This paper proposes a novel blockchain-based framework for securing vehicular networks against Sybil attacks while maintaining scalability, decentralization, and privacy. The system leverages dynamic Proof of Location (PoL) in a game-theoretic setting, where vehicles self-organize into groups and elect leaders who set PoL parameters based on traffic conditions. We implement a realistic Sybil attack in NS-3 and show that the framework adaptively tunes PoL difficulty, beacon count (NBea), and required witness signatures (NSig) according to vehicular density and trust scores, modeled via a Bayesian–Stackelberg game. Vehicles build communication graphs from PoL interactions and forward them to RSUs, which apply spectral clustering to separate benign from Sybil-controlled groups. Our evaluation highlights the interplay between latency, TPS, and the blockchain trilemma, and across three urban scenarios (dense urban, medium-sized city, and closed test circuit) confirms resilience to Sybil infiltration. Results further show that inter-vehicle distance and communication quality dominate Sybil detectability, while adaptive thresholds sustain high TPS with bounded latency under varying load conditions.

International audience

False emergency messages, a critical variant of False Data Injection Attacks (FDIAs) in Vehicular Ad Hoc Networks (VANETs), pose severe threats to traffic safety and undermine the reliability of intelligent transportation systems. Existing detection approaches often rely on macroscopic traffic models to validate the reported incidents. However, such models overlook the localized driving behaviors and fail to capture fine-grained dependencies between vehicles and events. To overcome these limitations, we introduce a spatio-temporal detection framework based on Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. The GCN component learns spatial interactions among vehicles relative to a reported incident, while the LSTM models the temporal dynamics of their behavioral evolution. Extensive simulations show that our framework consistently outperforms state-of-the-art baselines, demonstrating the importance of microscopic, context-aware traffic modeling for reliable FDIA detection in dynamic VANET environments.

Accurate environmental perception is crucial for the safe and efficient navigation of autonomous vehicles. Integrating data from various sensors, such as cameras, radars, and lidars, presents challenges due to differing sensor reliability and environmental conditions. This study introduces a new method for combining data from multiple sensors using evidence theory (Dempster-Shafer), which helps to address uncertainties and conflicting information. By dynamically merging sensor inputs and resolving conflicts, our model improves object detection and classification in uncertain situations. Through extensive simulations and detailed analyses using metrics like Belief (Bel), Plausibility (Pl), Confidence Interval (CI), and Pignistic Probability (P), the study confirms the effectiveness and dependability of this fusion approach for practical autonomous vehicle applications.

To address the growing challenges of road safety, efficiency, and environmental sustainability, Cooperative, Connected, and Automated Mobility (CCAM) leverages advanced communication and automation technologies across road networks. In Europe, Cooperative Intelligent Transportation Systems (C-ITS) facilitate communication among vehicles, infrastructure, and other entities, enhancing situational awareness and safety. Cooperative Awareness Messages (CAMs) provide continuous status information-such as vehicle position, speed, and direction-to nearby vehicles and infrastructure. Vehicles send CAMs to other vehicles at high frequencies ($1-10 \text{Hz}$), which, especially in dense networks, risks overloading communication channels. This may degrade network performance and potentially reduce the effectiveness of road safety applications. In this paper, we propose a new deep learning-based communication mechanism to reduce the risk of channel overload in C-ITS. Our approach enables nearby vehicles to form a temporary trust group valid for a specified period. During this period, vehicles initially send CAMs at a frequency of 1 Hz. Then, each vehicle predicts the subsequent messages of its neighbors using a variational autoencoder. Next, vehicles periodically verify the predicted CAMs by sending actual CAMs. This process ensures prediction reliability and reduces channel load by allowing vehicles to decrease CAM transmissions. We validated our approach in a simulation environment (using Omnet++, Sumo, and Artery) demonstrating its effectiveness in maintaining road safety, while reducing communication overhead.

This paper introduces a novel localization framework for GPS-denied environments, leveraging reflective QR codes, multi-sensor fusion, and V2X communication. The system integrates LiDAR-detectable QR codes encrypted with GPS coordinates, dead reckoning, and V2X data sharing to enhance localization accuracy in challenging conditions such as tunnels. A factor graph-based optimization fuses data from IMU, QR code detections, and V2X communication to ensure robustness. Experimental results demonstrate significant localization accuracy improvements over conventional methods, reducing position errors while maintaining reliable performance in lowlight conditions. The proposed approach offers a scalable and secure solution for autonomous vehicle localization, ensuring continuous operation and data integrity through end-to-end encryption.

International audience

Connected and Automated Mobility (CCAM) is undergoing a paradigm shift, with safety and efficiency increasingly dependent on connectivity. Cooperative Intelligent Transport Systems (C-ITS) support this transformation by enabling the exchange of Cooperative Awareness Messages (CAMs) between vehicles and roadside infrastructure. These messages, transmitted periodically at$\text{1 - 1 0 ~ H z}$, must be digitally signed in compliance with ETSI standards using Pseudonym Certificates (PCs). However, this security process introduces a significant overhead, as the size of the security data can be up to three times larger than the CAM payload, thereby consuming a considerable portion of the communication channel bandwidth. In this paper we propose a new authentication scheme based on deep learning. Instead of exchanging signed CAMs every time, the vehicles will authenticate each other once to establish cluster-based trust relationships, and then they will exchange only unsigned CAMs during the cluster lifetime. To ensure security within the cluster, an unsupervised variational autoencoder analyzes vehicle behavior to detect anomalies and confirm that each vehicle remains the same entity originally authenticated. Through simulations using OMNeT++, SUMO, and Artery, our method achieved a$\text{48.9 \%}$reduction in the volume of messages exchanged between vehicles, significantly decreasing communication channel overhead.

ECHO is a next-generation advanced driverassistance system (ADAS) that integrates multi-modal perception, cooperative V2X communication, and an agentic large language model (LLM) for explainable, human-centric support. Unlike traditional ADAS, ECHO does not directly control the vehicle but interprets real-time data from sensors, infrastructure, and driver state, producing transparent natural language guidance and standardized V2X intent messages. Extensive evaluation in both simulation and real-world settings shows that ECHO reduces reaction times to V2X events by over 40 %, decreases near-miss incidents by 60 %, and significantly enhances cooperative maneuver success compared to conventional ADAS. These results demonstrate the potential of agentic, explainable AI to advance connected mobility with improved safety, trust, and driver engagement.

This paper presents a novel localization approach that enhances accuracy and reduces error drift by integrating High Definition (HD) maps with multi-sensor data. Leveraging LiDAR and GPS data, our method cross-references detected physical landmarks with HD maps to improve precision. When sensor data is obstructed, Vehicle-to-Infrastructure (V2I) communication ensures continued accuracy. This hybrid approach significantly improves localization, especially in autonomous driving and urban planning. Our solution sets a new standard for real-time localization, enhancing the safety and efficiency of autonomous vehicle operations.

Toll management systems have a vital role in facilitating smooth and effective traffic flow at toll stations. To this end, numerous use cases have been explored to guide and detect vehicles at toll stations. This paper presents the results of a study conducted on a testbed as part of the European project InDiD. By utilizing more robust technologies, our work aims to enhance a specific use case explored within this project. Leveraging the resources of the APRR (Autoroute Paris-Rhin-Rhône enhanced) Cooperative Intelligent Transportation System (C-ITS) testbed, we did two experiments to assess the use of two technologies in improving vehicles orientation while approaching a toll station. The first one featured an upgraded vehicular communication network, incorporating both ITS-G5 and LTE-UU to improve the reliability of the vehicular communications. The subsequent one integrated computational power directly onto the vehicle (vMEC) to compare it with the use of an edge computing resource. The results show an improvement in reliability, a coverage extension, and a favorable latency tradeoff when using the vMEC. Additionally, we closely monitored the downlink resource consumption while employing hybrid communication.

The implication of cyber-physical systems into industrial processes has introduced some security breaches due to the lack of security mechanisms. This article aims to come up with a novel methodology to detect false data injection attacks on cyber-physical systems. To reach this goal, we propose an efficient anomaly-based approach for detecting false data injection attacks against industrial cyber-physical systems. Particularly, we use sequential pattern mining techniques, which are commonly used for learning most important patterns of a system. In our case, the frequent pattern learning algorithm is used to create a database corresponding to the normal operation of the system, then, this database is fed into an attack detection algorithm in order to alert the user whenever an attack is occurring. The extensive simulations prove that our attack detection approach is able to detect attacks with a great accuracy and that this methodology could work even for large scale systems.

Today’s cellular networks (known as 2G, 3G, and 4G) provide a solid foundation for connecting things. The Internet of Things (IoT) is helping people live and work smarter and take full control of their lives. In addition to providing smart devices for home automation, IoT is also critical for businesses. The security of classical cryptosystems is characterized by their simple arithmetic complexity. This type uses; shifts, arrangements, permutations, and substitutions of letters, words, or phrases to encrypt a given message. Moreover, this kind of cryptosystem is easy to break, because the complexity of their scheme is convergent. On the other hand, the security of modern cryptosystems is characterized by complex arithmetic, using the concept of keys; private keys to encrypt and public keys to decrypt. This type is hard to break because of the complexity of their scheme being divergent. This paper aims to secure the 5G networks with a new variant of the classical Polybius Checkerboard Cipher (HPCC). The system of letter substitution is based on the complexity and the divergence of private key generation. Filling a magic square with primes is an NP-hard task, which shows the complexity and divergence of the strategy adopted in this variant.

Cyber-physical industrial systems are internet-enabled physical entities embedded with computers and control components consisting of sensors and actuators. However, inter-connecting the cyber and physical spaces led to new security challenges. This paper presents a recovery controller based on a physics-informed neural network (PINN) to enhance the resilience of cyber-physical systems (CPS) against false data injection attacks (FDIA). The PINN-based controller is trained to predict corrective actions that can restore the desired operating conditions of the CPS after an attack. The proposed approach is validated on a quadruple water tank process, a benchmark system for CPS control. Results show that the PINN-based recovery controller can effectively restore the system's desired operating conditions, outperforming conventional recovery controllers that do not incorporate the physical dynamics of the CPS in their design.

Cooperative Intelligent Transport Systems (C-ITS) are very important in our daily lives. They ensure road safety through the exchange of data between vehicles and road side units (RSU). Due to the sensitivity of the exchanged data between different entities, C-ITS systems are vulnerable to Cyber-attacks, they require high protection. In order to guarantee the integrity and the authentication of the exchanged messages, the European Telecommunications Standards Institute (ETSI), has specified specific procedures to manage certificates and signatures of all sent messages. Each vehicle periodically sends signed CAMs. Then, the integration of the signature and certificate in each transmitted CAM has a considerable impact on the communication channel load and bandwidth. In this study, we propose a new lightweight authentication mechanism which considers that vehicles on road are composed of a set of clusters having different sizes. The clusters are dynamic and change continuously. In each cluster, we implement some procedures in order to reach a trusted environment where vehicles communicate with unsigned messages when they trust their neighbours. When the trust is not guaranteed, vehicles switch to the standard communication until trust recovery. In order to reach the trust, each vehicle computes its own prediction of neighbours behavior. based on trajectory, speed. The prediction is performed using an auto-encoder running the LTSM algorithm. We have implemented this mechanisms on the OMNET++ environment and we have concluded that our mechanisms reduce the overhead generated by the authentication algorithms around 34% of the size of exchanged messages.

The development of autonomous vehicles has garnered significant attention in recent years due to its potential to revolutionize the way we move and its impact on society, security, and the environment. One of the crucial components of these vehicles is the object detection system, responsible for identifying and localizing objects in the road environment. This task is essential for decision-making processes in autonomous vehicles, such as navigating the vehicle, avoiding obstacles, and changing the driving direction.Despite the challenges posed by the variability of objects in the road environment, this paper proposes a system for autonomous vehicle guidance based on embedded systems and the RTMAPS tool. The primary focus of the system is to perform effective object detection.To achieve this objective, the study evaluates several stateof-the-art algorithms for 2D object detection and selects the best algorithms based on precision and inference time. The selected algorithm is then implemented using RTMAPS in realworld scenarios on the university’s track. The results of this study provide valuable insights for the research and practical community in the field of autonomous vehicles and serve as a reference for future work in object detection

Cooperative Intelligent Transport Systems (C- ITS) are very important in our daily lives. They ensure road safety through the exchange of data between vehicles and road side units (RSU). Due to the sensitivity of the exchanged data between different entities, C- ITS systems are vulnerable to cyber attacks, they require high protection. In order to guarantee the integrity and the authentication of the exchanged messages, the European Telecommunications Standards Institute (ETSI), has specified specific procedures to manage certificates and signatures of all sent messages. Each vehicle periodically sends signed CAMs. Then, the integration of the signature and certificate in each transmitted CAM has a considerable impact on the communication channel load and bandwidth. In this study, we propose a new lightweight authentication mechanism which uses the cluster concept to decrease the network overhead. The objective is to reduce the number of signatures and certificates on all exchanged messages. The key idea is that neighbouring vehicles form a cluster to establish a trust relationship with each other, thus removing the need to send signed messages each time. Our method allows for the exchange of lightweight data without certificates or signatures (unsigned CAMs) and therefore verification and signature processes are no longer necessary all the time, which saves processing time and allows for smoother and faster communications.

Several works are aiming to develop techniques allowing detecting False Data Injection Attacks, which represents one of the most harmful attacks due to its ability to damage a Cyber Physical Systems (CPS). Among these techniques the watermarking represents one of the most used ones. This paper proposes the design of a False Data Injection Attack (FDIA) against a CPS protected by a watermark-based detector. The attack herein proposed is achieved in two phases. The first one is a passive phase, where the adversary builds a black box model of the system. Then, he uses the already built model to create the FDIA without being detected by the watermark based detector. The extensive simulations prove that this attack could be used to deceive the system even with the presence of a dynamic watermark.

The implementation of security in Cooperative Intelligent Transport Systems (C-ITS) is highly recommended to authenticate and ensure the integrity of Cooperative Awareness Message (CAM) exchanged between vehicles. Modern networks must be reliable and optimized in terms of the use of resources. In Europe, the ETSI standardization institute has defined a PKI (Public Key Infrastructure) for C-ITS that is used to distribute certificates for each vehicle. To ensure that CAMs (Cooperative Awareness Messages) are generated by trusted vehicles, they have to be signed using these certificates. However, integrating signature and certificate within each sent CAM presents a high impact on the overload of the communication channel and the bandwidth, due to the added size to the sent CAMs, which is significant. In this paper, we propose a new lightweight authentication protocol based on the ETSI standard. Our protocol is dynamic and integrates few concepts allowing to smartly reduce the transmitted security information, which often presents the highest cost in network systems. First, we build a cluster to establish a trusted link between vehicles giving them the opportunity to exchange information using unsigned CAMs (without integrating certificate and signature). As a result, the verification and the signing processes are not always necessary, which saves processing time and results in smoother and faster communication. Furthermore, we added a process that aims to check the consistency of the CAMs of each vehicle in the cluster in real time to avoid an attack. Under the Omnet++ simulator and the Artery framework, we have demonstrated that our protocol is more efficient in terms of communication channel usage and latency, while still secured.

This paper presents an improved version of Contention Based Forwarding (CBF) protocol, the current standardized dissemination protocol in VANETs by the ETSI, referred to as iCBF. iCBF address two main issues exhibited by the original CBF: (1) the high dissemination delay induced by the adopted intermittent re-transmission paradigm, and (2) the low message coverage capability due to the use of an indiscriminate inhibition rule of the relay candidates. The high delay problem has been mitigated by enabling a continuous re-transmissions process at the application layer, thanks to the use of one new sender-oriented relay selection mechanism to regulate the next dissemination entities at the sender side. In order to overcome some intrinsic VANETs challenges, especially the high speed vehicles, we exploit the original CBF's forwarding algorithm (with a slight modification) to monitor the explicitly selected relays and compensate for the unexpected message loss. The poor message coverage problem has been tackled through introducing a tridant concept, designed to adjust the relay selection and inhibition rules for ensuring an effective distribution of relays inside the targeted dissemination area. As respect to the original CBF, iCBF evaluation shows significant performance improvements in terms of messages coverage and transmission delay while not wasting the limited channel resources and bringing compliant with ETSI-GeoNetworking standard.

Smart cities are a wide range of projects made to facilitate the problems of everyday life and ensure security. Our interest focuses only on the Intelligent Transport System (ITS) that takes care of the transportation issues using the Vehicular Ad-Hoc Network (VANET) paradigm as its base. VANETs are a promising technology for autonomous driving that provides many benefits to the user conveniences to improve road safety and driving comfort. VANET is a promising technology for autonomous driving that provides many benefits to the user's conveniences by improving road safety and driving comfort. The problem with such rapid development is the continuously increasing digital threats. Among all these threats, we will target the Sybil attack since it has been proved to be one of the most dangerous attacks in VANETs. It allows the attacker to generate multiple forged identities to disseminate numerous false messages, disrupt safety-related services, or misuse the systems. In addition, Machine Learning (ML) is showing a significant influence on classification problems, thus we propose a behavior-based classification algorithm that is tested on the provided VeReMi dataset coupled with various machine learning techniques for comparison. The simulation results prove the ability of our proposed mechanism to detect the Sybil attack in VANETs.

Both minimal set cover and maximum 1-coverage are known to be NP-Hard when using homogeneous and heterogeneous wireless sensor networks. The proposed solutions in the literature guaranteeing k-coverage in WSN affect either the energy, the network lifetime, or the quality of service. These solutions still incur time complexity and energy overhead that increase with WSN large-scale, connectivity and size of coverage holes. To avoid these issues, this paper proposes a minimal semi-deterministic deployment model in a mobile wireless sensor network. This model is based on Pick's theorem to guarantee a maximum 1-coverage. This requires the subdivision of the area of interest into square sub-areas according to a pre-established grid, and then an initial deployment of sensor nodes randomly around each sub-area center. The main strengthen of the proposed deployment approach is the minimization of the nodes' movement from their initial positions. Where, each node moves once and remains active until it is exhausted. The results show a high efficiency in terms of increasing the network lifetime and the coverage compared to some well-known approaches.

Misbehavior detection in VANETs is critical to provide security and road safety since the communication between vehicles is directly affected by attackers’ messages. A new misbehavior detection approach is presented and compared with previous approaches. The estimated angle of arrival and the estimated distance using path loss model are proposed as new features to use for detection mechanism. When an attacker sends a message, it can produce false position values. Therefore, using a set of suitable features about the relation between sender and receiver will help to detect attackers. Machine learning techniques, Random Forest and k-Nearest Neighbor, are implemented to classify a vehicle as an attacker or not by considering the proposed features. The performance of the proposal is evaluated using a public dataset and easily compared to others. The results show that the proposed approach increases the performance of misbehavior detection in terms of classification evaluation metrics.

Since few years, cloud computing has been adopted vehicular networks and many issues have been handled within such networks as cloud architecture and application distribution This paper proposes a new mechanism, denoted Geographical Vehicular Central Data Networking (GeoVCDN), to distribute interests in the context of Vehicular Cloud Networking (VCN). Our mechanism takes the benefit from the ETSI (European Telecommunications Standardisation Institute) standardized sent messages such as Cooperative Awareness Messages (CAM) to distribute the interests and to collect new data. Moreover, our approach allows to use the multi-hop forwarding capability of vehicular networks to spread the new data. Extensive simulations show a real enhancement of our solution compared to existing ones in particular two well known mechanism: Rendez-vous Networks (RENE) and Named Data Networks (NDN).

The implication of Cyber-Physical Systems (CPS) in critical infrastructures (e.g., smart grids, water distribution networks, etc.) has introduced new security issues and vulnerabilities to those systems. In this paper, we demonstrate that black-box system identification using Support Vector Regression (SVR) can be used efficiently to build a model of a given industrial system even when this system is protected with a watermark-based detector. First, we briefly describe the Tennessee Eastman Process used in this study. Then, we present the principal of detection scheme and the theory behind SVR. Finally, we design an efficient black-box SVR algorithm for the Tennessee Eastman Process. Extensive simulations prove the efficiency of our proposed algorithm.

The area coverage is a non-trivial problem in Wireless Sensors Network (WSN) due to the lack of knowledge in the minimum sensor nodes set that can cover an area of interest and limitation of energy reserve, monitoring and communication ranges. Coverage protocols address two fundamental questions: how can the coverage performance of deployed sensor nodes in a monitoring region be evaluated; and how can the coverage performance be improved when wireless sensor network cannot effectively satisfy quality of service requirements? Constructing sets of minimal nodes to optimize the coverage problem push researchers to use different techniques from different domains, such as Voronoï Diagram, Connected Dominating Set, Clustering, and others. Each technique deals with the problem by its own philosophy. Our approach aims to use a hybrid model combining Diagram of Voronoï, Clustering, and Connected Dominating Set in order to benefit from the advantages of these three models to optimize area coverage, keep connectivity, and minimize energy consumption. The simulation showed the ability of our approach to ensure optimal coverage with minimal power consumption for a longtime.

Heterogeneity is one of the main issues for the deployment of the Industry 4.0. This is due to the diversity in the available robots and the IIoT devices. These equipments use different programming languages and communication protocols. To make the integration of such equipments easy, we propose TalkRoBots, a middleware that allows heterogeneous robots and IIoT devices to communicate together and exchange data in a transparent way. The middleware was experimented in a real scenario with different robots that demonstrate its efficiency.

Due to the high mobility and dynamic topology changes of vehicular Ad-hoc Networks (VANETs) which generate scattered networks, the network's performance has become a critical issue for connected and autonomous vehicles deployment. In order to address this issue, the Heterogeneous Vehicular Networks (HVN) paradigm was designed and it consists in a hybridation of the vehicular network (IEEE 802.11p) and the cellular networks (3G/LTE/4G). This makes the vertical handover to be one of the key technologies for the Internet of Vehicles (IoV) deployment. In this paper, we proposed a vertical handover mechanism (PMIP-MIVH) which uses a logical interface and a Distributed PMIPv6 scheme in order to improve the handover performance. Numerical analysis shows that PMIP-MIVH performs well in terms of handover connection times, handover latency and session continuity, specifically in HVN.

C-ITS (Cooperative Intelligent Transport Systems) are growing more than expected, they are an important part of smart cities. Connected vehicles is one of the most recent aspect of C-ITS. For these vehicles, usual communications could be ensured through wireless local area networks over ITS-G5 (based on WFI 802.11p). In smart cities, these interconnections form a Context Cloud. As a consequence a vehicle can access to information generated by any other C-ITS, no matter its location, as long as both are part of the Cloud. In this paper, we propose a secure Cloud environment for connected vehicles denoted VCDN, for Vehicular Central Data Networking, which exploits Information Centric Networking and Vehicular Cloud Computing paradigms to provide to vehicles the data generated in a Smart City. All the communications with the Cloud are authenticated messages and mainly Cooperative Awareness Messages (CAM). We have compared the performance of our solution to some other solutions, in particular REndez-vous NEtwork (RENE) and Named Data Networking (NDN). The results are promising since our solution is more efficient compared to these approaches in terms of network's overhead.

Cooperative Intelligent Transport Systems (C-ITS) are expected to play an important role in our lives. They will improve the traffic safety and bring about a revolution on the driving experience. However, these benefits are counterbalanced by possible attacks that threaten not only the vehicle's security, but also passengers' lives. One of the most common attacks is the Sybil attack, which is even more dangerous than others because it could be the starting point of many other attacks in C-ITS. This paper proposes a distributed approach allowing the detection of Sybil attacks by using the traffic flow theory. The key idea here is that each vehicle will monitor its neighbourhood in order to detect an eventual Sybil attack. This is achieved by a comparison between the real accurate speed of the vehicle and the one estimated using the V2V communications with vehicles in the vicinity. The estimated speed is derived by using the traffic flow fundamental diagram of the road's portion where the vehicles are moving. This detection algorithm is validated through some extensive simulations conducted using the well-known NS3 network simulator with SUMO traffic simulator.

Sensor nodes suffer from a lot of constraints, such as the limited energy source, the short radius of communication, the low processing and storage power. These fuzzy constraints deplete the energy of the implemented sensor network, especially, in coverage and routing data in the large-scale zones. The main constraint in WSNs is the energy. To outcome this constraint, we have proposed a Data Routing-Scheduling via Efficient-Energy Area Coverage in wireless Sensor Network protocol (EE_AC_DR) based on our proposed Dijkstra Front-Back algorithm. In fact, our protocol uses Dijkstra algorithm with steps to pass the nodes in the superior Cluster, or return it to the lower Cluster to choose the designed node as Cluster-Heads for playing a multiple role; a role of Cluster-Head, a role of coverage in the entire cluster and a role of communication routing the information in the best and shortest path towards the base station. This protocol is divided into the following five (5) steps: 1) the construction of the Clusters; 2) the choice of the Clusters-Heads; 3) the choice of the best neighbors; 4) the construction of Head-Clusters-Head, and 5) the choice of best Cluster-Head neighbors. We demonstrate, using some large scale simulations, that this protocol enhances the performances of the network and allows taking the best choices regarding the use of only one node in each cluster to monitor and communicate data using the shortest path with minimal cost.

Summary Position‐based routing, also called geographic routing, is widely recognised as an efficient routing approach for highly dynamic and mobile networks as vehicular ad hoc networks (VANETs). In this kind of networks, the high‐speed mobility of vehicles causes rapid changes on the network topology measured with vehicles density, limited‐time communication links, link failures, etc. In the meantime, the need of location service is a key issue; indeed, it will allow finding the position of a target node in order to reach it with a message. Some theoretical studies have proposed location services based on sharing nodes informations in different ways with hierarchy mechanism or with distribution mechanism or with centralization process. This paper proposes a location service deployed on RSUs (Road Side Units) for unicast routing over VANETs in urban environment. The proposed approach is able to measure the connectivity of a route. We propose then a new metric called Link Connectivity (LC) which measures this connectivity. Additionally, we have implemented our proposal using OMNET++ simulator and we have conducted extensive simulations with various scenarios to evaluate its scalability and robustness against frequent topology changes. As a conclusion, the proposed mechanism provides significant performance improvements in terms of packet delivery ratio, end‐to‐end delay, and overhead when it is compared to some other known proposals.

"Connected vehicles" is a very hot challenge since many years. Usual communications could be ensured through wireless local area networks (over ITS-G5 for example) or through cellular networks (over 3G, LTE, etc.). ITS-G5 is not enough deployed. Then, the need to have efficient solutions using cellular networks is required. Indeed, we propose in this paper a solution to trigger automatically some events after collecting messages from mobile nodes. The triggered events are those related to traffic congestion which could be combined with a notification about alternative routes. Our contribution consists of a deployment of an application over smartphones embedded in vehicles which are connected to a server (through cellular networks) which takes care of management of vehicle location as well as traffic congestion management. The deployment of the application during some weeks has provided a mobility model which has been used as an input to a simulator. Many simulations have been undertaken and some indicators have been measured as latency and packet loss rate.

Content is not always about medias and files, computing tasks output are also a content that can be described, stored and cached. In this paper, we investigated the problem of edge computing and caching in the fog computing networks. In our scenario, we consider the user requests computing tasks from the fog, that the devices could not handle. Moreover, fogs use their storage and computing capabilities to cache the tasks computation results in order to minimize the latency, and use it storage to offload their resources by caching the significant computing tasks output. We propose a clustering method based on the correlation between the tasks and the cached content to decide what fog will give a better service in term of latency to offer better quality of service and experience. The problem of the users-fogs association was formulated as a coalition game between the users and the fogs. Finally, we use the BoltzmannGibbs learning algorithm to make every entity able to learn the best coalition, in order to enhance the convergence of the system to reach a better and optimal stability.

Vehicular ad-hoc network (VANET) is a special type of wireless mobile ad-hoc network. Generally, communication between vehicles and fixed roadside units (RSUs) are used in Intelligent Transportation Systems (ITS) to allow vehicles updating their knowledge about the traffic status. However, the deployment of fixed RSU is expensive and it needs a long time to be achieved. To overcome this issue, we study a cost-efficient solution based on the deployment of some specific mobile RSUs. An analytical study is proposed to analyse the enhancement of the communication probability when considering mobile RSUs compared with the classical approach with fixed RSUs. The results show that the introduction of a rate of 5% of mobile RSUs can double the communication probability.

Multimedia transfer in ad-hoc wireless networks is a challenging issue and attracts many researchers. In this paper, we propose a cross layer scheme to handle video transfer. Our staring point is to provide a multipath forwarding protocol able to transmit efficiently video streams and regular data from many sources to a unique base station (BS). This protocol will have a close cooperation with the application layer in order to consider with care different video frames and to assign high priority to the most important frames and lower priority for the least important ones. In the meantime, many paths could be selected, our aim is to guarantee independence between paths in terms of interference in order to be able to use more than one path in the same time. Experimental analysis has been undertaken, they show improvements of some performance indicators such as packet data rate, delay, loss packet rate and user experience feedback.

Routing messages over vehicular ad hoc networks (VANETs) is usually achieved through geographic routing protocols. In such networks, the vehicle dynamics causes rapid changes on the vehicle density and the communication links. In order to be efficient to route messages from a vehicle to another, we need to locate each node (its position), this is achieved by a location service. This study works on simple location service adapted for unicast routing over VANETs in city environment. This service is able to find a route from a route from a source to the destination and this route is the one passing through the most dense path.. We have implemented our proposal on the OMNET++ simulator and we have conducted extensive simulations in different scenarios to evaluate its scalability and robustness against frequent topology changes. The results obtained have shown that our proposed protocol provides significant improvements in terms of packet delivery ratio, end-to-end delay and overhead compared to EGyTAR protocol.

Recently, the topology control strategies attract more and more the research community as being a crucial issue to be handled for the Wireless sensors networks (WSNs). In this paper, we propose a centralized power control mechanism based on the link gain information to reduce network energy consumption. Our mechanism works through two steps, first we construct a skeleton that ensure network connectivity while reducing considerably the number of links in the network. Second, based on the obtained skeleton, we reduce the power transmission for each node while keeping a connectivity with a node of the skeleton with a link gain greater than a predefined threshold. The simulation results conducted over TOSSIM, show that our proposal can save the network energy up to 10% while achieving better PDR value, which goes near to 12% compared to non-optimized network.

The recent enhancement of sensor devices, such as the Micro-Electro Mechanical Devices (MEMs) used for information collection and dissemination, has led to the emergence of the Internet of Things (IoT). This new paradigm overlaps with many research area such as the Wireless Sensor Networks (WSNs) where sensor nodes are deployed over an area to perform local computations based on information gathered from the surrounding. Virtual Backbone is a mechanism that aims at constructing a path with multi-hop from cluster-heads (CHs) to a Base Station (BS) via gateway nodes. This mechanism is efficient since it allows to enhance the reliability and prolong the network lifetime. In this paper, we propose a new routing protocol, denoted Multi-Hop Energy Aware Neighbor Oriented Clustering (MH-EANOC), which uses a virtual backbone to improve the network lifetime and reduce the number of lost packets. The aim of our proposition is to find the best connection between the CHs to ensure a fast and efficient backbone construction while minimizing the energy consumption. MH-EANOC uses the number of Advertisement (ADV) messages, the residual energy and the distance to the BS in the choice of the backbone's gateways. Our simulation results show that MH-EANOC outperforms EEUC and MH-LEACH in terms of packet delivery ratio and network lifetime.

Summary Efficient energy consumption is the most important challenge in wireless sensors networks. Many solutions have been proposed since many years as efficient medium access control protocols, smart sensing applications, appropriate task scheduling, and so on. Task scheduling allows could participate to optimise energy consumption, it aims to propose planning over repetitive time periods where sensors need to sleep, to collect data and to communicate. In this paper, we propose two scheduling procedures (semi‐dynamic and dynamic) which are executed over the ZigBee network in beacon‐enabled mode. Each of these algorithms has its own features and advantages. The Zigbee super‐frame is used as a means to inform each node on its duties (when to sleep or when to communicate). In order to evaluate our proposals, we have implemented them over TelosB motes running on operating system TinyOS. These algorithms have been implemented on the Z‐Monitor tool . We have compared our scheduling approaches to the usual static scheduling method provided by Zigbee. These evaluations show that our proposals enhance network lifetime and ensure better packet data rate and lower latency. Copyright © 2017 John Wiley & Sons, Ltd.

Greedy routing in VANETs requires some geographical informations, such as the source location and the destination location.The first one could be obtained using some localization devices like GPS receiver.However, the second one is provided by a location service.This later has a high overhead especially if it is implemented over V2V (vehicle to vehicle) communications.Many location services are well known as HLS, RLS, GLS.This paper is interested in reducing this overhead by using some Road Side Units (RSU) already deployed along the roads.We propose here a location service called "improved Reactive Location Service (iRLS)", which is an extension of the RLS service.The major difference is that RLS assumes only V2V communications and iRLS takes profit of a wireless backbone based on RSUs to catch the destination's position.This allows to reduce the overhead instead of flooding requests and also makes the communication faster since we will not have to wait to the request to reach the destination before receiving the response and then starting sending data.In our proposal, the closest RSU will reply with the actual location.In order to show the contribution of our approach, we have conducted some simulations that prove that iRLS outperforms any geographic protocol by using the V2I communications in terms of end-to-end delay which is one of the most important parameter.We considered also the ratio of packet received correctly by the destination vehicle (PDR), our protocol improves significantly this second parameter, and ensures more than 20% of packets received correctly Index Terms-VANETs; Location-based Services; Geographic Routing Protocols, .

This paper aims to present a methodology and a set of tools that could be used in order to check the validity of an Intelligent Transport System. These tools will consider each ITS component, i.e. C-ITS- R (Road Side Units) RSU, C-ITS-V (On-Board Unit) OBUU, C-ITS-C (Central Server) with its specific fea- tures as location precision for an OBU and adequate forwarding of dangerous events for an RSU. The aim of this paper is to tackle first con- formance testing for each component (in fact the component have to respect all basic specifications) before check the interoperability of all components (in order to ensure a correct functioning of the when they work together). Basic specifications have been mainly described by standardization institutes as ETSI or IEEE. But some additional specifications could be considered for particular aims (for example, car manufacturers do all agree on the distance to inform drivers on next dangerous events). This framework has been experimented with var- ious RSUs and OBUs from different providers. We have experimented the framework with all of them and many troubles have been detected. Most of the bugs are due to a wrong interpretation of specifica- tions. Sometimes, troubles reveal that specifications have been proposed with incorrect behaviors. The main conclusion is that such frameworks have to be improved and deployed widely in order to allow the deployment of large scale Intelligent Transport Systems.

Experimental deployment of Cooperative Intelligent Transportation Systems have been undertaken these last years. But a real deployment is lower than expected. One reason is the lack of complete validation techniques which handle the whole system. The aim of this paper is to present a complete framework able to test each component involved in a C-ITS and which is able to check the interoperability of all components. This framework ensures the conformance testing of all the C-ITS components regarding their specifications (mainly the communication protocols which ensure the interoperability over various layers) as well as the interoperability testing of these components in order to guarantee their correct functioning where they perform together. This framework has been used with mobile ITS stations and fixed ITS stations provided by different vendors. Many test series have been undertaken. C-ITS development is not quite mature, then many bugs have been detected thanks to the execution of test cases. The design of this framework and its use have shown that a deployment of an actual C-ITS is still a difficult task. The use of our framework has underlined that some standard specifications (either protocols or test case specifications) need to be improved.

Treating roads in winter (snow removal for example) is an important service that facilitates people's movement and increases the pavement's life. However, these treatments can be very expensive and inefficient if they are not properly scheduled. For this purpose, a complete view of the pavement's state is often essential for the management and the effectiveness of such treatments. Winter serviceability consists in managing the treatment of road in case of snow forecast. The main purpose of this service is to support roads or highways operators (either public or private) in this operation. In this paper, we introduce a new Sensor Vehicular Platform for Road Maintenance (SeVePlaRoM). This platform allows real time exchanges between the maintenance vehicles and the operating server in order to improve the maintenance and the quality of the interventions so we can be able to inform our clients in real-time about the road's condition in snow periods. Our platform was tested and validated using simulated vehicles and virtual machines. The simulations demonstrated that our platform fulfilled our expectations. 25 vehicles are now equipped with our technology and ready to test out our platform in real environment.

In Wireless Sensors Network (WSN) the energy parameter is important. The traffic management needs a clever scheduling algorithm that can balance the energy consumption and the time slots also can be divided according to the traffic pattern. Every sensor node collects the environmental data and sends it to the coordinator. Using scheduling algorithm allows the communication process to be done in a collision-free mode. This work propose two scheduling algorithms called semidynamic and dynamic. They are executed over ZigBee/ IEEE 802.15.4 network. The network coordinator is programmed to organize and synchronize the network based on the proposed algorithms. They are implemented in beacon-enabled mode. The beacon frames are defined only by the network coordinator. The beacon exchanging process between the coordinator and its child routers keep all sensor nodes synchronized. Our work is to use the scheduling algorithm in organizing beacon frames as well as super frames. We have validated our work by implementing the proposed algorithms over TelosB sensors. They are implemented under TinyOS environment.

The road safety and maintenance are very important and costly activities for road operators. Due to the decrease in the cost of the sensors technologies and wireless equipments, connecting maintenance fleet vehicles become very intuitive. It allows to enhance the efficiency and the reactivity of such services. In the present paper we describe an interconnection system that facilitates the data exchange between maintenance vehicles and Network Operation Center (NOC). We detail the data synchronization mechanism used by this system, which is equipping forty vehicles under tests. These tests showed that our system works well and enhance the efficiency of the road's maintenance and incidents' treatment.

This paper proposes a dynamic slot scheduling for tasks having different time constraints executed over wireless sensor networks (WSN). These tasks may have different priorities. They are usually repeated periodically. We present an algorithm which is able to provide a dynamic scheduling procedure for all tasks. In the actual version, the scheduling algorithm is executed on the network coordinator which monitor the slot distribution for all nodes. This algorithm is implemented over TelosB nodes.

This paper presents Semi-Dynamic Tree Scheduling Process for Wireless Sensor Networks (WSN). We combined two type of scheduling in this study: the static scheduling for coordinator nodes and the dynamic scheduling for leaf nodes. We consider a cluster tree topology in our study with, one main coordinator (Personal Area Network Coordinator), several children coordinators (Routers) and several end devices (leafs). We implement the scheduling algorithm on the PAN Coordinator. The experimental implementation is done over TelosB sensors under TinyOS environment.

This study presents a dynamic slot assignment for tasks executed over Wireless Body Area Networks. We consider tasks which have timing constraints for their execution. and different priorities. They are usually repeated periodically. In this study we propose an algorithm which is able to provide a dynamic scheduling procedure for all tasks. In the actual version, the scheduling algorithm is executed over the network coordinator. This algorithm is implemented over TelosB nodes composing a Wireless Body Area Network.

Location-based services provide (and maintain) location information used by geographic routing protocols. Routing and location service are widely related, but handled separately in usual studies about Vehicular Ad hoc Network (VANET). In this paper, we propose a hybrid approach, denoted mobility-Prediction-based Hybrid Routing and Hierarchical Location Service (PHRHLS), coupling a VANET routing protocol, the Greedy Perimeter Stateless Routing (GPSR), and the Hierarchical Location Service (HLS) extended with a mobility prediction algorithm. We show that our approach, PHRHLS, reduces the localization overhead and enhances the routing performances. Indeed, our extensive simulations show promising results in terms of end-to-end latency, packet delivery ratio and control message overhead.

In this paper, we propose a combination between a routing protocol Greedy Perimeter Stateless Routing (GPSR) and Hierarchical Location Service (HLS) that we denote Hybrid Hierarchical Location Service (HHLS). HLS and GPSR used to be combined in the original work with a direct method, i.e. GPRS takes care of routing packets and HLS is called to get the destination position when the target node position is not known or is not fresh enough. When a destination is quite far away from the sender, the exact position of the target is calculated, and an extra overhead is generated from sender to receiver. Our main purpose is to reduce this overhead in HHLS. We suggest to proceed as follows: when a packet has to be sent to the destination, it will be sent directly to the former position of the target instead of requesting for the exact position. When the packet is approaching the former position, the exact position request is then sent. We have proposed a patch over the NS-2 simulator for HHLS according to our proposal. We have conducted experimentations which show promising results in terms of latency, packet delivery rate and overhead.

VANETs (Vehicular Ad-hoc NETworks) are a special case of MANETs (Mobile Ad-hoc NETworks). Their main feature is the high mobility range of nodes, which causes topology changes and frequent disconnections. Topology-based routing protocols have weak performances in such networks. This is why a new set of routing protocols, designated as geographic routing protocols, were designed to enhance performances and ensure a better scalability. These geographic protocols assume on one hand that all nodes must be aware about their position (by using a positioning system like GPS). On the other hand they also assume a certain knowledge about the position of the destination node and the position of their neighbors thanks to Location-based Services. In this paper, we compare three location-based services: Reactive Location Service (RLS), Grid Location Service (GLS) and Hierarchical Location Service (HLS) while coupled to the well known geographic routing protocol Greedy Perimeter Stateless Routing (GPSR). As far as we know, our work is the first that targets the performance evaluation of location-based services while coupled with a routing protocol. The simulations were performed using the NS-2 simulator on a realistic map about the city of Reims (France). Besides, a scalability study of GLS and HLS is presented. This study is based on three qualitative metrics (the location maintenance cost, the location query cost and the storage cost).

In modern vehicles, there are a lot of devices (GPS receiver, Tachograph, etc.) with different functions. The communication between these peripherals is rarely ensured. In fact, they have to exchange useful information about the vehicle status. Many protocols and standards are used to connect embedded devices. Then, the compatibility between them is not always guaranteed. We propose in this paper a new design of a smart channel. This channel allows the communication and interoperability between heterogeneous embedded systems. The smart channel builds services which can be customized by the end-user. Furthermore, simulation results are provided to illustrate this claim and to assess the performance of the proposed model.

Nodes in VANETs move at high speed. This high mobility makes most conventional routing protocols incompatible with this type of network. A new class of geographic routings has emerged. Most of these routing protocols suppose that the nodes position is known in advance and that the nodes do not have time to move significantly between sending packets and receiving their acknowledgments. This assumption is not always realistic because of the high nodes movement and the low wireless transmissions range. Consequently, packets routing may fail if this assumption is not guaranteed. In this paper, we propose a prediction mechanism, which will estimate the expected new vehicle position to reduce the packet loss.