing structure, more sophisticated link metrics such as ETX reflect more clearly the radio link quality but increase the number of DODAG reconfigurations. We also provided a detailed methodology to measure the DODAG stability and to implement efficiently each routing metric with RPL.