International audience

Low-power wide area networks (LPWANs) are being increasingly used in Internet of Things applications, including smart city and environmental monitoring, as they enable communications from low-power end-devices to distant gateways. LoRaWAN is the most common protocol for LPWANs, and is able to automatically tradeoff throughput and reliability thanks to an algorithm called Adaptive DataRate (ADR). However, the LoRaWAN standard imposes mobile nodes to disable the ADR. In this paper, we propose a protocol called MADERE (for Mobile ADR) that attempts to adapt the LoRaWAN parameters for mobile end-devices. We show that MADERE performs well compared to the few existing algorithms from the literature, with limited overhead.

Recent monitoring applications extensively rely on low-power wide-area networks, such as those provided by LoRa and LoRaWAN, in order to enable end-devices to communicate over long distances. However, in large-scale deployments, the small throughput of LoRa is further reduced due to collisions. In this paper, we propose a new scheme that aims to decode colliding frames. It relies on frequency detection at each symbol frontier. It reduces detection errors when symbols of similar values are superposed. It is compatible with legacy LoRaWAN communications, and only requires modifications at the gateway. Our simulation results show that our proposition is able to decode more collisions than the other protocols from the literature (about twice more for 16 nodes and SF12), therefore increasing the throughput and thus the scalability of the network.

LoRa (Long Range) is a physical layer designed for low-power wide area networks. It is widely used to provide long range connectivity to Internet of Things devices. In order to improve the limited throughput of LoRa, researchers have proposed several collision resolution algorithms. However, a common software framework to compare these algorithms is lacking. In this paper, we propose an open-source framework using GNU Radio, mainly designed to test and compare collision resolution algorithms, as well as physical layer algorithms. Our framework can help optimizing the parameters of algorithms according to channel conditions such as very low signal to noise ratio for instance. We also discuss technical implementation issues of existing collision resolution algorithms. Finally, we show how our framework can be used for either real experiments on USRPs, or for simulations with a large number of nodes.

LoRa is one of the leading technologies for Low-Power Wide Area Networks and the Internet of Things. Collisions in LoRa might cause retransmissions, which negatively impact the network performance and scalability. Several algorithms have been proposed to decode colliding frames under specific conditions. However, there remain indistinguishable frames due to uncertainties in some or all symbols. In this paper, we propose a general algorithm that significantly improves the recovery capabilities of existing algorithms by leveraging the LoRa coding techniques. Simulation results show that our algorithm can significantly reduce the number of the failed decoding of LoRa frames and improve the performance of the network.

LoRa is becoming widely used in low-power wide area networks as it enables a communication range of several kilometers with low energy consumption, but with a low bitrate. Collisions in LoRa further reduce the overall performance of the network, and more specifically the throughput. In this paper, we propose a slotted MAC protocol that enables the decoding of colliding LoRa signals. It is based on a new decoding technique at the physical layer that is able to decode the symbols of many frames in collision. Simulation results show that our MAC protocol significantly increases the achievable performance of LoRa networks. For instance, for 25 nodes having a duty-cycle of 10% and with SF7, the throughput with our protocol is 11% larger than the existing protocols.

In LoRa (Long Range), when a collision occurs in the network, each end-device has to retransmit its colliding frame. This reduces the throughput, and increases the energy consumption of the end-devices and the delay of the frames. In this paper, we propose an algorithm to decode colliding synchronized LoRa signals and thus improve the overall performance of the network. Indeed, we use successive transmissions of bitmaps by the end-devices to determine the correct symbols of each colliding frame, instead of retransmitting the whole frames. Simulation results show that our algorithm is able to significantly improve the overall throughput of LoRaWAN, and to decrease the energy consumption and the delay of the transmitters.

The LoRa physical layer is one of the most promising Low Power Wide-Area Network (LPWAN) technologies for future Internet of Things (IoT) applications. It provides a flexible adaptation of coverage and data rate by allocating different Spreading Factors (SFs) and transmit powers to end-devices. We focus on improving throughput fairness while reducing energy consumption. Whereas most existing methods assume perfect SF orthogonality and ignore the harmful effects of inter-SF interferences, we formulate a joint SF and power allocation problem to maximize the minimum uplink throughput of end-devices, subject to co-SF and inter-SF interferences and power constraints. This results into a mixed-integer non-linear optimization, which, for tractability, is split into two sub-problems: firstly, the SF assignment for fixed transmit powers, and secondly, the power allocation given the previously obtained assignment solution. For the first sub-problem, we propose a low-complexity many-to-one matching algorithm between SFs and end-devices. For the second one, given its intractability, we transform it using two types of constraints' approximation: a linearized and a quadratic version. Our performance evaluation demonstrates that the proposed SF allocation and power optimization methods enable to drastically enhance various performance objectives such as throughput, fairness and power consumption, and that they outperform baseline schemes.

Low-Power Wide-Area Network (LPWAN) based on LoRa physical layer is envisioned as one of the most promising technologies to support future Internet of Things (IoT) systems. LoRa provides flexible adaptations of coverage and data rates by allocating different Spreading Factors (SFs) to end-devices. Although most works so far had considered perfect orthogonality among SFs, the harmful effects of inter-SF interferences have been demonstrated recently. Therefore in this work, we consider the problem of SF allocation optimization under co-SF and inter-SF interferences, for uplink transmissions from end-devices to the gateway. To provide fairness, we formulate the problem as maximizing the minimum achievable average rate in LoRa, and propose a SF allocation algorithm based on matching theory. Numerical results show that our proposed algorithm enables to jointly enhance the minimal user rates, network throughput and fairness, compared to baseline SF allocation methods.

The Long Range Wide Area Network (LoRaWAN) standard was mainly developed to meet the requirements of many emerging Internet of Things (IoT) applications as it provides low power and low cost connectivity over long distances. In LoRaWAN, when an end-device transmits an uplink message, gateways that receive this message transmit it to the network server, which, in turn, selects a single gateway to reply to the end-device. LoRaWAN does not specify how to select the gateway. In this paper, we focus on the gateway selection for downlink communications in LoRaWAN in order to improve the throughput of the network. We aim to present and evaluate several algorithms for selecting the best gateway for downlink while increasing LoRaWAN throughput for different types of gateway deployment. We show that the system throughput depends on this deployment and that balancing the number of end-devices per gateway improves the performance compared to choosing the gateway with the highest signal quality.

Long-range low-power wireless communications, such as LoRa, are used in many IoT and environmental monitoring applications. They typically increase the communication range to several kilometers, at the cost of reducing the bitrate to a few bits per seconds. Collisions further reduce the performance of these communications. In this paper, we propose two algorithms to decode colliding signals: one algorithm requires the transmitters to be slightly desynchronized, and the other requires the transmitters to be synchronized. To do so, we use the timing information to match the correct symbols to the correct transmitters. We show that our algorithms are able to significantly improve the overall throughput of LoRa.

In networks that operate during a long time, the routing protocol might have to be changed: this is the case when the network administrator plans a router change. Loop-free transition algorithms are used to ensure that there is no loop during the migration from the initial routing protocol to the final routing protocol. In this paper, we propose a distributed loop-free transition algorithm, called DLF (distributed loop-free heuristic). The algorithm is based on the fact that routing loops resulting from the removal of a node are localized, and can be detected efficiently. We show through simulations that DLF compares well with the existing centralized algorithms, and outperforms the existing distributed algorithm, in terms of migration duration.

Wireless sensor networks have long been characterized by short range communications. Lately, long range wireless sensor networks such as LoRaWAN (long range wide area network) have emerged, increasing the communication range at the cost of reduced bit rate. This paper focuses on the MAC layer of LoRaWAN and studies communications from a gateway to an end-device. We propose a Markov chain model to estimate the delivery delay of an acknowledged communication (with retransmissions) and study the impact of the number of channels, the data-rate and the number of nodes.

In networks that operate during a long time, the routing protocol might have to be changed (in order to apply a routing protocol update, or to take into account a change in the routing metrics). A loop-free transition algorithm has to be used in order to perform the transition to the new routing protocol without generating transient routing loops. In this paper, we propose a loop-free transition algorithm called ACH (avoiding cycles heuristic), which is able to perform the transition in a very small number of steps. Compared to other algorithms of the literature, ACH yields a number of steps which is independent of both the number of nodes and the number of destinations, and thus allows the transition to be performed in a small time. We show through simulations that ACH significantly outperforms other heuristics of the literature, due to its capability to deal with several destinations at once, and due to a priority-based procedure to avoid cycles.

Wireless sensor networks can accommodate multiple applications by using a multi-stack architecture in order to deliver a large number of QoS. Multi-stack architectures can be optimized by allowing packet exchanges between stacks. However, routing loops may appear because of these exchanges. In this paper, we highlight the problem of routing loops generated when the same packet is routed according to two routing protocols. We define the delayable property of routing protocols by considering that some nodes might hold packets in order to avoid loops in the network. We show that minimizing the number of such nodes is an NP-complete problem. Then, we propose two heuristics to address this issue: a centralized deterministic heuristic requiring a global knowledge of the network, and a distributed stochastic heuristic reducing the number of hops from source to destination. Our two heuristics show important benefits: we reach a gain of up to 67% for the first heuristic and of up to 53% for the second heuristic, in terms of number of hops.

Wireless sensor networks are often deployed for monitoring purposes: when nodes detect the occurrence of a significant event, they transmit an information to a control entity in a multi-hop fashion. When data rate increases, congestion becomes a fundamental issue, especially when an emergency situation generates alarm messages originating from a specific area of the network. Indeed, congestion increases delays and packet losses, and yields to an unfair use of the energy of nodes. In this paper, we propose to improve the ZigBee routing protocol, aiming at reducing traffic congestion. The proposed solution uses intermediate nodes, denoted as pivots, which are selected by the data sources in order to reduce congestion on paths. Simulation results highlight the significant improvement achieved in terms of packet losses and average delays, with respect to the ZigBee routing protocol, while the overhead generated in the network is maintained under control. A mathematical model to derive the average path length and the number of pivots is also provided.

Wireless sensor networks deployed nowadays are traditionally mono-stack: they are operating according to a single combination of one MAC protocol and one network (NWK) protocol. This work proposes a new multi-stack architecture in which several combinations of MAC and NWK protocols are used. This can be achieved by dividing time into time intervals and activating different combinations during each period. Simulations of this approach prove that QoS is mitigated among the combinations. To alleviate the complexity of the time-intervals dimensioning, a formal description of a queue exchange algorithm that allows frames from a time-interval to be sent during another time-interval is proposed. This algorithm improves significantly the global performance of the network.

Wireless sensor networks are increasingly used for remote monitoring, fire detection, emergency response. Such networks are equipped with small devices powered by batteries and designed to be operated for years. They are often based on the ZigBee standard which defines low power and low data rate protocols. As network size and data rates increase, congestion arises as a problem in these networks, especially when an emergency situation generates alarm messages in a specific area in the network. Indeed, congestion occurs as the alarms converge to a specific destination, which results into packet losses and higher delays. In this paper, we propose a solution for congested links, called the PiRAT (Pivot Routing for Alarm Transmission) protocol. It is based on multi-path routing in order to add some diversity in routing the alarms. PiRAT uses intermediate nodes as pivots to reach the destination. Simulation results show that PiRAT has better performance than previous protocols in terms of packet loss, end-to-end delay, congestion and node overload.