LoRaWAN networks essentially overcome the low efficiency of ALOHA-based channel access method by relying on the frequency/Spreading Factor (SF) diversity and on the Adaptive Data Rate control mechanism. The Carrier Sense Multiple Access (CSMA) approaches were not considered by the LoRa Alliance until very recently when a LoRaWAN Technical Recommendation for enabling a CSMA protocol on LoRa networks was released, based on the Channel Activity Detection (CAD) mechanism. In this article, we study the performance and the scalability of the newly proposed LoRaWAN CSMA protocol with extensive simulations, in a very dense urban scenario and varying network topologies, radio and traffic conditions. We show that in such scenario the LoRaWAN CSMA has limited performance compared with a state-of-art multi-channel CSMA. We then propose gradual improvements of the LoRaWAN CSMA and thoroughly analyze their benefits.

The increasing volume of data in various environments such as IoT and the need to maintain data privacy and security have led to the development of usage control models. Usage control policies are models that enable fine-grained access control over data by enforcing restrictions on how users can use the data. Semantic mechanisms, on the other hand, use context and meaning to identify potential security threats and prevent them from accessing sensitive information. Although not widely explored, merging these two techniques could create an efficient mechanism to help ensure the confidentiality, integrity, and availability of critical data and resources. This paper aims to encourage this research path by proposing a translation model that converts usage control rules into SWRL. In particular, we consider during our approach the notions of contexţ permission and prohibition. The proposition is validated by constructing a multi-layer proof of concept that use ontologies and OWL for implementing the translation model. Furthermore, to ascertain the practicality of our approach, a time processing evaluation is conducted, and the results are found to be satisfactory.

The current medium access in LoRa, involving strategies very similar to early ALOHA systems, does not scale for future denser LoRa networks, subject to many collisions. Semtech's Channel Activity Detection (CAD) feature enables to implement a carrier sense (CS) in LoRa WANs, but its unreliability at short distance dramatically decreases its efficiency for classical CS strategies. We present CANL, a novel LoRa channel access approach based on an asynchronous collision avoidance (CA) mechanism and operating without the CAD procedure. Extensive simulations using an extended LoRaSim confirm the performance of CANL in a wide range of configurations. The results are promising and show that the proposed CA approach can greatly increase the delivery ratio in dense LoRa networks compared to a classical CS strategy while keeping the energy consumption at a reasonable level.

The main purpose of IoT is to deliver reliable, high quality services and innovative solutions by transforming the captured data into meaningful information, and thus improving user's daily life. In this regard, it is in the interest of the community to encourage entities within IoT environments to share their data, and therefore serve public interest and contribute to the innovation and technological progress. Meanwhile, the distributed nature of IoT networks and the diversity of its actors lead to the recognition of security and data sharing management as one of the major challenges of the IoT domain. For instance, due to insufficient governance of the shared data within IoT environments, data provider retains little to no control over his assets once he has agreed to share them. Furthermore, data consumers are not able to trace the source of the available resource nor its history processing to assess its quality. All this creates a digital environment that is certainly functional but lacks mutual trust between its actors, which can prevent the domain's full potential to be exploited, and therefore disrupt the implemented services. In our work, we propose an approach to improve data sharing management using three main elements: semantic modeling, usage control policies, and data provenance.

The main purpose of IoT is to deliver reliable, high quality services and innovative solutions by transforming the captured data into meaningful information, and thus improving user's daily life. In this regard, it is in the interest of the community to encourage entities within IoT environments to share their data, and therefore serve public interest and contribute to the innovation and technological progress. Meanwhile, the distributed nature of IoT networks and the diversity of its actors lead to the recognition of security and data sharing management as one of the major challenges of the IoT domain. For instance, due to insufficient governance of the shared data within IoT environments, data provider retains little to no control over his assets once he has agreed to share them. Furthermore, data consumers are not able to trace the source of the available resource nor its history processing to assess its quality. All this creates a digital environment that is certainly functional but lacks mutual trust between its actors, which can prevent the domain's full potential to be exploited, and therefore disrupt the implemented services. In our work, we propose an approach to improve data sharing management using three main elements: semantic modeling, usage control policies, and data provenance.

About 35% of the world’s food are produced in small-scale farms while only occupying about 12% of all agricultural land. However, smallholder farmers usually face a number of constraints and the water resource is one of the major constraints. The usage of smart technologies and especially sensor systems in so-called Smart Farming Technologies can be applied to the optimization of irrigation. Regardless of the irrigation technique, soil sensors are promising in providing data that can be used to further reduce the usage of water. However, despite all these possibilities, the smallholder community are still reluctant to step into technology-based systems. There are various reasons but prohibitive cost and complexity of deployment usually appear overwhelming. The PRIMA INTEL-IRRIS project has the ambition to make digital and smart farming technologies attractive & more accessible to these communities by proposing the intelligent irrigation “in-the-box” concept. This paper describes the low-cost and full edge-IoT/AI system targeting the smallholder farmers communities and how it can provide the intelligent irrigation “in-the-box” concept.

There have been considerable changes in FIRE as a consequence of the evolving vision and the needs and interests of the industrial and scientific communities. Originally established from a core of networking testbeds and aimed at investigating fundamental issues of networking infrastructure, FIRE’s mission has changed to deliver widely reusable facilities for the Future Internet community, resulting in the current emphasis on federation. Figure 1.1 provides an overview of representative testbeds that forms the European federated ecosystem.

Gas discharge tube (GDT) is one of the most important non-linear components used in low-voltage telecom networks to provide overvoltage protection such as lightning. The efficiency of GDT is best illustrated by an impulse voltage-time characteristic. Predictable this characteristic is important because downstream equipments being protected by the GDT are typically capable of tolerating short transient overvoltages. In this paper, an experimental investigation of the impulse voltage-time characteristic of GDTs is performed. Hyperbolic and empirical models are proposed to describe the experimental results and a good agreement with experimental data is found.

This paper presents some results about the behaviour of a Gas Discharge Tube (GDT) under high surge currents. GDTs are amongst the components used to protect electrical equipment against electrical surges from atmospheric or other sources. The end-of-life of these components is an important feature for safety reasons. This paper shows that the end-of-life of GDTs depends on the type of electrical stress, which should be taken into account during the normative tests. Two normalized waveforms (8/20 mu s and 10/350 mu s) were applied to GDT. For each waveform, the resistance of the GDT to increasingly high currents was verified by measuring the static and dynamic breakdown voltages. Then, the resistance of the GDT to multiple shocks at a defined current level was also measured in the same way. It was thus possible to determine the associated destruction modes. These tests were validated for GDT which are filled with different gas pressures in order to determine the influence of the gas pressure.

Internet of Things (IoT) is one of the key technologies in the industry 4.0 era and promotes the interconnection of numerous data sources in several sectors such as ecology, agriculture, or healthcare. Meanwhile, each entity within these connected environments carries its unique requirements and individual goals. For connected environments to gain greater legitimacy among end users, service-oriented systems must adopt a new paradigm that allows end users to move from being passive consumers to actively participate in monitoring their own data at different stages of its lifecycle. In this context, a usage model based on ontological reasoning can be integrated within a data provenance mechanism to help create a trust worthy environment. In this paper, we introduce a vision for democratizing service-oriented systems. We discuss potential new directions that need to be pursued in the area of data management. Then, we review existing schemes applied in IoT data provenance and rely on the requirements to discuss their strengths and weaknesses. Finally, we summarize a number of potential solutions to direct future research.

With worldwide deployment of LoRa/LoRaWAN LPWAN networks in a large variety of applications, it is crucial to improve the robustness of LoRa channel access which is largely ALOHA-like to support environments with higher node density. This article presents extensive experiments on LoRa Channel Activity Detection and Capture Effect property in order to better understand how a competition-based channel access mechanisms can be optimized for LoRa LPWAN radio technology. In the light of these experimentation results, the contribution continues by identifying design guidelines for a channel access mechanism in LoRa and by proposing a channel access method with a lightweight collision avoidance mechanism that can operate without a reliable Clear Channel Assessment procedure. The proposed channel access mechanism has been implemented and preliminary tests show promising capabilities in increasing the Packet Delivery Rate in dense configurations.

Recently, Low-Power Wide Area Networks (LPWAN) play a key role in the Internet-of-Things (IoT) maturation process. Under the LPWAN broad term are a variety of technologies enabling power efficient wireless communication over very long distances. For instance, technologies based on ultra-narrow band modulation (UNB)–for example SigFox–or Chirp Spread Spectrum modulation (CSS)–for example LoRa–have become de facto standards in the IoT ecosystem. Given the incredible worldwide uptake of LPWAN networks for a large variety of innovative IoT applications, including multimedia sensors, it is important to understand the challenges behind large scale and dense LPWAN deployment, especially because both Sigfox and LoRa networks are currently deployed in unlicensed bands. This situation is most likely not going to change, at least in the next few years, as working in the unlicensed band allows for a much quicker uptake of the technology. This chapter has a particular focus on LoRa technology as it can be deployed in a private and ad-hoc manner, making experimental deployments much easier. Existing studies on LoRa scalability and radio channel access mechanisms for LoRa LPWAN will be reviewed and promising approaches will be presented in more details. The chapter will also provide to the readers useful information on the LoRa physical layer, as well as on promising interference mitigation techniques that can be applied such as capture effect and successive interference cancellation. The chapter will also give a large part on experimental results based on real-world deployments of both IoT test-beds and IoT production networks in the context of 3 R&D projects (2 EU H2020 projects–WAZIUP & WAZIHUB–and 1 national ANR project–PERSEPTEUR).

Self-organising is an important characteristics of wireless mesh networks, which provides high flexibility and adaptive connectivity for end users. In this study, we specifically study multicast features in wireless mesh networks to improve network capacity by taking advantage of shared links to reach simultaneously multiple users. Self-organising also provides topology control to manage the dynamic of groups where nodes can join and leave at any time. We evaluate the performance of two algorithms to dynamically create multicast groups. The first one, named Node Joining the Multicast tree, allows nodes to join the multicast tree while reducing the number of relay nodes and minimising interferences by reassignment of wireless channels. The second one, named Node Disjoining the Multicast tree, addresses the multicast tree pruning process when nodes leave the multicast tree. These two algorithms aim to optimise the performance of a multicast tree and to guaranty network connectivity by performing the required channel reassignments. These algorithms also provide an efficient mechanism for recovering from node failures. Using delay and throughput as metrics, simulation results show that the proposed algorithms are able to significantly improve throughput, delay, and robustness compared to existing multicast routing algorithms based on the static shortest multicast tree.

In a wireless network, understanding the spatiotemporal propagation of a radio signal and its attenuation over distance has always been a great concern. However, to set up an efficient network with these needs, it is imperative to have a good characterization of the signal propagation over the deployment environment. The contribution of this paper is twofold. First, we study, select and test some of existing signal propagation models on a LoRa network in order to see which model best fits LoRa signal propagation behavior. Second, we empirically optimize the best model from the first phase. The resulting model is then tested and validated in another real-world environment and compared to other models already experimented for LoRa networks. The Hata model is found in the first phase to show more accurate results and is therefore adapted using real measured data. The adapted model from Hata is then tested and validated with another and larger data set. Comparisons with Lee and Oulu models that have been used in previous real LoRa networks studies show that our adapted model can provide more accurate predictions to assist LoRa network deployment campaigns.

Wireless mesh networks are designed as an economical solution to provide high quality service for last-mile broadband Internet access. The paramount priority of these networks is the throughput maximization which is in conflict with a scarce bandwidth. Multicast is a technology that provides a good trade-off between maximizing the throughput and minimizing the bandwidth usage. This paper quantifies the reliability gain of combining classes for reliable multicast in the wireless mesh network. We define the delay as the performance metric for reliability. We then provide an analytical analysis to study the impact of group size, packet loss rate and depth of the multicast tree on the performance improvement achieved by combining classes. Our numerical results show that combining classes significantly reduces distribution delays, compared to the receiver-initiated class alone. The performance gains increase as the group size, the packet loss rate and the depth of the multicast tree increase, making the classes combination approach more scalable with respect to these parameters.

LoRa is designed for long-range communication where devices are directly connected to the gateway, which removes typically the need of constructing and maintaining a complex multi-hop network. Nonetheless, even with the advantage of penetration of walls, the range may not sometimes be sufficient. This article describes a 2-hop LoRa approach to reduce both packet losses and transmission cost. To that aim, we introduce a smart, transparent and battery-operated relay-device that can be added after a deployment campaign to seamlessly provide an extra hop between the remote devices and the gateway. Field tests were conducted to assess relays’ ability to automatically synchronize to the network without advertising their presence.

An abstract is not available.