Ad-Hoc, Mobile, and Wireless Networks

We are developing a resilient information management (RIM) system that enables people to share critical information with each other to rescue victims just after disasters have happened. The RIM system works on a locally and quickly established WiFi network environment. Thus, using this system, people can manage and share various types of information including medical information, damaged area and map information, and supply/demand information even if the Internet and communication network infrastructures have collapsed. In this paper, we introduce the concept of the RIM system and its current status with some related-technologies.

The availability of effective communications in post-disaster scenarios is key to implement emergency networks that enable the sharing of critical information and support the coordination of the emergency response. To deliver those levels of QoS suitable to these applications, it is vital to exploit the multiple communication opportunities made available by the progressive deployment of the 5G and Smart City paradigms, ranging from ad-hoc networks among smartphones and surviving IoT devices, to cellular networks but also drone-based and vehicle-based wireless access networks. Therefore, the user device should be able to opportunistically select the most convenient among them to satisfy the demands for QoS imposed by the applications and also minimize the power consumption. The driving idea of this paper is to leverage non-cooperative game theory to design such an opportunistic user association strategy in a post-disaster scenario using UAV ad-hoc networks. The adaptive game-theoretic scheme allows increasing of the QoS of the communication means by lowering the loss rate and also keeps moderate the energy consumption.

This work presents a methodology for planning and validation of AdHoc and IoT network simulator, considering congested and uncongested nodes. The validated model is specialized to consider mobile and vehicular networks (MANET and VANET), and a disaster recovery scenario is introduced. The goal is to analyze the traffic of the destination node and estimate its capacity considering an AdHoc application. Specifically, we aim to use validation to further determine the processor utilization and message delay. The proposed model and simulation tool may be used not only to plan and dimension the network but also to guide the management of the network in critical situations that can be anticipated. In addition to the MANET validation, the results showed that a Monte Carlo routing optimization (VANET case) and availability/reliability (disaster recovery case) may be relevant to the effective resource usage of the network.

Making use of reliable and precise location and tracking systems is essential to save firefighters lives during fire operations and to speed up the rescue intervention. The issue is that Global Navigation Satellite System (GNSS) (e.g., GPS and Galileo) is not always available especially in harsh wireless environments such as inside buildings and in dense forests. This is why GNSS technology needs to be combined with auxiliary sensors like inertial measurement units (IMU) and ultra-wideband (UWB) radios for ranging to enhance the availability and the accuracy of the positioning system. In this paper, we report our work in the scope of the AIOSAT (Autonomous Indoor/Outdoor Safety Tracking System) project, funded under the EU H2020 framework. In this project, the Royal Military Academy (RMA) is responsible for developing a solution to measure inter-distances between firefighters, based on IEEE Std 802.15.4 compliant UWB radios. For these inter-distance measurements, accuracy better than 50 cm is obtained with high availability and robustness. Medium access control based on time division multiple access (TDMA) mechanism is also implemented to solve the conflict to access the UWB channel. As a result, each node in a network can perform range measurements to its neighbors in less than 84 ms. In addition, in this project, we are in charge of developing a long-range narrow-band communication solution based on LoRa and Nb-IoT to report updated positions to the brigade leader and the command center.

Wireless Sensor Networks (WSNs) are useful in several application domains. They are often used for data gathering in an interested area. The popularity of WSNs is due to their ease of deployment and auto-configuration capabilities. A WSN network is composed by several sensor nodes that must cooperate and build the network where each node is in range of at least one other node. In star network topology, the sink node is in range of the all others and the communication from each node to the sink is assumed to be a single hop. So, the sink node can discover all the others nodes around it belonging to the star topology.In most cases, the network set-up phase begins with a topology discovery. One usual way for the discovery process is to allow each node to broadcast hello messages during a given period of time. When the sink located at the center of the star topology is equipped with a directional antenna, this discovery process has to be done for each beam direction of the sink antenna. In this work we are dealing with a star topology having a sink with a directional switched-beam antenna. In such case, the connectivity between the sink and other nodes is intermittent.In this paper, we present an optimized approach called WAYE that helps to reduce the network discovery time using a sink with a switched-beam antenna. The performance evaluation using Contiki Os Cooja simulator shows that the proposed approach outperforms the IEEE 802.15.4 CSMA/CA algorithm with directional and omni-directional antenna.

We describe a distributed algorithm to build a convergecast tree and a corresponding schedule for a given wireless network executing under Time Slotted Channel Hopping (TSCH). TSCH is one of the modes of operation defined in IEEE 802.15.4e and is the communication basis of current industrial wireless networks standards and the Internet of Things. In particular, the algorithm we describe is efficient, scalable, provides deterministic communication (no collisions) and is based on the Signal-to-Interference-plus-Noise-Ratio (SINR) model, currently considered the most appropriate to develop and analyze algorithms for wireless networks when interference is taken into consideration.

Industrial networks are typically used to monitor safety-related processes where high reliability and an upper bounded latency are crucial. Because of its flexibility, wireless is more and more popular, even for real-time applications. Because radio transmissions are known to be lossy, deterministic protocols have been proposed, to schedule carefully the transmissions to avoid collisions. In parallel, industrial environments now integrate mobile industrial robots to enable the Industry 4.0. Thus, the challenge consists in handling a set of mobile devices inside a static wireless network infrastructure. A mobile robot has to join the network before being able to communicate. Here, we analyze this attachment delay, comprising both the synchronization and the negotiation of dedicated cells. In particular, since the control frames (EB and 6P) have a strong impact on the convergence, our proposed model carefully integrates the collision probability of these packets. We validate the accuracy of our model, and we analyze the impact of the different EB transmission policies on the discovery delay. Our performance evaluation demonstrates the interest of using efficiently the radio resources for beacons to handle these mobiles devices.

Wireless mesh networks using IEEE 802.15.4 are getting increasingly popular for industrial applications because of low energy consumption and low maintenance costs. The IEEE 802.15.4 standard introduces DSME (Deterministic and Synchronous Multi-channel Extension). DSME uses time-slotted channel access to guarantee timely data delivery, multi-channel communication, and frequency hopping to mitigate the effects of external interferences. A distinguishing feature of DSME is its flexibility and adaptability to time-varying network traffic and to changes in the network topology. In this paper we evaluate the ability of DSME to adapt to time-varying network traffic. We examine the limits for slot allocation rates for different topologies. The evaluation is performed with openDSME, an open-source implementation of DSME.

Erraticness of the radio spectrum makes communication on wireless networks scarcely deterministic, which renders them hardly suitable for the use in application scenarios that demand high reliability, e.g., industrial wireless control systems. To counteract unpredictable phenomena like electromagnetic noise, moving obstacles, and collisions with interfering traffic, diversity in time, frequency, and space is customarily exploited.Recently, a number of solutions have appeared, possibly relying on redundant communication hardware, that combine more than one diversity scheme. In this paper, such strategies are analyzed using a simple, yet significant, mathematical model, and their performance compared to determine trade-offs between implementation complexity and the achieved level of dependability.

Cloud computing can enable the unraveling of new scientific breakthroughs. We will eventually arrive to compute overwhelmingly large sizes of information, larger than we ever thought about it. Better scheduling algorithms are the key to process Big Data. This paper presents a load balancing scheduling algorithm for Many Task Computing using the computational resources from Cloud, in order to process a huge number of tasks with a finite number of resources. As such, the algorithm can be also used for Big Data, because it scales easily for big applications if we put a load balancing algorithm on top of virtual machines. We impose an upper bound of one for the maximum nodes that can carry an arbitrary job without executing it and we show that this statement holds by simulating the algorithm in MTS2 (Many Task Scheduling Simulator). We also show that the algorithm’s overlay performs even better when there are multiple nodes and we discuss about choosing the best local scheduling policy for the working nodes.

Opportunistic networks enables the devices to communicate as and when the opportunity rises. This property of OppNets has been explored in routing approaches in a similar operating manner as the traditional infrastructure networks. Specifically, context-aware routing approaches have been the major focus of OppNets in the recent literature. However, the potential of OppNets also extends to data dissemination in destination-less networks. Forwarding approaches in such a network need context such that the data dissemination is favored without the necessity to reach a particular set of users or a particular destination. Hence, the context-awareness need to be defined differently for destination-less OppNets as compared to OppNets in destination-oriented scenarios. In this paper, we propose a mobility aided context-aware mechanism for data dissemination in destination-less OppNets based on mobility based local information available at individual nodes. The results show that the proposed approach achieves high delivery ratios as epidemic routing while reducing the overhead by 70% as compared to epidemic routing.

Cooperative diversity techniques are being used to improve the communication reliability in Wireless Sensor Networks (WSN). Typically, these techniques use relay nodes to retransmit messages that otherwise would not be heard by their destination nodes. Thus, the relay selection techniques are fundamental to improve WSN’s communication behavior. However, to perform the adequate relay selection, it is necessary to identify which are the most relevant parameters for the operation of the network and analyze their impact when used in the relay selection, that is, it is necessary to define which are the best parameters to use as selection criteria. In this context, this paper performs an analysis of the impact of each of the parameters used to perform the relay selection in the Optimized Relay Selection Technique (ORST). This analysis was assessed by simulation using the OMNeT++ tool and the WSN framework Castalia. It was considered a set of parameters, aiming to identify their relevance and possibly optimize the objective function used in this technique. Simulation results show that the objective function can be optimized considering a small number of parameters to perform the relay selection.

In this paper we address routing in the context of segmented wireless sensor networks in which a mobile entity, known as MULE, may collect data from the different subnetworks and forward it to a sink for processing. The chosen settings are inspired by the potential application of wireless sensor networks for airport surface monitoring. In such an environment, the subnetworks could take advantage of airport service vehicles, buses or even taxiing aircraft to transfer information to the sink (e.g., control tower), without interfering with the regular functioning of the airport. Generally, this kind of communication problem is addressed in the literature considering a single subsink in each subnetwork. We consider in this paper the multiple subsinks case and propose two strategies to decide when and where (to which subsink) sensor nodes should transmit their sensing data. Through a dedicated simulation model we have developed, we assess and compare the performance of both strategies in terms of packet delivery ratio, power consumption and workload balance among subsinks. This paper is an intermediate step in the research of this problem, which evidences the benefit of storing the information on the subsinks and distributing it among them before the arrival of the MULE. Based on results, we provide some information on further works.

In disruption-tolerant networking (DTN), data is transmitted in a store-carry-forward fashion from network node to network node. In this paper, we present an open source DTN implementation, called DTN7, of the recently released Bundle Protocol Version 7 (draft version 13). DTN7 is written in Go and provides features like memory safety and concurrent execution. With its modular design and interchangeable components, DTN7 facilitates DTN research and application development. Furthermore, we present results of a comparative experimental evaluation of DTN7 and other DTN systems including Serval, IBR-DTN, and Forban. Our results indicate that DTN7 is a flexible and efficient open-source multi-platform implementation of the most recent Bundle Protocol Version 7.

Low Power Wide Area Networks (LPWANs) have emerged as new networks for Internet of Things (IoT). LPWANs are characterized by long-range communications and low energy consumption. Furthermore, LPWAN technologies have a small data unit and do not provide a fragmentation mechanism. To enable these technologies to support IPv6 and, thus, be compliant with the IPv6 Maximum Transmission Unit (MTU) of 1280 bytes, the LPWAN Working Group (WG) of the Internet Engineering Task Force (IETF) has defined a new framework called Static Context Header Compression (SCHC). SCHC includes Fragmentation/Reassembly (F/R) functionality for transmitting larger packet sizes than the layer 2 MTU that the underlying LPWAN technology offers and a header compression mechanism. Moreover, SCHC defines three operational modes to perform the F/R process: No-ACK, ACK-Always and ACK-on-Error. Each mode provides different reliability levels and mechanisms. In this paper, we provide an overview of the SCHC F/R modes and evaluate their trade-offs over LoRaWAN by simulations. The analyzed parameters are the total channel occupancy, goodput and total delay at the SCHC layer. The results of our analysis show that No-ACK mode is the method with lowest total channel occupancy, highest goodput and lower total delay, but lacks a reliability mechanism. ACK-Always and ACK-on-Error modes offer the same total delay, and similar total channel occupancy, whereas ACK-on-Error offers greater goodput.

As many research papers show, one of the problems of a LoRa network is its limit regarding the scalability. However, these papers also indicate that it is possible to achieve the scalability for them by dynamically selecting transmission parameters and/or by employing multiple gateways. In this paper, we build upon the latter solution and show that although data extraction rate in such networks is quite good, it suffers hugely from data duplication on the communication path between the gateways and network server. In remote areas, the gateways are usually connected to a network server by cellular networks, which yields additional transmission costs. In LoRaWAN network topology, the gateways aren’t connected to each other and therefore cannot actively filter the traffic prior to sending it further downstream. Thus, we propose a randomized algorithm allowing to reduce duplication of the packets sent to the network server without communicating with other gateways.

The Internet of Things (IoT) has drawn an enormous attention into the scientific community thanks to unimaginable before applications newly available in everyday life. The technological landscape behind the implied surge of automated interactions among humans and machines has been shaped by plugging into the Internet very low power devices that can perform monitoring and actuation operations through very cheap circuitry. The most challenging IoT scenarios include deployments of low power devices dispersed over wide geographical areas. In such scenarios, satellites will play a key role in bridging the gap towards a pervasive IoT able to easily handle disaster recovery scenarios (earthquakes, tsunamis, and flash floods, etc.), where the presence of a resilient backhauling communications infrastructure is crucial. In these scenarios, Direct-to-Satellite IoT (DtS-IoT) connectivity is preferred as no intermediate ground gateway is required, facilitating and speeding up the deployment of wide coverage IoT infrastructure. In this work, an in-depth yet thorough survey on the state-of-the-art of DtS-IoT is presented. The available physical layer techniques specifically designed for the IoT satellite link are described, and the suitability of both the current Medium Access Control protocol and the upper layer protocols to communicate over space links will be argued. We also discuss the design of the overall satellite LEO constellation and topology to be considered in DtS-IoT networks.

Low-power wide-area networks (LPWAN) have been rapidly gaining ground in recent years, triggered by their capability to satisfy important market segments. Narrowband Internet of Things (NB-IoT) is one of the most appealing LPWAN technologies, foreseen to play an important role in the fifth generation mobile communication (5G) network. In order to guarantee a worldwide coverage to the low-cost devices distributed all over the globe, satellite connectivity is a key asset due to their large footprint on Earth, especially in remote areas where the investment towards a terrestrial infrastructure is not justified. However, such terrestrial networks aiming at deploying satellite systems either as an integrated part of it or a stand-alone solution, would require a careful and detailed analysis covering several aspects and all the layers of communication. In this paper, we demonstrate the link budgets of a satellite-based NB-IoT system under different parameters, providing some simulation results as a benchmark for further study. In addition, we analyze and discuss the impact that different power budgets would have in important features of the NB-IoT network, such as delay, capacity and device battery life.

In several application contexts, keeping transmission latencies on a wireless network bounded is required. When high bandwidth is additionally demanded, IEEE 802.11 is certainly a reasonable choice. Reliable data delivery is customarily achieved through automatic retransmission upon errors. In Wi-Fi, retries are managed in hardware by adapters. Unfortunately, this constrains the possible sequences with which messages are sent on air, which increases latency and worsens communication determinism. Previous works showed that such limitations can be overcome by having frames retransmissions managed in software by conventional user-space applications. To do so, slight modifications are needed to device drivers to provide the required functions.In this paper, a comprehensive performance analysis of software retransmission mechanisms is performed, which highlights that the related overhead is negligible when compared with the provided advantages and confirms that finely scheduling real-time traffic over Wi-Fi is actually possible. A pilot implementation showed that tangible improvements can be obtained by using a scheduling policy with packet granularity.

WiFi (IEEE 802.11 standard) networks are widely used to support real-time (RT) applications, from home environment systems to complex networked control systems (NCS). Nevertheless, the Quality of Service (QoS) extensions incorporated into the standard are still unable to guarantee some relevant RT communications requirements. This paper presents an experimental validation of the RT-WiFi architecture that was recently proposed to deal with RT communication requirements and analysed through simulation. The experimental results demonstrate the feasibility of implementing the RT-WiFi architecture and improving the QoS level of communications through a comparative analysis with the EDCA (Enhanced Distributed Channel Access) mechanism, which is a mechanism incorporated in the IEEE 802.11 standard to provide different levels of transmission priority of different types of traffic.

Wi-Fi networks often consist of several Access Points (APs) to form an Extended Service Set. These APs may interfere with each other as soon as they use the same channel or overlapping channels. A classical model to describe interference is the conflict graph. As the interference level varies in the network and in time, we consider a weighted conflict graph. In this paper, we propose a method to infer the weights of the conflict graph of a Wi-Fi network. Weights represent the proportion of activity from a neighbor detected by the Clear Channel Assessment mechanism. Our method relies on a theoretical model based on Markov networks applied to a decomposition of the original conflict graph. The input of our solution is the activity measured at each AP, measurements available in practice. The proposed method is validated through ns-3 simulations performed for different scenarios. Results show that our solution is able to accurately estimate the weights of the conflict graph.

Software-Defined Networking (SDN) is a promising approach to simplify the management of Wireless Sensor Networks (WSNs). Many SDN frameworks for WSNs have been proposed, while real-world testbeds to accelerate the development of SDN-based WSN applications are still rare. In this work, we propose SDNWisebed: an SDN-empowered WSN testbed management system that enhances the WSN management functions with a stateful Software-Defined Networking solution. This testbed was designed to evaluate various types of SDN-based WSN applications and enhance their performance, such as WSN routing protocols and network applications, before deploying them in real-world infrastructures. To validate its efficiency, we conducted both functional and performance evaluation. Real-world experiment results show that the speed of integration of new SDN applications can be improved thanks to the stateful feature awareness of SDNWisebed.

The nano terahertz networks represent one of the promising areas in the field of wireless telecommunications. Technological advances in miniaturization of antennas and terahertz communications have paved the way for new network applications such as the body network, the programmable material and multi-core processors. Some of these applications require the concentration of a very large number of tiny nodes in a limited space. In this ultra-dense context and in the absence of centralized access control units, we propose to implement a distributed strategy of spatial and temporal traffic regulation to guard against the risks of congestion, interference and energy over-consumption. In this paper, we propose a protocol for optimizing terahertz radio links using beam steering antenna, distributed time division technique and sleep mode in order to reduce the flow of redundant traffic over the network, smooth the volume of communications exchanged over time, and preserves the lifetime of the nodes.

In this study, we consider a wireless powered communication network where multiple users with radio frequency energy harvesting capabilities communicate to a hybrid energy and information access point in full duplex mode. We characterize an optimization framework for minimum length scheduling to determine the optimal rate adaptation and transmission scheduling subject to energy causality and traffic demand constraints of the users considering discrete-rate transmission model. We first formulate the problem as a mixed integer nonlinear programming problem which is hard to solve for a global optimum in polynomial-time. Then, based on an analysis on the characteristics of the optimal solution, we derive optimality conditions for rate adaptation and scheduling using which we propose a fast polynomial-time complexity heuristic algorithm. We illustrate through numerical analysis that the proposed algorithm performs very close to optimal for various network scenarios.

A single-hop beeping network is a distributed communication model in which each station can communicate with all other but only by $$1-bit$$ messages called beeps. In this paper, we focus on resolving two fundamental distributed computing issues: the naming and the counting on this model. Especially, we are interested in optimizing energy complexity and running time for those issues. Our contribution is to have design randomized algorithms with an optimal running time of $$O(n \log n)$$ and optimal $$O(\log n)$$ energy complexity whether for the naming or the counting for a single-hop beeping network of n stations.

The number of CCTV video surveillance systems has grown rapidly over the past decade. As CCTV systems are large energy consumers, the problem of optimising the energy consumption of CCTV systems is urgently needed. In this study, we analyse with mathematical models the energy balance consumption for an architecture that implements a path-by-learning prediction algorithm that predicts the path and destination of a mobile in a CCTV network in order to reduce energy consumption. This method significantly reduces the energy consumption of the CCTV system in real time. An experimental system is designed to evaluate the method and experiments are carried out to demonstrate the validity of the method. The experimental results show that the method has not only significantly improved resource use and reduced energy consumption.

In an effort to extend the lifetime and reliability of multi-hop wireless sensor networks we recently presented LoBaPS, a protocol to select opportunistic parents and achieve load balancing. This algorithm takes advantage of the wake-up radio for its ultra-low power consumption and always-on feature. Moreover, it overcomes an open problem in the routing layer: achieving both stability and efficient parent selection at the same time. However, the random load balancing strategy and the energy wastage in listening mode still limits the network lifetime. In this article, we present eLoBaPS, a significant modification of LoBaPS that distributes better the energy among the parents improving around 17% the lifetime of the network towards the ideal case. In a nutshell, the next hop is selected in a decentralized way and it is the parent that issues a shorter back-off period before attempting to retransmit. In addition, the nodes overhear all the traffic in the wake-up radio channel and adapt the protocol parameters to the current state of the battery of the neighbors. We perform simulations with a network of ContikiOS nodes running eLoBaPS, LoBaPS and W-MAC, a reference protocol that uses the wake-up radio.

Cooperative Intelligent Transport Systems (C-ITS) are a promising solution to enhance road management, traffic efficiency, fuel consumption and road safety. Green Light Optimal Speed Advisory (GLOSA) is one of the traffic efficiency ITS services that can significantly cut fuel consumption and decrease waiting time while crossing intersections. When approaching a signalized intersection, GLOSA allows to inform the driver of an advisory speed to respect in order to reach the intersection while the traffic light is green. In this paper, we propose a multiple segments approach algorithm for GLOSA that allows the driver to anticipate multiple intersections ahead and adopt a speed that allows him to cross the consecutive traffic lights while their state is green. We simulated our approach using Artery framework under realistic communication and traffic conditions based on a wireless communication simulator and a real life map. Results show that taking into account multiple intersections while adopting the speed allows the driver to better optimize the crossing of intersections. Results also show the impact of activation distance and sending frequency on each approach. We show that an activation distance of 400 m allows a significant stop time gain of about 100% for both approaches.

Context describes the status of a system and of the environment in which it operates. In context-aware systems, contextual information is obtained by monitoring the environment with various sensors. Applied to a vehicular network, the context describes the state of the network, considering its various components and requirements for running applications. The context is used by the network to decide about routing, about fault correction and about recovery and the adequacy of services. This adapts the network to changes that occur in the environment. Due to the high dynamicity of the network, context information changes frequently, and old information should no longer be used for system decisions. It is therefore important that the information collected by the context is presented, along with indications of validity time, adding quality to this information. The validity time of context information is one of the parameters that characterize Quality of Context (QoC). In this article we present a context definition for vehicular networks and QoC parameters for this context. In particular, as QoC parameters we present the validity of the status of communication between pairs of vehicles, the timeliness of this context information, and the confidence, which indicates the reliability of the context. We programmed the context conditions into a simulator to generate results. The results show the efficiency of the context and the QoS metrics, and that these metrics are applicable and provide relative reliability to the context.

Infrastructure-less communications between moving vehicles present emblematic challenges because of high node mobility and link volatility, which may harm the performances of different categories of emerging vehicular applications. In order to move data between vehicles that are not in direct communication range, several distributed routing protocols have been proposed and tested in vehicular networks, highlighting their strengths and weaknesses. Some previous works report disagreeing claims about routing protocol performances in similar vehicular scenarios. Therefore, in this work, we evaluate the performances in terms of Packet Delivery Ratio (PDR), packet delay, frame collision rate, and signaling rate of three well-known routing protocols (AODV, DSDV, and GPSR), simulating them in a realistic Manhattan scenario. Furthermore, we evaluate the impact of typical urban obstacles (e.g. buildings) on the considered performance metrics. We observed that, in the proposed urban scenario, AODV provided the best PDR, GPSR the best packet delay, and DSDV failed to provide satisfactory performances due to signaling-induced congestion. Simulations showed that considering the shadowing effects induced by the buildings in an urban scenario drastically changes the observed performances, i.e. reduces the frame collisions, decreases the PDR, and increases the packet delay.

Unmanned Aerial Vehicles (UAV) can be used to deploy communication networks by acting as access points for ground users. Taking advantage of the lightness and the high maneuverability of drones, such a network can be implemented quickly and inexpensively in situations where network infrastructures are damaged or overloaded (emergency situations), or nonexistent (wild life observation). To mitigate these issues, an off-loading network based on UAVs carrying radio access points was proposed in our previous work. The goal is to temporarily provide multiple services, voice, video, data, etc., over a specific zone.The design of the aerial network was formulated as a self-deployment method built on a Coulomb’s law analogy where users and UAVs act as electrical charges. In this paper, we go beyond the proposed scheme by considering a multi-channel model taking into account the interference. We set up association and channel switching schemes that boost the overall performance of the network.

Wireless Body Area Networks (WBAN) open an interdisciplinary area within Wireless Sensor Networks (WSN) research, with a tremendous impact in healthcare area where sensors are used to monitor, collect and transmit biological parameters of the human body. We propose the first network-MAC cross-layer broadcast protocol in WBAN. Our protocol, evaluated in the OMNET++ simulator enriched with a realistic human body mobility and channel model issued from a recent research on biomedical and health informatics, outperforms existing flat broadcast strategies in terms of network coverage, sensors energy consumption and correct reception of FIFO-ordered packets. We investigate the resilience of both existing flat broadcast strategies and our new cross-layer protocol face to various transmission rates and human body mobility. Existing flat broadcast strategies, without exception, start to have a drastic drop of performance for transmission rates above 11 Kb/s while our cross-layer protocol maintains its good performance for transmission rates up to 190 Kb/s.

Wireless Body Area Networks (WBANs), designed especially for healthcare applications require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Generally, medical applications have different kinds of data traffic which may be classified into periodic, urgent or on-demand. Each type has its own requirements and constraints. The IEEE 802.15.6 WBAN specific standard, designed especially to handle healthcare applications, proposes different channel access mechanisms and superframe structures but does not specify how to handle the different types of medical traffic. The present paper describes MTM-MAC protocol, a new traffic aware MAC protocol which adapts the IEEE 8021.15.6 and exploit network context-awareness to satisfy the specific requirements of each traffic type. Through simulations, the proposed protocol proved its efficiency in comparison with IEEE 802.15.6 in terms of delay, energy and throughput.

The growth of the Internet of Things (IoT) is raising significant impact in several contexts, e.g., in cities, at home, and even attached to the human body. This digital transformation is happening at a high pace and causing a great impact in our daily lives, namely in our attempt to make cities smarter in an attempt to increase their efficiency while reducing costs and increasing safety. However, this effort is being supported by the massive deployment of sensors throughout cities worldwide, leading to increase concerns regarding security and privacy. While some of these issues have already been tackled, device authentication remains without a viable solution, specially when considering a resilient decentralized approach that is the most suitable for this scenario, as it avoids some issues related to centralization, e.g., censorship and data leakage or profit from corporations. The provisioning is usually an arduous task that encompasses device configuration, including identity and key provisioning. Given the potential large number of devices, this process must be scalable and semi-autonomous, at least. This work presents a novel approach for provisioning IoT devices that adopts an architecture where other device acts as a manager that represents a CA, allowing it to be switched on/off during the provisioning phase to reduce single point of failure (SPOF) problems. Our solution combines One Time Password (OTP) on a secure token and cryptographic algorithms on a hybrid authentication system.

The number of connected Things is growing at a frantic pace, which has led to vertical, proprietary Internet of Things (IoT) solutions. To ensure a horizontal IoT cross-industry interoperability, eight of the word’s leading ICT standards bodies introduce the oneM2M standard. Its main goal is to satisfy the need for a common M2M Service Layer that guarantees the communication between heterogeneous devices and applications. Various security mechanisms have been proposed in the oneM2M specifications to protect the IoT solutions. As a complementary security level, we propose the first generic Intrusion Detection System (IDS) for the oneM2M Service Layer based on Edge Machine Leaning (ML). This oneM2M-IDS can be added to the basic architecture of oneM2M or can be added as a plugin to existing systems based on oneM2M. In this work, we define and implement oneM2M attack scenarios related to the service availability. Moreover, we propose an edge IDS architecture and we detail ML features selection. The performance of the proposed IDS is studied through multiple experiments with different ML algorithms.

Internet of Things (IoT) refers to business process and applications of sensed data, information and content generated from interconnected world by means of connected devices that exist in the Internet infrastructure. Every day thousands of additional devices are connected to the Internet. The rapid growth of connected devices to the Internet as well as adoption of IoT technology across business sectors have led to a careful study and development of technical standards. IoT success is highly dependent on the elaboration of inter-operable global standards within and across application domains. For example, common language (vocabulary) and standard reference architecture are a prerequisite to develop cost-effective business solutions and enable cooperation between various applications, to cover a wide range of disciplines. This paper intends to summarize the major efforts of Standards Development Organizations (SDOs) and alliances towards IoT technical standardization. In particular, it identifies the implementation challenges in IoT ecosystem mainly from the perspective of technical, business, and societal. Then, it provides the level of focus of major SDOs and alliances in IoT related technical standardization on identified areas of challenges.

Satellite communication systems are a promising solution to extend and complement terrestrial communication networks in un-served or remote area. This aspect is reflected by recent commercial and standardisation endeavours. In particular, 3GPP recently initiated a study item for new radio-based, i.e. 5G, non-terrestrial communication networks aimed at deploying satellite systems to integrate with terrestrial networks in mobile broadband and machine-type communication scenarios. In this context, employing a constellation of small satellites in Low Earth Orbit (LEO) adsorbs lots of attractions duo to their ability to provide cost-efficient communications with lower service latency compared to traditional geostationary satellite networks. Here, we aim at showing the potential of our new constellation of BroadBand GomSpace (GOMBB) LEO satellites which are able to integrate by future terrestrial communication networks, i.e. 5G and beyond.

The relentless growth of the human population over the time is driving an exceptional rise in food demand. Improving the efficiency of farming processes is the only way to face the so called Malthusian catastrophe. This objective could be pursued by automating production processes in farms. Robots can play a key role in this context, especially when they can execute tasks on collaborative basis. At the same time, low latency communication capabilities are required to translate in reality the robotic-aided smart agriculture vision. This contribution explores the interplay of 5G, Internet of Things (IoT), and Mobile Edge Computing (MEC) as enabling drivers for technology spread in the agriculture domain, based on Industry 4.0 principles. In particular, some key performance indicators have been investigated for a rural-area scenario, exploring different technological configurations.

Weather-based forecasting models play a major role in agricultural decision support systems but warnings are usually computed at regional level due to a limited amount of automatic weather stations. Farmers have to refer to the nearest AWS but recommendations are not always adapted to their situation. Agromet project aims to set up an operational web-platform designed for real-time agro-meteorological data dissemination at high spatial (1 km × 1 km grid) and temporal (hourly) resolution in Wallonia, southern part of Belgium. This paper focuses on the interpolation of hourly temperature and daily maximum temperature. Five learners are tested: multilinear regression, inverse distance weighted, one nearest neighbor, ordinary kriging and kriging with external drift. All interpolation methods except ordinary kriging perform better than taking the nearest station to predict air temperature. Multilinear regression is the best one. The size of the dataset is a limit to data interpolation. IoT is an opportunity to improve the quality of the interpolated data by increasing the size of our training dataset. Either by developing our own low price and robust sensors to measure air temperature and humidity or by exploiting data measured by non-meteorological devices monitoring temperature (e.g. tractors or cars).

Over the past decade, Luxembourg has experienced an increase in extreme precipitation events during the summer season. As a direct consequence of this evolution, increasingly flashy hydrological responses have been observed in the river network – eventually leading to several flash flood events. In an area that has been historically prone to large scale winter floods, the current flood forecasting and monitoring chain is not adapted to this specific type of events, characterized by small spatial extents (<200 km2), short time scales (<6 h) and high magnitudes. The SIGFOX network deployed in Luxembourg since 2016 provides a unique opportunity to leverage the potential for a Low-Power Wide-Area Network (LPWAN) to implement and operate a hydro-meteorological monitoring system of unprecedented spatial and temporal density. The restricted message size (12 bytes) supported by this technology is suited for the small data sets that are to be transmitted from each monitored hydro-meteorological site. In addition, the inter-connection of the different sensing devices allows for an immediate adaptation of the data acquisition and transmission frequencies – according to rapidly changing hydro-meteorological states. The entire network is able to switch from a sleep and low power consumption mode to a warning mode, with high frequency recordings and transmissions. The initial limit of 140 daily transmissions is eventually compensated for by a systematic compression of the numeric data on the one hand and the switch to cellular transmission during flash flood warning mode. Here we present the prototype implemented in the Ernz Blanche catchment (102 km2), which was successively exposed to flash flood events in 2016 and 2018. The overall set-up consists of 4 raingauges, 4 streamgauges, and 4 soil moisture sensors. The first three months of operation of the prototype monitoring and transmission system on the Ernz Blanche catchment are assessed for validating the data transmission, acquisition, and emergency warning system.

We address the problem of defining a wireless sensor network by deploying sensors with the aim of guaranteeing the coverage of the area and the connectivity among the sensors. The wireless sensor networks are widely studied since they provide several services, e.g., environmental monitoring and target tracking. We consider several typologies of sensors characterized by different sensing and connectivity ranges. A cost is associated with each typology of sensors. In particular, the higher the sensing and connectivity ranges, the higher the cost. We formulate the problem of deploying sensors at minimum cost such that each sensor is connected to a base station with either a one- or a multi-hop and the area is full covered. We present preliminary computational results by solving the proposed mathematical model, on several instances. We provide a simulation-based analysis of the performances of such a deployment from the routing perspective.

Unmanned Aerial Vehicles (UAVs) based systems are a suitable solution for monitoring, more particularly for traffic monitoring. The mobility, the low cost, and the broad view range of UAVs make them an attractive solution for traffic monitoring of city roads. UAVs are used to collect and send information about vehicles and unusual events to a traffic processing center, for traffic regulation. Existing UAVs based systems use only one UAV with a fixed trajectory. In this paper, we are using multiple cooperative UAVs to monitor the road traffic. This approach is based on adaptive UAVs trajectories, adjusted by moving points in UAVs fields of view. We introduced a learning phase to search for events locations with a frequent occurrence and to place UAVs above those locations. Our approach allows the detection of a lot of events and permits the reduction of UAVs energy consumption.

Even before 5G is rolled out, Mobile Edge Computing (MEC) can be considered as a key driver towards the deployment of vehicular use cases, which pose stringent latency and bandwidth requirements to the underlying Vehicle-to-Everything (V2X) communication infrastructure. In this paper, we present a MEC-enabled cooperative Collision AVoidance (CAV) service designed to anticipate the detection and localization of road hazards by extending vehicles’ perception range beyond the capabilities of their own sensors. The CAV service is a software application that runs on MEC servers allocated at the roadside and at Mobile Network Operators’ (MNO) infrastructures. The CAV service receives ETSI ITS-G5 standard-compliant messages transmitted by vehicles: periodic Cooperative Awareness Messages (CAM), which include the position, velocity and direction of the vehicle; and event-triggered Decentralized Environmental Notification Messages (DENM), which include the position of detected road hazards. The CAV service creates a distributed dynamic map using all the received information, and sends unicast messages to each vehicle with the relevant information within its collision risk area. We have implemented and validated the operation of the CAV service using vehicles’ On-Board Units (OBU) based on OpenC2X, an open-source experimental platform supporting the ETSI ITS-G5 standard.

Networks of sensors are key components of an Internet of Things. This paper outlines a demonstration of a wireless technology called LoRa/LoRaWAN that may be used to network sensors over a range of several kilometers. LoRa is an example of a Low Power Wide Area Network (LPWAN) and features hardware, software and network protocols especially designed to achieve wide area coverage with exceptionally low power consumption. However, these features constrain effective data rate and multiplexing capabilities. Our demonstration applies LoRa to an Environment Monitoring and Electrical Power System application where these tradeoffs are justified.

In the immediate aftermath of nature-based disasters such as earthquakes, fires, or floods, have a clear vision of the situation and the population involved is of main priority for rescue operations—it is a matter of life and death. But these disaster events may cause malfunctions in communication services making the exchange information impossible—the experienced delay sending a message in an overcrowded area is a shred of evidence.In this demo, we introduce Floater, a mobile awareness-based communication application for the immediate aftermath of a disaster, when ad hoc infrastructure support has not been deployed yet. Floater enables communications between peers in a common area without requiring the support of a cellular network. The application is developed for Android and it does not require an account or an Internet connection. Floater exploits local knowledge and constraints opportunistic replication (peer to peer) of information to build a global view of the involved area efficiently.The app is the first to implement Floating Content, an infrastructure-less communication paradigm based on opportunistic replication of a piece of content in a geographically constrained location and for a limited amount of time.The demo illustrates the feasibility and the main functionalities of Floater and presents disaster assistance use cases for supporting rescue operations.

The fast growing number of low earth orbit exploitation and deep space missions results in enormous volumes of telemetry data. In order to operate efficiently satellites constellations as well as spacecrafts, DMSS offers a self-learning visual platform for anomaly detection in telemetry data coming from embedded sensors. As use-case, the data of two space missions operated by the European Space Agency were analyzed: Mars Express and GAIA.

A problem of the sensor network lifetime maximization is typically solved for a fixed temperature, which means that the sensor battery performance is constant over the network time. However, networks usually have to operate in the varying temperature conditions, for example, outdoors, or in unheated rooms. The operating temperature variations influence network lifetime. Notably, sensors may discharge faster in temperatures below the one determined at the planning stage. Thus, the network cannot guarantee the required level of coverage over its entire lifetime. In this paper, we test network lifetime for the systems operating in conditions typical for the moderate climate zone in February and March. We also propose a method of the sensor schedule adaptation to the varying temperature conditions. The results show that appropriate rearrangement of slots in a schedule may significantly decrease the schedule corruption caused by the premature discharge of the sensors.