Wireless Sensor Networks (WSN) are considered to be a key enabler towards the Internet of Things (IoT) concept and one of its main underlying technologies. Applications built on top of IoT infrastructures such as WSNs share a set of common functions that concern not only data management such as data collection, dissemination or aggregation, but also classical networking functions, such as routing or addressing. Even though application deployment is becoming more feasible, it can still be a complex process especially in the presence of vertical solutions. WSNs should, therefore, be more flexible in order to facilitate the development of efficient applications. A promising networking paradigm which can help achieve such a requirement is the Software-Defined Networking (SDN) concept which decouples the network data plane from the control plane. To allow multiple applications to share and reuse common networking functions, we propose to implement them as SDN reusable building blocks and to instantiate and customize them through SDN rules. On the other hand, we provide a rigorous definition of these functions and of their relationships in order to make them reusable to efficiently develop the applications. We consider the smart city as a typical WSN/IoT domain of applications. Our approach aims at facilitating the development, use and management of such functions in a WSN and thus of IoT applications.

With network slicing, Mobile Network Operators can accommodate on a common network infrastructure various customized services from Service Providers (SPs). Usually, the Service Function Chains belonging to a slice are deployed on a best-effort basis. Nothing ensures that enough infrastructure resources can be allocated to satisfy the demands of SPs. This paper introduces a radio resources provisioning approach to satisfy the demands of slices with radio coverage constraints. By provisioning, we ensure that enough resources are reserved for further SFC deployment. Numerical results show the effectiveness of the proposed provisioning framework for a slice deployment on a mobile network infrastructure satisfying a minimum data rate for users in the geographical areas where services have to be made available.

With network slicing in 5G networks, Mobile Network Operators can create various slices for Service Providers (SPs) to accommodate customized services. Usually, the various Service Function Chains (SFCs) belonging to a slice are deployed on a best-effort basis. Nothing ensures that the Infrastructure Provider (InP) will be able to allocate enough resources to cope with the increasing demands of some SP. Moreover, in many situations, slices have to be deployed over some geographical area: coverage as well as minimum per-user rate constraints have then to be taken into account. This paper takes the InP perspective and proposes a slice resource provisioning approach to cope with multiple slice demands in terms of computing, storage, coverage, and rate constraints. The resource requirements of the various SFCs within a slice are aggregated within a graph of Slice Resource Demands (SRD). Infrastructure nodes and links have then to be provisioned so as to satisfy all SRDs. This problem leads to a Mixed Integer Linear Programming formulation. A two-step approach is considered, with several variants, depending on whether the constraints of each slice to be provisioned are taken into account sequentially or jointly. Once provisioning has been performed, any slice deployment strategy may be considered on the reduced-size infrastructure graph on which resources have been provisioned. Simulation results demonstrate the effectiveness of the proposed approach compared to a more classical direct slice embedding approach.

Broadcast traffic in IEEE 802.11 vehicular networks is known to suffer from poor performance due to the lack of recovery mechanisms from packet losses, based on the rules of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. This may have a detrimental impact on cooperative vehicular safety applications that build on the reliable regular broadcasting of status messages by vehicles in a local neighborhood. Full-Duplex (FD) techniques can improve the broadcast CSMA/CA performance by letting a sending vehicle sense the channel while transmitting, thus enabling “collision detection”. The vehicle, consequently, can abort the packet prone to collision and reattempt a later transmission. In this paper, we define a stochastic geometry model that captures the collision detection capability of FD-enabled vehicles, while accurately characterizing the interference power generated by other vehicles on a road segment, and the dynamics of the backoff mechanism used for broadcast packet retransmissions. The model provides helpful insights into the FD broadcast CSMA/CA behaviour, highlighting a clear relationship between the settings for the carrier sense threshold and the collision detection threshold and the number of covered receivers on the road.

With the increasing number of WLAN devices and application hungry resource demands, infrastructure mode WLAN networks are becoming denser and form a multi cell network. In this context, the clients should associate to one of the available Access Points (APs). The IEEE 802.11 standard association, based on the strongest RSSI (Received Signal Strength Indicator) AP, shows limited performance and does not take into account client priority levels and traffic demands. The aim of this paper is to propose jointly an offline association and resources sharing scheme implanted at a SDN central controller of a multirate WLAN. Our goal is to take into account the clients different priorities and bandwidth demands. The simulation results shown enhancements in clients satisfaction specially for the higher priority ones.

Emergent WLAN applications demand more and more network resources. At the same time, the increasing number of users leads to dense WLAN networks. In this context, the standard client-Access Point association has been shown to reach far from optimal performance. Thanks to the SDN paradigm, centralised programmable strategies could be applied by the WLAN controllers to choose the best Access Point for each user when many Access Points are in the vicinity of a user. In this paper, we present an on-line centralized client-Access Point association scheme based on reinforcement learning which aims at minimizing the clients dissatisfaction in terms of obtained rate. The scheme is implemented in a SDN controller which pilots the Access Points. Simulation results show the superiority of our scheme over the IEEE standard signal strength based association in terms of aggregated throughput and users satisfaction.

Wide white areas are defined as large regions with little or no infrastructure such as deserts or large forest areas. Indeed, strategic phenomena and activities take place in these areas which necessitate data collection and analysis. However, the difficulty of access and the vastness of wide white area make the deployment of such networks hard and inefficient. In this work, we propose a new approach which aims at efficiently collecting data from networks deployed in wide white areas. The goal of our method is to improve data collection efficiency by maximizing the amount of the collected data. The proposed method uses commercial flights to collect data while they cross over an area of interest. We investigate the feasibility of such a scheme by determining the collection capacity of commercial aircrafts in different locations of the desert.

Network slicing has recently appeared as a key enabler for the future 5G networks where Mobile Network Operators (MNO) create various slices for Service Providers (SP) to accommodate customized services. As network slices are operated on a common network infrastructure owned by some Infrastructure Provider (InP), sharing the resources across a set of network slices is highly important for future deployment. In this paper, taking the InP perspective, we propose an optimization framework for slice resource provisioning addressing multiple slice demands in terms of computing, storage, and wireless capacity. We assume that the aggregated resource requirements of the various Service Function Chains to be deployed within a slice may be represented by a graph of slice resource demands. Infrastructure nodes and links have then to be provisioned so as to satisfy these resource demands. A Mixed Integer Linear Programming formulation is considered to address this problem. A realistic use case of slices deployment over a mobile access network is then considered. Simulation results demonstrate the effectiveness of the proposed framework for network slice provisioning.

Wide white areas are defined as large regions with very little to no infrastructure. For example, deserts and large forest areas fall in this category. Many strategic phenomena and activities take place in these areas (e.g. mining, environmental monitoring) which necessitate data collection and analysis. In this context, we propose a network deployment scheme which aims at efficiently linking sparse points of interest in a very wide white area. The goal of the method is to minimize the cost of the deployment while providing a fault tolerant network. The proposed method is based on an algorithm which mimics the evolution of a type of mold called physarum. Our deployment problem is close to a Minimum Steiner Tree (MST) problem known to be NP-hard, we thus compare our results to a heuristic of MST.

Road safety applications heavily rely on periodic message exchanges known as beaconing in order to gain awareness about the current situation within the vehicle communication range. The high level of transmission contention in dense vehicular networks can induce successive beacon collisions. These collisions impede the vehicles to have an up-to-date view of the environment which can lead to bad decisions from the applications and in the worst case create car crashes. Many propositions of the literature try to tackle this problem by modifying the beacon emission period and/or power either randomly or based on the network density or other measured indicators. In this paper, we explore the possibility to use bio-inspired desynchronization algorithms to avoid beacon collisions. The main idea behind these algorithms is to make nodes converging toward a consensus where they do not emit their beacon at the same time in order to avoid collisions. We show that desynchronization algorithms, if properly implemented, can significantly reduce the probability to have large inter-beacon delays.

Large scale ad hoc networks such as Wireless Sensor Networks are more and more deployed to ensure critical missions (such as forest fire detection, intrusion detection, etc). Critical applications require timeliness and reliability because human lives may depend on it. In order to give the strongest possible guaranties, the fulfillment of the timing requirements must be formally verified. In the literature, mainly two approaches are used for the formal verification of WSNs real-time protocols: Model Checking which consists in an exhaustive exploration of the behaviors of the system and Network Calculus which abstracts the elements of the system with compos able mathematical functions. The Model Checking solution suffers from the combinatorial explosion problem which prevents from verifying large scale systems. On the contrary, Network Calculus scales well, but the abstraction made when defining the service curve is often made without proof that it actually corresponds to the worst case of the considered protocol. In this paper we propose a verification technique which takes advantage of the exhaustiveness of the Model Checking and the scalability of the Network Calculus. The Model Checking technique being used at the scale of a node in order to verify its behavior and the Network Calculus at the scale of the network to represent the interactions of every node with the rest of the network. We use the UPPAAL model checker and Sensor Network Calculus and apply our method to a WSN real-time protocol in order to evaluate the performance of the method.

Wireless Sensor Networks (WSNs) anomaly detection applications aim at identifying events which occur in a monitored area. Forest fire, landslide or intrusion detection are some examples. In order to perform anomaly detection, wireless sensors are deployed in the area of interest and the nodes monitor a physical parameter. If this parameter exceeds a predefined threshold, the node generates an alarm and sends it in direction of the collection point (the sink). In some cases, the anomaly can span over several nodes, so each of the nodes produces one alarm, resulting in several alarms sent for the same event. These alarms are produced and sent in a very short amount of time, this phenomenon is called alarm storm and causes network congestion, collisions and increases the energy consumption. In this paper, we propose a mechanism which allows to reduce the number of redundant alarms. The proposed mechanism consists in a competition among nodes sensing the anomaly, which aims at determining the node which is the better located to actually send the alarm. The proposed mechanism is evaluated by extensive simulations, the results show that the scheme is able to reduce drastically the number of redundant alarms while not interfering on the MAC and routing processes which guarantee timeliness and reliability to anomaly detection applications.

Along with the development of cognitive radio networks, designing optimistic security mechanisms is becoming a big challenge. This study proposes a taxonomy of attacks on cognitive radio networks. This will help researches to better understand the security problems and to design more optimistic countermeasures. A new simulation framework for security threats has been developed to check all these attacks and countermeasures. The simulation framework has been tested with a primary user emulation attack. A new testbed for simulations suitable for cognitive radio security is ready.