This study presents a compact and cost-effective antenna for Beyond 5G (B5G) and 6G systems. The prototype, featuring a rectangular patch with a full ground plane on an FR4-epoxy substrate, performs very well at 26 GHz, achieving over 80% efficiency, a peak gain of 7 dBi, and an S11 below −45 dB. A two-element MIMO configuration was then developed. To reduce the strong coupling that usually occurs between closely spaced elements, linear split-ring resonators were added between the radiating elements. This solution effectively reduced interference while maintaining high antenna performance, improving isolation to −40 dB across the working band. The proposed MIMO system also shows excellent metrics: the envelope correlation coefficient (ECC) is around 0.001, the diversity gain (DG) reaches 9.9 dB, the channel capacity loss (CCL) is about 0.002 bits/Hz/s, and the total active reflection coefficient (TARC) is close to 0.006. Overall, the design provides a simple and effective approach to building compact, high-performance MIMO antennas, making it well suited for next-generation B5G and 6G applications.

International audience

The sixth generation (6 G) of wireless communication demands advanced personalization, low latency, and scalability to support emerging applications such as extended reality (XR) and intelligent digital twins. Conventional federated learning (FL) methods struggle to address these requirements due to their limited adaptability to diverse user contexts. To tackle these issues, we suggest FCAFL, a new federated learning method that uses Formal Concept Analysis (FCA) to group users based on their needs and combine models in a way that considers their specific situations. FCA-FL achieves state-of-the-art performance with 82% accuracy, $63 \%$ communication overhead, and 92 Mbps throughput, significantly outperforming traditional approaches. Additionally, it maintains robust signal quality with an SINR range of $26 \mathrm{~dB}-22 \mathrm{~dB}$, ensuring scalability in high-density networks. Future work will explore dynamic clustering, quantum-enhanced FL, and real-world deployments to further enhance FCA-FL’s potential as a transformative solution for personalized 6G services.

This research investigates the application of Vision Transformers (ViT) for facial emotion recognition through extensive experimentation on three benchmark datasets: CK+, FER2013, and AffectNet. Our study systematically examines how dataset characteristics influence model performance, revealing substantial variations in recognition accuracy based on data quality and environmental conditions. The ViT architecture demonstrates outstanding performance on the controlled CK+ dataset, achieving 95.2% accuracy and 93.8% F1-score, confirming its effectiveness under laboratory conditions. However, performance decreases considerably on real-world datasets, with $\mathbf{6 0. 4 \%}$ accuracy on FER2013 and $58.1 \%$ on AffectNet, emphasizing the challenges of practical deployment in uncontrolled environments. Comparative evaluation with existing methods shows that our ViT approach surpasses traditional CNN architectures by $\mathbf{1} \boldsymbol{-} \mathbf{3} \boldsymbol{\%}$ across all datasets while maintaining computational efficiency. The research identifies consistent overfitting patterns during training, with happiness demonstrating the highest recognition performance and fear-sadness pairs presenting the most significant classification challenges across all conditions.

Radio resource allocation involves managing, distributing, and optimizing available wireless network resources (frequency spectrum, transmission power, network access time, antennas or beams). The advent of 6G networks, with billions of heterogeneous connected devices and increasingly complex infrastructure, necessitates intelligent and equitable resource allocation to ensure optimal Quality of Service (QoS) while preventing congestion. In this context, we propose a Deep Reinforcement Learning (DRL)-based allocation method for 6G V2X (Vehicle-toEverything) networks. Connected vehicles continuously generate sensitive data (location, trajectories, speed), whose centralized collection for DRL training poses significant risks including data breaches, GDPR (General Data Protection Regulation) noncompliance (due to challenging anonymization requirements), and user distrust of personal data collection systems. To balance performance with privacy preservation, we introduce a hybrid DRL-FL (Federated Learning) architecture that addresses 6G vehicular network challenges while ensuring data confidentiality. Our approach reduces base station energy consumption while ensuring rigorous user privacy protection.

Intelligent and cost-effective healthcare has gained popularity due to the growing global population and increasing medical expenses. It is imperative to have a proficient e-health monitoring system capable of detecting anomalies in real time and assisting specialists in formulating diagnoses based on the collected data. The Internet of Things (IoT) has been effectively implemented across numerous industrial sectors, with notable applications in automation, monitoring, healthcare, and biomedical engineering. Hospitals and private medical centers employ IoT technology to enhance patient health. This work falls within the e-health context, utilizing IoT and 5 G connectivity to remotely monitor heart patients. The proposed system utilizes sensors embedded in a handheld device to observe the patient’s Electrocardiogram (ECG) readings and instantly inform doctors or caregivers whether or not the values are within the standard range. 5 G mobile networks enable each connected object owned by dependent people to connect to a cloud server. Critical data is collected and shared using portable sensors, which are then transmitted to secure fog/cloud computing devices for analysis. Additionally, the Artificial Intelligence (AI) sector is rapidly expanding, with applications that enhance human activities, particularly in the healthcare domain. AI is increasingly important in e-health through the evolution of machine learning (ML) and deep learning (DL). In this paper, we used DL as a technique for the analysis and processing of the collected data. The results demonstrate that our proposed model enables suitable classification in the ECG domain with accuracy levels of $100 \%$ and $98.02 \%$ for the training and validation phases, respectively.

Transport development impacts various aspects of life, including the economy, education, and healthcare. The concept of vehicle-to-everything (V2X) aims to provide safer and more satisfying travel experiences through Fifth-Generation (5G) of cellular network technology. Network Slicing (NS) is a key technology in the 5G architecture that addresses personalized Quality Of Service (QoS) requirements and resource management challenges. Handover (HO) is an essential technique in telecommunication and mobile communication systems. This technique maintains uninterrupted connectivity for users for mobile and vehicular networks. However, the increase in the number of HOs seeks to mitigate network performance. For that reason, in this study the purpose is to find a solution to improve network performance by decreasing the number of HOs. The application of Proximal Policy Optimization (PPO), a Deep Reinforcement Learning (DRL) algorithm, in a sliced vehicular network is the method to use in this research. We compared the simulation results obtained using PPO with a state-of-the-art algorithm and other DRL algorithms to identify the most effective approach. Our results show that PPO achieves superior performance, with approximately 80% and 20% improvements in cumulative reward and HO numbers, respectively. These findings indicate that PPO is the most suitable algorithm for sliced vehicular networks.

In recent years, Internet of Things (IoT) keeps evolving and permitting end users to benefit from its advantages. For example, automation, continuous monitoring and improved productivity. Although this technology facilitates the user’s life, the experience can be ruined due to cyberattacks aiming to interrupt the service and collect unauthorized data. Therefore, we propose a trust-based system to ensure continuous control of the system’s users. Any interaction between the user and the trust system is managed by a permissioned blockchain. A smart contract will be responsible for the trust’s verification, update and retrieve actions. More tests are provided in smart contracts to be launched automatically and preserving subsequently the security of the system. Regarding the trust evaluation, our approach allows the detection of Denial-of-service attempts. Also, the results show that a user’s transactions’ latency increases in parallel with transactions’ number. Additionally, the throughput increases accordingly with the transactions number invoked on blockchain ensuring system’s scalability.

Third Generation Partnership Project (3GPP) introduced Vehicle-to-Everything (V2X) in Long Term Evolution (LTE) Release 14 and Release 15. The present work aimed to investigate the resource allocation problem for V2X communications. To this end, we proposed applying the Variable Neighborhood Search (VNS) algorithm to solve the resource allocation problem. The proposed method aims to maximize the total throughput in the system while maintaining a minimum latency and reliability for both Cellular User Equipment (CUEs) and Vehicle User Equipment (VUEs). To verify the effectiveness of the proposed method, the VNS-based resource allocation scheme was compared to two other schemes; the first is based on the Particle Swarm Optimization (PSO) algorithm, and the second on the Ant Colony Optimization (ACO) Algorithm. The simulation was carried out using MATLAB software. The obtained results prove the performance of the proposed scheme in terms of resource allocation for V2X communications. The performance gains of the proposed approach demonstrate its feasibility and utility for V2X communications.

Unlike 4G, 5G aspires to offer distinct services such as voice and video (video streaming) communications, ehealth, and vehicular communication while utilizing the same 4G infrastructure. The cutting-edge technology of network slicing into the Radio Access Network (RAN) can be used to achieve this challenging goal. However, mobility management in a sliced Fifth Generation (5G network presents new and complex problems. User mobility in a network-sliced environment needs to be handled across not just various base stations or access methods but also various slices. In particular, base station (BS) physical resource constraints and network slice (NS) logical connection constraints should be taken into account while choosing a handover (HO) strategy. Here, we present a solution to improve network performance in a sliced 5G network by minimizing HO’s number. To this end, we applied a Deep Reinforcement Learning (DRL) method: Proximal Policy Optimization (PPO), a policy gradient reinforcement learning method. The simulation results show that PPO outperforms other algorithms, and the HO’s number is reduced.

Vehicular networks are a vast and significant research subject that attracts the transportation and telecommunications industries. The transportation industry’s primary goal is to ensure road safety. For this purpose, as a solution, it was necessary to combine cellular networks and vehicular technologies, which led to Cellular Vehicle-to-Everything (CV2X). Thus, vehicles that support 4th generation (4G) or 5th generation (5G) capacities must be capable of transparently adjusting to the existing dual infrastructure by enforcing the new 5G radio and current 4G Long-Term Evolution (LTE) technology. In this context, Dual connectivity (DC) was invented to enable vehicles to be connected simultaneously using the two technologies and to resolve the problem of frequent Handovers (HO). This study aims to enhance the network’s performance by reducing HO’s number. To do this, we opted to use and test our network with two Deep Reinforcement Learning (DRL) algorithms: Proximal Policy Optimization (PPO) and Advantage Actor-Critic (A2C). Simulation results and the comparison between these two algorithms reveal that PPO is the algorithm that performs the best in almost all scenarios.

Research on cooperative intelligent traffic issues has enhanced ground transportation's efficiency, safety, and comfort. The present work is interested in the resource allocation problem in V2X communications. We propose a new hybrid metaheuristic for a resource allocation scheme to maximize the system's total sum rate. This method is based on the particle swarm optimization (PSO) algorithm and a new suggested local search. We try to leverage the strengths and mitigate the weaknesses of both algorithms. The standard PSO algorithm has issues converging to optimal solutions because it lacks exploitation abilities. The local search aims to expand the search space vertically, allowing for a more balanced approach and addressing global exploration and local exploitation. We compared the proposed approach to the PSO and the Ant Colony Optimization (ACO) algorithms. The simulation was conducted using the MATLAB software platform. The results demonstrate that The algorithms proposed in this article significantly improve the system throughput and access rate of vehicular user equipment (VUEs) while ensuring the data rate of cellular user equipment (CUEs).'The results demonstrate the superiority of the proposed scheme.

Over the past decade, polar codes have gained momentum in academia and industry. They are selected for the control channel in the 3rd Generation Partnership Project (3GPP) for the 5th generation (5G) New Radio (NR) standard for mobile communications. To this end, the present work proposes a new polar code for ultra-reliable and low latency (URLLC) use case of 5G NR. Since polar codes are known by their performance in terms of error correction, two scenarios are considered. The first is interested in the evolution of Block Error Rate (BLER) as a function of downlink Signal Noise Ratio (SNR) while using Quadrature phase shift keying (QPSK) modulation on an Additive White Gaussian Noise (AWGN) channel. The second scenario is interested in the evolution of BLER as a function of uplink SNR while using QPSK modulation on an AWGN channel. Simulation results prove the performance of the new polar code type for 5G NR networks, especially in terms of throughput and BLER.

The Internet of Things (IoT) has expeditiously evolved from a recent concept to a prevalent and often crucial side of diverse environments, including industry, healthcare, homes and buildings, etc. Its applications for almost all the fields have actually become a principal target for various threats, mainly botnets. To mitigate this recent threat, diverse techniques were developed, particularly those founded on Machine Learning, Deep Learning and Transfer Learning which have achieved significant results in detecting IoT botnets. In our paper we propose a transfer learning intrusion detection system (IDS) to identify IoT botnets, comparing between deep learning and transfer learning models using two different algorithms, Artificial Neural Network (ANN) and Recurrent Neural Network (RNN). Results prove that the suggested approach based TL reaches high accuracy up to 99% that overcomes the accuracy of DL model for the two algorithms.

The commercialization of 5th generation (5G) technology began in several countries in 2020. However, it takes time to transition to a 5G network. 5G brings new techniques such as millimeter-wave (mm-wave), IoT, network densification, slicing, etc. Therefore, users with 4th generation (4G) or 5G capabilities must be able to seamlessly adjust to the existing dual infrastructure by implementing the new 5G radio and current 4G-Long-Term Evolution (LTE) technology. Dual connectivity (DC) is a solution proposed by the 3rd Generation Partnership Project (3GPP) in mobile heterogeneous networks (HetNets) to make this type of communication possible. Moreover, DC is a solution to frequent handovers (HO). Compared to conventional networks, user equipment (UE) in an ultra-dense mm-wave cellular network suffers HO events more frequently, leading to longer service interruption times and performance deterioration due to blockages. Machine Learning (ML) is one of the recent solutions used in mobile networks to solve several problems. Deep Reinforcement Learning (DRL) is a branch of machine learning that combines deep learning with reinforcement learning. Here, we aimed to improve the network performance using Proximal Policy Optimization (PPO) and Advantage Actor-Critic (A2C), two policy-based DRL algorithms, to examine our model and discuss the most performant algorithm among them. The results indicate that in most of the applied instances, PPO is frequently the algorithm that performs the best.

The 3rd Generation Partnership Project (3GPP) has maintained the standardization efforts on Vehicle-To-Everything (V2X) communications with NR-V2X (New-Radio-V2X) in Releases 16 and 17 in order to serve a wide variety of V2X use cases and applications with various quality of service needs and support situations with high vehicle density. One of the use cases that has attracted a lot of attention recently is vehicle platoons. Thus, vehicle platoons are a collection of vehicles that are tightly connected to one another virtually since they are going in the same direction at a constant speed while keeping a constant inter-vehicle distance. However, when a vehicle platoon travels from a source base station to a target base station, the existing communication technique incurs significant signaling overhead between the radio access network (RAN) and the core network (CN). In this study, we aim to reduce the number of handovers (HO) to enhance the performance of our vehicle network by using Deep Reinforcement Learning (DRL) as a technique. Simulation results reveal that the proposed model decreases the number of HO and increases the value of the cumulative reward.

The Internet of Things (IoT) is an emerging technology which goal is to render the real world more intelligent, and it is expanding exponentially. This expansion poses a whole bunch of challenges, where the leading challenge is security. The focus of this research is on IoT botnet attacks, which is becoming a major attack for iot networks, detecting the Mrai botnet. We develop a mining based detection technique employing deep learning with different neural network models. We use the iot-23 dataset to determine if the behavior is legitimate or malicious and in a second phase, the most efficient model is used to predict a variant of mirai botnet; Hakai. Developped models enable us to achieve high accuracy that is superior to 90%..

The introduction of the coronavirus (COVID-19) has resulted in higher surveillance costs, international hospital overcrowding, and disastrous diseases for the public. In order to treat and diagnose patients, wireless body networks (WBAN) have become essential. In computer-assisted rehabilitation and health surveillance, WBAN offers a wide range of applications, including those pertaining to emergency medical response systems, such as in the present pandemic situation. The patient's physiological characteristics are measured by biomedical sensor nodes, and the results are stored on a system called a local therapy unit. Only authorized users (doctors and other healthcare professionals) can remotely view the data from these patients as long as they are linked to their smart devices. However, in extreme circumstances, abnormal or incorrect measurements caused by damaged or malicious sensor nodes may result in incorrect diagnosis and even patient death. Patient privacy is in danger when these new technologies are used without taking data security into account. Thus, it is crucial for healthcare apps to retain anonymity. In order to resolve these problems, we suggest an effective healthcare system based on distributed agents. This system will ensure the secure collection and transfer of COVID-19 patient data to healthcare experts and will make it easier to identify and diagnose fatal irregularities. Our main contribution is to provide distributed real-time processing, learning, and risk analysis capabilities in order to deliver an intelligent and secure system. Agents are in charge of locating legitimate patient datasets from Tunisian doctors. In order to do this, we calculated risks related to sensors, signals, and the wireless medical network, sent data via Telnet and NetCat, employed ANN as the learning method, and securely sent data using the AES encryption protocol security. Our method exhibited performance values of 99% accuracy, 100% recall, and an F-score of 99.4% with a running time of 1.50 seconds.

The increase in human life expectancy, the COVID-19 pandemic and the rising cost of medical services have created enormous challenges for the governments and the healthcare industry. Unhealthy lifestyle has increased the need for continuous health monitoring and disease diagnosis. In the absence of a precise and effective treatment for COVID-19, providers around the world have made efforts to use drugs commonly used in other cases of indications to save the lives of infected people. A very important discovery was made between the prolongation of the QTc interval (corrected QT) associated with the ECG and mortality in patients with coronavirus. In addition, the QTc prolongation is mainly related to the drug treatments taken during the hospitalization of these COVID-19 patients. It is therefore very important to identify the influence of COVID-19 and medical treatments on the prolongation of the QT interval, which causes cardiovascular disturbances, but there is no identification process that allows us to differentiate patients who have a prolonged QT interval following cardiovascular disease from those who have COVID-19 and receive treatments that influence this interval. In this article, we propose a detection system based on machine learning. Random Forest was used for a multi-class classification. The learning results give an accuracy of 82% and a process execution time of 1.5s. Our simulations confirm that the QTc interval can be an identification tool for COVID-19 and post-COVID-19 patients.

It becomes very common to use cell phones in public transportation and the cars. Vehicular networking has a major problem which is the degradation of signal quality due to interference and the large number of mobile devices. Artificial intelligence (AI) is a promising technique for next-generation wireless networks. Deep learning is a type of AI derived from machine learning; here the machine can learn by itself, unlike programming where it is content to execute rules to the letter predetermined. In addition, AI can be explored in order to solve various problems. In this paper, we tackle the problem of resource allocation in a vehicular small cell network (VSCN). Indeed, we propose a new mechanism based on deep reinforcement learning denoted Resource Allocation based Deep Reinforcement Learning (RA-DRL). The main goal of our proposed method is to maximize the total system sum rate (throughput) while guaranteeing minimum interferences, Quality of Service (QoS) and the demand for all users. Simulation results demonstrate that our proposed RA-DRL algorithm exhibits better performance comparing to the other methods, by maximizing the total system sum rate while maintaining inter-VSCs interferences and a minimum latency

Nowadays, there are large amount of data generated by the IoT objects. For that, big data and Cloud and Fog Computing technologies have become increasingly important. Unfortunately, these environments still present many difficulties. And according to the statistics, we note that the major percentages of attacks come mainly from end users. Hence, we need an access control system. So, we focus our work on user access control. In fact, our contribution in this paper is mainly focused on securing user access to Fog Computing networks. For this, we propose, an efficient and complete protocol for access control service, which based on the trust assessment and the monitoring of the user's activities. Afterwards, we aim to improve our protocol by integrating the concept of certificates. We have shown through analysis studies and simulation results that the proposed scheme provides both security requirements in terms of confidentiality, integrity, availability, and anonymity; and network performance in terms of access response latency.

The concept of distribution in the Cloud and Fog computing makes the network more vulnerable to malicious activities. This requires use of distributed firewalls to stop incoming intrusions, where the Controllers are used to mitigate rules for the purpose of cooperation based on risk analysis. These security components are used in the architecture of Distributed Cloud / Fog with a zoned topology. We propose in this paper to use this topology that implements an access-control based on a set of cooperation levels between user-FN (FN: Node Fog). In addition, we secure the exchange of cooperation messages by guaranteeing integrity, confidentiality and authentication while avoiding replay attacks. This improves the security of the cloud network. As proof, we simulate Cloud/Fog network using the NeSSi² tool. This simulation obtained results are hopeful in term of delay and transmission rate must be a decrease of 1.5 ms. Furthermore, the protocol used in exchange of cooperation messages, is analyzed using Security Protocol Animator (SPAN) for Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The obtained validation results show that the scheme is safe.

The next generation of telecom networks, the Fifth generation (5G) have started hitting the market end of 2018 and will continue expand worldwide, introducing new features, higher data rates(up to 1Gbps) as well as massive IoT(Internet of Things) and the inclusing of artificial intelligence (AI) and its sub categories like machine learning and deep learning to solve many problem such as the radio network planning problem. While most existing research focuses on the use of deterministic algorithms, or meta-heuristic algorithms with a single objective, this paper exploits the power of genetic algorithm in addition to achieving multiple objective genetic algorithm (MOGA): to minimize cost and interference and to maximize user coverage. The experimental results prove that the use of genetic algorithm with stochastic universal selection is quite efficient in achieving those objectives, as well as, reaching a near optimal solution in a short infinite time.

Cloud based Intrusion Detection Systems (IDS) presented an effective way to increase the detection rates of malicious activities in the past couple of years. However, the implementation of these systems using traditional techniques is a herculean task due to the exponential growth of network bandwidth with the very limited availability of computational resources. One topic that intuitively stands out as a potential for solving this issue is Artificial Intelligence (AI). In this paper, we present an overview of recent detection proposals in the field of security intrusion detection using the contributions of new trends in AI (Artificial Intelligence) with an experiment carried out to evaluate the performance of different machine learning techniques using the most used dataset in information security research NSL-KDD and its various components in WEKA. Results show that the best classification algorithm is Random Forest with a Precision of 98.6%.

The Intelligent Transport System (ITS) is a basic application scenario in next-generation wireless networks, which require ultra-high throughput and ultra-low latency. More recently, non-orthogonal multiple access (NOMA) has been seen as a promising technique to meet the growing demand for data traffic for future 5G systems. The NOMA technique makes it possible to share the same resource by several issuers. However, the sharing of resources between a set of users, causes an interference problem. As a result, interference mitigation (IM) is becoming a more important phenomenon in NOMA-based vehicle networks. This work presents a new algorithm called SAVCN-IM (Scheduling Algorithm for V2X Communication based on NOMA with Interference Mitigation), for the 5G network. The proposed algorithm reduces interference to improve network performance in terms of throughput and error rates. In fact, the SAVCN-IM assigns the available resource blocks (RBs) in order to maximize throughput taking into account the value of SINR between transmitters and receivers. It also maximizes the number of V2X users served and minimizes the bit error rate. Simulation results indicate promising performance for SAVCN-IM.

The wireless body sensor network (WBSN) is an emerging technology in the healthcare domain, which collects data from vital parameters of the patient's body, using small portable components such as sensors. It allows to continuously monitor patients without restricting their movements and to inform the health specialist of the evolution of their states. However, the deployment of new technologies in health applications without taking into account data security makes the privacy of patients vulnerable. Thus, these systems have insufficient performance for large and varied data sets, because they do not process information sufficiently diverse to cover all scenarios. Moreover, the interpretation of physiological signals is a tedious process in which human errors can be caused.To address these issues, we propose, in this paper, an effective health system that ensures the secure collection and transfer of patient data to the physician, to facilitate the diagnosis and the detection of life threatening diseases. Our main contribution is to offer real-time, high quality processing, learning and analysis capabilities, in a smart and secure system. For that, we have collected real patient datasets from Tunisian doctors.To achieve this goal, we used ANN and XgBoost as learning algorithms and AES as an encryption protocol for sending secure data to medical personnel for diagnostic purposes. The results show an accuracy of 80% with an execution time of 1.54 s.

In recent years, the world of wireless telecommunications is in full progress. Indeed, although the evolution of 4G mobile networks continues, the standardization work of the 5G networks is in full progress. The connected vehicle is part of the services expected from 5G. Indeed, the interconnection between vehicles promises a safer and more enjoyable driving experience. However, as the huge number of vehicle devices are increasing day by day and each vehicle must perform a full authentication procedure to reach to the network, network congestion may occur when a group of vehicles requires simultaneous access, moreover this can have a decisive effect on the promised high rate of 5G. The EPS‐AKA authentication mechanism used in 4G networks is too insufficient to handle a large number of mobile devices. In this context, our article aims to define a reliable solution for the authentication of a group of vehicles simultaneous in 5G cellular networks. A reauthentication procedure is also proposed. Analysis results obtained using the SPAN tool has proven that authentication and privacy objectives are met. In addition, elaborate performance evaluations in terms of communication signalling and computational overhead demonstrate that our protocol is more efficient than those existing protocols.

The rapid evolution of the wireless communication technologies along with the growing number of connected vehicles and the limitation of available radio resources make scheduling tasks very important for the fifth generation (5G) mobile communication system Thus, to handle the challenges of access collisions, the scarcity of spectral efficiency due to the limited bandwidth and massive connectivity, non-orthogonal multiple access (NOMA) schemes have been introduced as a potential solution for 5G wireless networks. Accordingly, this paper presents a new optimal scheduling algorithm for V2X connections called Dynamic Scheduling Algorithm based on NOMA with Priority Assignment for vehicular Networks (DSA-PA-NOMA), which improves performances in terms of Quality of Service (QoS), throughput and bit error rate (BER). The proposed algorithm consider the traffic classification imposed by V2X exigency and aims to maximize the system throughput by taking into account the channel conditions of Vehicular User Equipment (VUE) expressed by the Signal-to-Interference-plus-Noise Ratio (SINR) value. The optimal distribution of the available Resources Blocks (RBs) is based on a dynamic reallocation process depending in the average blocking rate value (ABR) especially for vehicular Safety Traffic (ST).

Device-to-Device (D2D) enables direct communication among Vehicle-to-Everything (V2X) applications. Due to the high mobility in a vehicular environment, it is necessary to take into account the fast channel variations when defining resource allocation schemes in V2X networks. Furthermore, an efficient power control for V2X communications is needed to meet the large and growing number of vehicular devices and the growing demand for data traffic. In addition and for several types of networks, the use of transmission beamformer selection to reduce the power is a challenge. In this paper, we consider the power control problem in V2X networks. In addition, a joint beamforming and power control (BFPC) method for downlink V2X communication is proposed. It aims to reduce the total transmit power in the system while guaranteeing Quality of Service (QoS) for both, Vehicle User Equipments (VUEs) and Cellular User Equipments (CUEs). The problem is formulated as a non-convex optimization that we propose to solve it by using SemiDefinite Relaxation (SDR). The simulation results show the effectiveness of our BFPC proposed method compared to fixed power control method.

Device-to-Device (D2D) communication is an emergent technology that provides many advantages for the LTE-A networks as higher spectral efficiency and wireless Peer-to-Peer services. It is considered as a promising technology used in many different fields like public safety, network traffic offloading, and social applications and services. However, the integration of D2D communications in cellular networks creates two main challenges. First, the interference caused by the D2D links to the cellular links could significantly affect the performance of the cellular devices. Second, the minimum QoS requirements of D2D communications need to be guaranteed. Thus, the synchronization between devices becomes a necessity while Radio Resource Management (RRM) always represents a challenge. In this paper, we study the RRM problem for Vehicle-to-Vehicle (V2V) communication. A dynamic neural Q-learning-based resource allocation and resource sharing algorithm is proposed for D2D-based V2V communication in the LTE-A cellular networks. Simulation results show that the proposed algorithm is able to offer the best-performing allocations to improve network performance.

The upcoming Fifth Generation of mobile cellular networks 5G is expected to support a set of many requirements and new use cases. The main two user requirements are amplified data-rates at high-speed mobility and a robust and strong network security. Thus, the Third Generation Partnership Project (3GPP) published its first 5G security specifications recently in June 2018 and has been revised in December 2018. Although the security has been improved when compared to previous generations, our analysis recognizes some unrealistic system assumptions that are decisive for security as well as a number protocol edge cases that make 5G systems vulnerable to several attacks. In this paper, we propose a Secure Efficient and Lightweight authentication and Key Agreement protocol SEL-AKA of 5G cellular network taken into account the different limitations relieved in 5G-AKA and without relying on a Global Public Key Infrastructure. Analysis results obtained using the SPAN tool have proved that authentication and privacy objectives are met.

Seamless mobility management is considered as an important cornerstone of fifth generation (5G) networks. In fact, it is considered as one of the requirements for the next generation all-IP to fulfill their services in real-time. It allows devices and users to maintain highly seamless connectivity by switching between multiple wireless network using Vertical HandOver techniques (VHO). To address this need, some mobility management solutions have been proposed by researchers in order to support the VHO of devices using the Proxy Mobile IPv6 (PMIPv6) protocol. However, these solutions suffer from lack of security. For that, a new secure protocol, called Secure Fast PMIPv6 for Vertical HandOver (SFPMIPv6-VHO), is proposed in this paper. The proposed schema ensures a strong authentication in the case of the VHO between the Evolved Packet System (EPS) of Long Term Evolution (LTE) and the Wireless Fidelity (WIFI) using FPMIPv6 protocol. In addition, it suggested the integration of the Access Network Discovery and Selection Function (ANDSF) to perform an authentication preparation of user equipment (UE) in the selected network due to the limits of discover heterogeneous networks in the case of the PMIPv6 protocol. Our proposed protocol is modeled and validated using the tools of Automated Validation of Internet Security Protocols and Applications (AVISPA) and Security Protocol Animator for AVISPA (SPAN). The results of our simulations indicate that our protocol is robust against various attacks and that responds to our goals.

In recent years, there is a lot of research interest to study the Vehicle-to-everything (V2X) communication due to its ability to enhance intelligent transport systems (ITS), traffic safety and effective driving assistance. Since V2X has stringent latency and reliability requirements, the underlay Device-to-Device (D2D) communication empowers V2X services to meet their requirements. In this paper, we investigate the radio resource management (RRM) for V2X based on D2D communication, where resource sharing can take place between cellular user equipment (C-UE) and vehicular user equipment (V-UE). Hence, we propose an Efficient Scheduling and Resource Allocation algorithm (ESRA) for V-UEs and C-UEs which aims at maximizing sum rate and providing fairness for C-UEs, as well as at guaranteeing reliability and latency requirements for V-UEs. Simulation results show the very promising performance of our proposed ESRA algorithm compared with other existing methods.

The rapid evolution of the wireless communication technologies along with the growing number of connected vehicles and the limitation of available radio resources make scheduling tasks very important for LTE-V2X vehicular networks. Accordingly, this paper presents a new optimal scheduling algorithm for V2X connections called DSA-PA, which improves performances in terms of Quality of Service (QoS), throughput and fairness. The proposed algorithm consider the traffic classification imposed by V2X exigency and aims to maximize the system throughput by taking into account the channel conditions of Vehicular User Equipment (VUE) expressed by the Signal-to-Interference-plus-Noise Ratio (SINR) value. The optimal distribution of the available Resources Blocks (RBs) is based on a dynamic reallocation process depending in the average blocking rate value (ABR) especially for vehicular Safety Traffic (ST).

To meet the growing demand of users, the fifth generation (5G) will continue to provide services to higher data rates with higher carrier frequencies and wider bandwidths. As part of the 5G communication paradigm, ultra-reliable communication (URC) is envisaged as an important technology pillar for providing anywhere and anytime services to end users. Ultra Reliable Communication (URC) is considered an important technology that why it has become an active research topic. In this work, we analyze the availability of a service in the space domain. We characterize spatially available areas consisting of all locations that meet a performance requirement with confidence, and we define cell availability and system availability, individual user availability and user-oriented System Availability. Poisson point process (PPP) and Voronoi tessellation are adopted to model the spatial characteristics of a cell deployment in heterogeneous networks. Numerical results are presented, also highlighting the effect of different system parameters on the achievable link availability.

Thanks to the deployment of new techniques to support high data rate, high reliability, and QoS provision, Long-Term Evolution (LTE) can be applied for diverse applications. Vehicle-to-everything (V2X) is one of the evolving applications for LTE technology to improve traffic safety, to minimize congestion, and to ensure comfortable driving which requires stringent reliability and latency requirements. As mentioned in the 3rd Generation Partnership Project (3GPP), LTE-based Device-to-Device (D2D) communication is an enabler for V2X services to meet these requirements. Therefore, radio resource management (RRM) is important to efficiently allocate resources to V2X communications. In this paper, we present the V2X communications, their requirements and services, the V2X-based LTE-D2D communication modes, and the existing resource allocation algorithms for V2X communications. Moreover, we classify the existing resource allocation algorithms proposed in the literature and we compare them according to selected criteria.

In recent years, the work environments such as the cloud and Internet of Things (IoT) have become more sophisticated, and for proof, the access control network has become very important. To adapt to changing environments, in cloud computing, access network verification is an important requirement for researchers to integrate traditional verification using virtual firewalls.

Femtocells, also known as Home enhanced Node B (HeNB), are low cost and low power wireless Access Point (AP). This device is habitually deployed in an indoor environment to provide in-building coverage enhancement. Although femtocells are low power base stations, a vast deployment of femtocells causes many technical problems such as: interferences, user Quality of Service (QoS) and power control and consumption of femtocells. To solve such problems, most exciting works focus on power control and QoS in femtocell networks. In this paper, we provide a new intelligent QoS and power control method, denoted Users and Applications QoS Priorities (UAQP) power control method. This method aims to optimize the energy consumption of Femtocell Base Station (FBS) through adjusting their transmitting power according to two types of priorities, users and applications priorities. The simulation demonstrates the effectiveness of our proposed power control method and their performance compared to fixed power control method.

With the emergence of Internet of Things (IoT) and the growth of cloud computing technology, Electronic Health systems are integrated as a significant and active domain, which enables the development of medical practices with an affordable cost. Thus, the questions about preserving the security and privacy of the sensitive user's information are raised. Hence, in order to convince users to move their sensitive health records to cloud networks, a strong and secure access control schemes should be employed to protect their data. In fact, access control schemes play a key role in the protection of e-Health records, by which several policies will coexist to grant security and privacy in a network. That is why, one of the essential targets in this work is to retain a secure access to health cloud services. Thus, this paper offers a certificate-based access control strategy, where we introduce an access method for e-health cloud that is mainly based on trust assessment. The main features of the proposed scheme are the integration of trust concept with the monitoring process in order to ensure more security in access control. We more explained the methodology of the proposed approach through appropriate evaluation results, which improves system security and performance by minimizing the time spent to have permissions to access services and optimizing the overall system resource utilization.

Mobile Cloud Computing (MCC) is a technique in which mobile users are able to use the cloud services that enable cost reduction, flexibility and on demand, scalability. In fact, MCC enables to share the hardware, data and storage. However, access network verification is an important requirement; the traditional cloud computing architecture has specific security requirements that are not captured by traditional network access control models, e.g. Virtual firewalls (VF). The latter uses an effective static verification method that is not adapted to the MCC, where existing threats increase because of the combination of different types of networks (Mobile and Internet). Thus, distributing firewalls is introduced by researchers to prevent possible attacks and secure complex networks like MCC. However, it is difficult to design, manage and cooperate firewall policies. Thence, we propose in this paper an architecture for MCC motivating the use of distributed firewalls/Controllers, where two levels of firewall cooperation are proposed: horizontal cooperation in the cloud and vertical cooperation between the mobile and the cloud. This architecture is in charge of administering and updating rules between distributed firewalls and their neighbors via the Controller component. For validation, we use a cloud implementation based on the Openstack platform. The retrieved delay is promising with regard to the traffic burden.

Vehicle-to-everything (V2X) communication has been significantly studied in recent years due to its potential to improve intelligent transport systems (ITS), effective driving assistance and traffic safety. V2X technology has strict latency and reliability requirements. Therefore, the underlay Device-to-Device (D2D) communication of the future 5G cellular networks enables V2X to meet its requirements. This paper investigates the radio resource management (RRM) for V2X services based on D2D communication where both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications coexist. Hence, we propose an Efficient Resources Allocation and Power Control for V2X communications (ERAPC) algorithm that aims at maximizing the sum rate for V2I users and at guaranteeing the reliability and latency requirements for V2V users. Simulation results show the promising performance of the proposed ERAPC algorithm compared with other existing methods.

Vehicular Ad Hoc Networks (VANETs) offer many interesting services such as infotainment applications and safety information to vehicles. In order to protect these networks, we should ensure the confidentiality, integrity and authentication for V2I (Vehicles to Infrastructure) communications and V2V (Vehicle to Vehicle) communications. Nevertheless, in VANET environments, mobility of the vehicles is very high, so that a sound security can increase the Quality of Service (QoS) of the protocol. "The Dual Authentication and Key Management Techniques" is a solution that is created to authenticate and secure VANET communication. However, it suffers from some lack of security aspects. In this paper, we devise an improvement to this scheme in order to get a deliberate compromise between security and quality of service.

Cloud computing is a distributed and dynamic computing model that still has many difficulties. Intrusion prevention based on access control is an essential research challenge to better ensure the security of the cloud network. The flexibility and the scalability of the application of access control are the essential issues in a cloud environment. This paper proposes the use of risk and role based dynamic access control for preventing intrusions targeting the cloud computing, where the main enhancement of the proposed procedure is that access decision is mainly based on the resources available in the cloud services providers. The proposed scheme get the access decision based on a mixture of eXtensible Access Control Markup Language (XACML) decisions, risk analysis, and vulnerabilities assessment. Experimental results based on a comparison with related work are also presented to show the efficiency of the proposed approach.

Cloud Computing is a new promoted technology today. The adoption of the cloud computing has been increased for both enterprises and end-users. But, the major critical problem of this technology is its security that is becoming more and more serious. Thus, intrusion detection has been considered the best solution to secure the Cloud platform. Therefore, the main aim of all new researches is to retrieve an effective and performing intrusion detection system adaptable to cloud environment. In this paper, we propose a new Intrusion Detection System (IDS) for the -+8 rates and detection delay in order to make real time detection in the whole of Cloud platform based on the OpenStack framework. The results show that the C-DIDS is more efficient in term of delay compared to the existing GCCIDS solution.

The distribution's feature of cloud computing and the increasing threat of attacks and malicious activities make necessary the use of distributed firewalls to control access to networks. Network-based access management and control is an essential research challenge to enhance the security of the cloud network. We propose, in this paper the use of risk-based access decisions in a distributed and cooperative firewall topology. The proposed model is based on a combination of eXtensible Access Control Markup Language (XACML) decisions and risk-based network access control in the cloud. For proof, we simulate cloud network using the NeSSi2tool. The obtained results are promising in term of delay and blocking rate.

The emergence of Device-to-Device (D2D) communications is identified as one of the key technology components for future cellular systems, which anticipates a drastic improvement need of data traffic volume and a substantial user density. The concept of D2D communications opens up potential benefits for improving system performance with aiming to offload evolved node base station (eNB) from traffic routing by avoiding unnecessary transmissions to and from eNB and enabling direct link between communicating devices in proximity, but also brings new challenges, such as interference management. To promote research on these aspects, in this paper we propose a new radio resource allocation scheme called Dual Metric scheduling based on Quality of service and Power Control for network assisted D2D communications (DMQPC-D2D), which aims to allocate efficiently the resource blocks (RBs) among conventional cellular users (CUEs) and D2D users (DUEs). Once the RB allocation is performed, a power control process is applied to looking into the problem of eliminating the interference among DUEs and improving the energy efficiency of the system. Simulation results indicate promising performance of DMQPC-D2D.

NEtwork MObility (NEMO) has gained recently a lot of attention from a number of standardization and researches committees. Although NEMO-Basic Support Protocol (NEMO-BSP) seems to be suitable in the context of the Intelligent Transport Systems (ITS), it has several shortcomings, such as packets loss and lack of security, since it is a host-based mobility scheme. Therefore, in order to improve handoff performance and solve these limitations, schemes adapting Proxy MIPv6 for NEMO have been appeared. But the majorities did not deal with the case of the handover of the Visiting Mobile Nodes (VMN) located below the Mobile Router (MR). Thus, this paper proposes a Visiting Mobile Node Authentication Protocol for Proxy MIPv6-Based NEtwork MObility which ensures strong authentication between entities. To evaluate the security performance of our proposition, we have used the AVISPA/SPAN software which guarantees that our proposed protocol is a safe scheme.

Long Term Evolution Advanced (LTE-A) is one of the fastest growing technologies used for transmitting data in cellular networks. It provides its subscribers with enhanced service capabilities and enhanced network performance and this is carried through the smart deployment of new techniques and technologies. LTE-A is for improvement of the radio access part of cellular networks, for some time, it must co-exist with the 2G and 3G cellular networks, so interworking necessities, potential interference, resource management, etc. are an important issues. The Radio Resource Management (RRM) main role is to guarantee the efficient exploit of available radio resources using the available adaptation techniques, and to serve users based on their Quality of Service (QoS) parameters. In this paper, a novel dynamic neural Q-learning based scheduling algorithm is proposed for downlink transmission in LTE-A cellular network, aims to make a good trade-off between fairness and throughput. The proposed algorithm is based on the Q-learning technology and adoptable to variations in channel conditions. The key idea of our algorithm is how to intelligently choose the appropriate scheduling rule according to the predicted values of cell throughput and cell fairness index.

IP spoofing attacks create big problems in terms of security in Wireless Mesh Networks IEEE 802.11s (WMNs). These attacks are accounted to be sent from infected hosts. In order to avoid these threats, IP traceback mechanisms are considered the main challenges to realize such a forensic analysis of the Internet traffic and to permit an elegantly tracing back to the correct source. In this paper, we present our novel approach of IP traceback. In fact, our solution is founded on the marking approach to trace proactively the source of spoofed packets in WMN; it uses a private and secure ICMP message to register the whole trace of the attack path. For validation objectives, we implemented our solution using the network simulator NS3 to test the performance and the efficiency of our proposed scheme cling to some collected evaluation metrics. The results prove that the attack path will be accurately constructed by means of our novel solution which achieves the purpose of traceability of the attack source.

The wireless Internet of Things (IoT) is the future of Internet technologies in which every object around us will be connected using some kind of network to every other object, and they will have the capability to send and receive data from them. IoT will trigger a large range of use cases. One interesting and prominent use case is Vehicle-to-Everything (V2X) communications, which aim at revolutionizing the travelling experience especially within a smart city. The connected vehicles enable the exchange of information between the vehicle and its surroundings via the IoT. V2X communications face great challenges due to the special features in mobility, such as high mobility, frequent topology changes. Hence, as vehicles move in and out of the coverage areas of other vehicles, Wi-Fi and cellular base stations, and change their communication Point of Attachment (PoA), mobility management aims to provide a seamless communication by efficient handover strategies and Radio Access Technology (RAT) selection schemes. In this paper, we present a novel multi-criteria handover algorithm to select the best RAT for V2X communications. Fuzzy logic system is used to decide whether a target candidate is suitable for handover. The efficiency of our mechanism is evaluated through appropriate simulation by using OMNET++, SUMO and VeinsLTE framework. The properties of our mechanism satisfy the service continuity requirements while decreasing the V2V handover failure rate and the handover failure rate mode switch.

VANETs (Vehicular ad hoc networks) are an important communication to offer safety information and other infotainment applications to vehicles. To secure these networks, it is important to ensure the authentication and confidentiality of communicationV2V (vehicle to vehicle) and V2I (Vehicles to infrastructure). However, in VANET environments, vehicles are moving with a very high speed on the roads, so a strong security can degrade the performance of the protocol. Among the research that presents some schemes to secure VANET communications, we mention the Dual Authentication and Key Management Techniques that suffers from several lack of security. In this paper, we present an enhancement to this solution to obtain a deliberate compromise between quality of service and security. Security analysis proves that our scheme is secure and the result of performance validation is promising.

3G networks evolve to Long Term Evolution (LTE) in order to satisfy the increasing demands of data rates in both downlink and uplink, OPEX/CAPEX operators' requirements and needs for low service delay. LTE network is characterized by a scalable bandwidth capacity and ability to inter-operate with previous cellular technologies. In this paper, we consider a heterogeneous LTE network consisting of macro cells and femtocells. Femtocells are randomly deployed in macro cell area in order to improve indoor coverage as well capacity enhancement. Mixed types of traffic are considered ranging from real time to non real time flows, and quality of service is evaluated in term of throughput, packet loss ratio, fairness index and spectral efficiency. The aim of this study is to show limit of same algorithm in LTE system and also to propose candidate algorithms for next generation wireless systems.

Given wireless networks struggle with limited radio resources, to be able to transmit multimedia applications with specified Quality of service “QoS” requirements, including delay constraints, it's important to intensify the need for efficient resource allocation. Therefore, the best solution is to establish a partition of radio resources that provides a minimum quality for each user in the network. Here, it is necessary to establish a concession between the requirements of users and the available resources on the network. This can be achieved within a better radio resource management and the use of optimization techniques. The purpose of this paper is to find a solution that maximizes the quality of transmission by solving the problem of wireless channel partitioning. This solution is based on a technique that provides the optimal source data rate and the optimal bandwidth for each user with a guarantee of QoS requirements. Simulation results show that, using the spectral efficiency parameter for the evaluation, three main parameters must be considered to have the optimal source data rate and the optimal bandwidth, which are delay limit, delay violation probability and SNR average to achieve high spectral efficiency and to exploit optimally the resources of the channel.

In this work, we propose a new radio resource allocation scheme called ODM-QPC (Opportunistic Dual Metric scheduling based on Quality of service and Power Control), for the uplink LTE (Long Term Evolution) networks. The scheduler aims to allocate efficiently the Resource Blocks (RBs) with maximizing the system throughput and taking into account the fairness among users, while subject to the SC-FDMA constraints. Providing QoS requirements is also presented. In fact, it allocates a maximum number of RBs to each User Equipment (UE) according to its target QoS. Once RBs are allocated to UEs, Power Control (PC) is then applied to the mobile's emission power without affecting the user's throughput. The proposed radio resource algorithm has several interesting proprieties such as maximizing the aggregate throughput with considering equity, satisfaction of the QoS of users and reduction of the user's power depending on the user's channels conditions on the set allocated RBs.

The evolving fifth generation (5G) cellular wireless networks are envisioned to provide higher data rates, enhance end-user quality-of-experience (QoE), reduce end-to-end latency, and lower energy consumption. This article presents several emerging technologies which could enable and define future 5G mobile communication standards and cellular networks. This article discusses novel design techniques including dense hetergeounes networks and stochastic geometry as an approach that will be used to design 5G cellular networks and new features are discussed such as the new mm-wave , Massive Multiple Input Multiple Out (Massive MIMO)and new access technique (Filter Bank multi Carrier). FBMC, cloud Radio Acess Network C-RAN and virtualization of wireless resources . Finally, the study presents new 5G applications, namely Machine type communication and IoT .

Heterogeneity and convergence are two distinctive features of new generation of radio communication systems like the Long Term Evolution-Advanced (LTE-A) system. LTE-A enhancements focus on the four areas of capacity, coverage, inter-cells coordination, and cost. Improvements in these areas are based on using several technologies. Multiple-Input Multiple Output/Orthogonal Frequency Division Multiple Access (MIMO/OFDMA) are two of the base technologies that will act as enablers. In this paper, we motivate the importance of intertechnologies and inter-entities cooperation, which can exploit heterogeneity as an enabler to improve the system capacity as well as the quality of service (QoS) for users. We present a new cooperative radio resource allocation scheme for LTE-A network to coordinate better utilization of network's available radio resources. We adopted the the 802.21 Media Independent Handover protocol (MIH) framework, in order to facilitate the exchange between heterogeneous network entities so as to insure self-configuration of radio resource management parameters. We worked on allocating the right PRB to the right user at the right time. We also analyzed some existing solutions and evaluate our proposed scheme using simulation analysis. Simulation results illustrate the performance gains brought by the proposed optimizations, especially for average throughput of macro-cell users comparing to their initial performance within two-tier LTE-A network.

Given a wireless network topology, a maximum number of users with specified Quality of service “QoS” requirements, including delay constraints, are allowed to transmit and receive data. Therefore, the best solution is to establish a partition of radio resources that provides a minimum quality for each user in the network. If all users can not be served in the same time, it is important to classify them according to their delay constraints. Also, if a new user requests a new session in the network, some specifications should be considered not only for them but also for the existing users before being involved in the network. The purpose of this paper is to find a solution that maximizes the number of video users by solving the problem of wireless channel partitioning. This solution is based on two main assumptions: calculate the minimum bandwidth required by each video user and interpret the maximum allowed delay constraint guaranteeing QoS requirements. The simulation results show that our proposed method, compared to the fair resource allocation technique, increases significantly the number of served users.

In single cellular networks, the mobile stations cannot communicate directly with each other. All communications are relayed through the base stations. Such topology suffers from many limitations such as the congestion problem when a large number of users are communicating in the same time to a base station. In this context, the device-to-device communications have been proposed to overcome the limitations of the conventional cellular architecture. Indeed, a mobile station can allow two nearby stations to communicate with each other without involving a base station. However, security becomes an important challenge that must be taken into consideration as the mobile stations participate in routing data between each other. For that reason, we propose in this paper a secure routing protocol for Multi-hop Cellular Networks (MCNs). Our goal is to discover a secure and short route between the source and the destination. To evaluate this proposed protocol, we perform some simulations based on Network Simulator (NS-2) and crypto++ library. The simulation results show that it provides acceptable performance in terms of throughput and routing overhead as comparing with SAODV.

In Ad Hoc technology, a mobile node is characterized by a limited battery power. Therefore, the energy consumption becomes an important challenge that must be taken into account when designing a new Ad Hoc routing protocol. An efficient routing protocol should also consider a high level of Quality of Service (QoS) such as the end-to-end delay and the bandwidth as the applications do not have the same requirements. Moreover, avoiding some problems like the congestion problem becomes a necessity in order to enhance the system performance and decrease the energy consumption. In this paper, we propose a new routing protocol for Ad Hoc networks. The main objectives of this protocol are to increase the network lifetime and achieve a high level of QoS by selecting a multi-path that considers the energy constraint, traffic load and QoS requirements in terms of bandwidth and end-to-end delay. To evaluate our proposed protocol, extensive simulations are performed using Network Simulator (NS-2) tool. Simulation results show that our proposed protocol outperforms Ad Hoc On-Demand Distance Vector Modified (AODVM) in terms of Network lifetime, Packet delivery ratio and End-to-end delay.

Heterogeneity and convergence are two distinctive features for new generation networks like the Long Term Evolution-Advanced (LTE-A) system. LTE-A is now being deployed and is the way forward for high speed cellular services. LTE-A enhancements the four areas of capacity, coverage, inter-cells coordination, and cost. Improvements in these areas are based on using several technologies. Multiple-Input Multiple Output along with Orthogonal Frequency Division Multiple Access (MIMO/OFDMA) are two of the base technologies that are enablers. In addition, self-organizing and optimization (SON) technologies have been also developed to enable automatic configuration, optimization of network operations, including the 802.21 Media Independent Handover protocol (MIH), which is designed to optimize the vertical handover process. In this paper, we show the importance of inter-technologies and inter-entities cooperation, which can exploit heterogeneity as an enabler to improve the system capacity as well as the quality of service (QoS) for users. We present a new cooperative radio resource allocation scheme for LTE-A network to coordinate better the utilization of network's available radio resources. We adopted the MIH framework, in order to facilitate the exchange between heterogeneous network entities to insure self-configuration of radio resource management parameters. We worked on allocating the right PRB to the right user at the right time. We also analyze some existing solutions and evaluate our proposed scheme using simulation analysis. Simulation results illustrate the performance gains brought by the proposed optimization, especially for average throughput of macro-cell users comparing to their initial performance within two-tier LTE-A network.

Abstract Nowadays, many advanced are developed and become available for users. So, the demand for a higher data rate wireless access significantly increases. For that reason, new cellular wireless networks have been introduced such as Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) and LTE‐advanced. However, the centralized topology of these technologies requires that the users have a direct connection to the Base Station (BS). Such topology suffers from congestion problem when a large number of users are communicating in the same time. To overcome the congestion problem, the Device‐to‐device and the mobile relays communications have been proposed to overcome the limitations of the conventional cellular architecture. These technologies can improve the cellular network capacity and reduce the infrastructure costs. However, security in multi‐hop cellular networks (MCNs) is a great challenge especially when other mobile nodes participate in the routing process. Existing works on this topic focus on ensuring security for routing information. However, most studies do not secure the data transmission after the route selection and do not simultaneously ensure all the security requirements. In this paper, we propose a new secure and reliable routing protocol for MCNs. The main objective of this protocol is to select only the trustworthy intermediate nodes to participate in the route construction. These trustworthy nodes perform the route discovery process in a secure way and so discover a secure path that does not contain any attacker as an intermediate node. The intermediate nodes of the selected route participate in establishing a group key. This key is used to secure the data transmission phase after route selection. To achieve anonymity, the BS assigns to each mobile that participates in the selected route a temporary identity. We evaluate our proposed protocol in terms of security using AVISPA tool, and we conduct some simulations using Network Simulator (NS‐2). The simulation results show that it is reliable and provides acceptable performance in terms of throughput, end‐to‐end delay and normalized routing load. Copyright © 2016 John Wiley & Sons, Ltd.

Multi-hop Cellular Network (MCN) is a promising architecture aiming to enhance the performance of the current single hop cellular network. Indeed, it combines the flexibility of Ad Hoc networks and the benefits of the fixed infrastructure. The traffic is relayed through multi-hop communication, which can extend the coverage area and achieve high throughput. Providing security in this type of network is an important issue since the mobile nodes participate in the routing process. Many researchers focus on this topic by providing security for routing protocol and data transmission. In this paper, we propose a secure routing protocol for MCN. In this protocol, we address two challenges: ensuring confidentiality and integrity of routing discovery and establishing a session key to secure the data transmission after route selection. Simulation results show that the proposed protocol is efficient and it ensures a high security level against attacks.

In this paper, we propose an adaptive call admission control scheme based on higher order Markov chains to effectively handle the call blocking probability in 3GPP LTE femtocell networks supporting multimedia services with different classes of traffic and diverse bandwidth requirements. The accuracy of the approximate analytic model is validated by simulation analysis. The numerical results show that the proposed scheme is able to attain negligible call blocking probability without sacrificing resource utilization.

Wireless Mesh Networks (WMNs) are continuously overwhelmed with various kinds of security threats. Amongst these threats is Denial of Service (DoS) which represents a huge umbrella of powerful attacks. It is very essential to understand the complexities of these attacks and counter-mechanisms existed in the literature. The best antidote to defend against these attacks would be to resolve the problem at its root by identifying the source of the attacks. The traceback technique realizes such a forensic analysis of the internet traffic. In this paper, we explain our novel approach of IP traceback based on marking approach and that used the Chinese remainder theorem to conceive the communication protocol in WMN IEEE 802.11s environments. We evaluated the performance and the efficiency of our proposed scheme based on some collected evaluation metrics.

Currently, Network Mobility (NEMO) Basic Support protocol enables the attachment of mobile networks to different points in the Internet. It permits session continuity for all nodes in the mobile network to be reachable as the network moves. While this standard is based on the MobileIPv6 standard, it inherits these disadvantages such as security vulnerabilities. To manage the problems of NEMO, many schemes combine it with a network-based approach such as Proxy Mobile IPv6 (PMIPv6). Despite the fact that this latter expedites the real deployment of IP mobility management; it suffers from lack of security. Therefore, we propose an Efficient and Secure Mutual Authentication Mechanism during initial attachment in NEMO-based Proxy Mobile IPv6 Networks called EMA-NEMO based PMIPv6 in order to provide mutual authentication between a mobile router and diameter server during initial attachment of the mobile router to a PMIPv6 domain. Moreover, we evaluate the performance of our scheme using the Automated Validation of Internet Security Protocols and Applications (AVISPA) software which has proved that authentication goals are achieved.

Abstract In order to separate a host's identity from its location on the Internet, the Host Identity Protocol (HIP) was developed by the Internet Engineering Task Force as a mobility management solution. HIP provides a solid basis to enable secured mobility and multihoming features. Several extensions and proposals have been introduced in recent publications to improve the micro‐mobility features of HIP. Moreover, many other publications have dealt with the efficiency of Network Mobility (NEMO) management with HIP. However, the HIP‐based micro‐mobility management solutions adapted to NEMO scenario do not cover all security aspects requirements and still suffer from security flaws. Therefore, in this paper, a number of potential threats in the typical HIP with Rendez Vous Server are identified. A new secure and efficient scheme for network mobility management is also proposed to overcome the outlined ones. The proposed solution ensures strong authentication between network entities, reduces Denial of Service attacks, secures against Domain Name Server spoofing, reply, and eavesdropping attacks, and ensures end‐to‐end confidentiality and integrity protection. To analyze the security properties of the proposed scheme, we have performed automated formal specification and evaluation with the help of both the Automated Validation of Internet Security Protocols and Applications and the Security Protocol Animator, which have proved that authentication and confidentiality goals are achieved. Hence, the scheme is effective when an intruder is present. Copyright © 2014 John Wiley & Sons, Ltd.

Call admission control mechanisms play an important role in heterogeneous wireless networks where different radio access technologies will coexist to grant Quality of Service (QoS) in a network. They are used to decide whether or not an incoming service request will be accepted according to an admission constraint as well as determining in which radio access technology among the available it will be connected. In this paper, we propose an adaptive bandwidth management and call admission control scheme for heterogeneous wireless networks. The proposed scheme takes into account the separation between the incoming traffic for each class and prioritizes handoff calls over the new calls. The objectives of the proposed adaptive CAC approach are to guarantee QoS requirements of all accepted calls, reduce new call blocking probability and handoff call dropping probability and maintain efficient resource utilization.

This paper proposes a new approach for optimizing the handover decision and the target network selection process in 3GPP LTE-Advanced network. We aim to manage load state between LTE-Advanced cells, as well as between different existing Radio Access Technologies (RATs). In fact, a well-balanced load ensures the prevention of a congestion state. With Fourth generation networks, like LTE_A, the access layer includes all existing RATs. All of them are controlled by a unique core network. To managewith more flexibility and different interworked RATs, we adopt the MIH 802.21 protocol. Our proposed scheme offers to the Radio Resources Management (RRM) entity a dynamic and autonomous aspect in order to maintain the network performance. Finally, the performance of the proposed scheme is evaluated using simulation analysis.

The vital trend inside wireless networks is the heterogeneity of access technology. Vertical handover management is one of key challenges in such environment to ensure seamless mobility and service continuity especially in the case of network mobility. To deal with some of these challenges, numerous efforts were made in the context of standards and scientific research to perform the vertical handover process such as the IEEE 802.21 Media Independent Handover framework and the Network Mobility Basic Support Protocol. However, these optimizations stay insufficient to solve all issues. This paper proposes new mobility management framework in the case of Network Mobility handover. The proposed scheme is based on the principal concepts of IEEE 802.21 for context information gathering and optimized handover decision making. Also, a Modified P-NEMO for the handover execution phase is suggested to overcome the dependence of standardizations on the NEMO application deployment and the infrastructure network. Detailed simulations show that our proposed framework provides less complexity and better performance for enhancing vertical handover.

Heterogeneous Wireless Network aims to provide seamless services for mobile stations or mobile routers while roaming across different mobile communication networks. Designing secure and efficient authentication protocols to enable fast handover is one of key challenges in such heterogeneous environment. In this paper, we propose a new authentication protocol called SMM-NEMO (Secure Macro Mobility protocol for NEtwork MObility) which is a deliberate compromise between security and quality of service. It provides lower handover latency and protects against many attacks. The proposed protocol has been modeled and verified using the AVISPA (Automated Validation of Internet Security Protocols and Applications) and SPAN for AVISPA software and it is found to be a safe and efficient scheme.

The success of mobile communication shows the interest of a mobility support of the whole network. Hence, by extending existing host mobility solutions, Network Mobility (NEMO) protocol was developed by the Internet Engineering Task Force (IETF) to enable the movement of mobile nodes and networks while maintaining connectivity to their network or the Internet in case of mobility events. The emergence of NEMO is facing more and more problems linked to security threats. Thus, in order to achieve seamless handover in NEMO, we propose in this paper a Secure Micro Mobility for Network Mobility (SMM-NEMO) using AAA (Authentication, Authorization and Accounting) mechanism. This helps to efficiently authenticate and securely generate session keys. It enables the integration of authentication schemes with the mobility protocol Fast Handover for Hierarchical Mobile IPv6 (F-HMIPv6). This proposed protocol has been modeled and verified using the Automated Validation of Internet Security Protocols and Applications (AVISPA) software which has proved its security when an intruder is present.

Different wireless technologies have been standardized and commercialized, but none of these technologies is considered the best because each one has its own advantages and disadvantages. For example, Wireless Local Area Network (WLAN) offers bit rates surpassing those of Third generation (3G), but is found lacking with respect to roaming, mobility support and lack of sufficient security measures and architecture beyond basic radio access. Hence, inter-working between heterogeneous wireless networks is important to combine their best features and achieve the optimal in wireless communications. Security in inter-working is a major challenge due to the difference of security architectures between these wireless technologies. Therefore, several authentication protocols have been proposed to improve security such as Extensible Authentication Protocol for 3rd generation Authentication and Key Agreement (EAP-AKA) protocol which is used in 3G mobile networks to authenticate to non-cellular networks such as WLANs. In this paper, we analyze threats and attacks of this standard and we propose a re-authentication protocol from WLAN to LTE (ReP WLAN-LTE). This proposed solution allows a mobile connected to a WLAN to migrate to a LTE network. Moreover, it provides perfect forward secrecy to guarantee stronger security, mutual authentication, and resistance to replay attack. Through extensive simulation experiments, we found out that our proposed protocol presents optimal values for handoff latency and satisfactory loss rates, which meet the need for the quality of services.

Providing end-to-end support for Quality of Service (QoS) guarantees is a central and critical issue in heterogeneous networks. In this paper, we address the problem of assigning delay budgets to each network node along the routing path so that the end-to-end delay requirements of the supported applications are met. In order to meet the QoS requirements of multimedia applications, different scheduling algorithms are used. Each scheduling service is characterized by a mandatory set of QoS parameters, which is tailored to best describe the guarantees required by the applications. In this paper, we propose a new method for distributing end-to-end delay in the heterogeneous networks. We show that our scheme can achieve better delay distribution. Further, we evaluate the performance of our proposed scheme using simulation analysis.

ABSTRACT Wireless mesh networks are one of the most important improvements in the world of wireless technologies. In fact, they offer many advantages to ensure a free mobility and a self‐configuration of the various network equipment, a better quality of services, as well as an extensible domain and area. In spite of all of these contributions, mesh technology still suffers from some problems such as security especially in handoff phases. In this study, we propose an authentication scheme that is designed to reduce the authentication delay during a wireless mesh network handoff process. The proposed mechanism takes into account the mobility of clients as well as the router movements. This work takes advantage of some existing techniques such as Blom key predistribution scheme and Du key process generation method. Our simulation results prove the effectiveness of our proposed scheme. Our performance evaluation results shows that the suggested solution outperforms existing schemes in improving handoff latency values (<15 ms) and in the ability of satisfying the requirements of security as well as the quality of services in terms of having low loss rate (less than 1%) and having a low blocking rate. Copyright © 2012 John Wiley & Sons, Ltd.

Satisfying quality of service (QoS) is one of the main goals of the wireless fourth generation (4G), which will integrate tightly a multitude of different heterogeneous networks including cellular networks (second generation, third generation, wireless local area networks, bluetooth, etc). In this paper, we develop an information-theoretic framework for optimal location updating and paging for wireless 4G network, which integrate tightly many different access networks. Then, we adopt the LZW compression algorithm as the basis of our location management schemes. Simulation results demonstrate that our proposed schemes decrease the signaling cost.