ABSTRACT Unmanned Aerial Vehicle (UAV) networks are increasingly deployed in dynamic environments where reliable and low‐latency communication is critical. However, high mobility, intermittent connectivity, spectrum limitations, and energy constraints make conventional static communication protocols inadequate for maintaining stable, dependable links. To address these challenges, this paper proposes TRC‐MAPPO, a topology‐aware reliability‐constrained multi‐agent deep reinforcement learning framework for adaptive UAV swarm communication. The routing problem is formulated as a constrained decision‐making task that jointly considers packet delivery reliability, end‐to‐end delay, link stability, bandwidth usage, and energy consumption. Unlike single‐agent DRL baselines, TRC‐MAPPO represents the swarm as a dynamic communication graph and combines local relay selection with centralized training, enabling cooperative routing decisions under time‐varying network conditions. Simulations are conducted in a controlled, dynamic UAV environment, with the same mobility and traffic settings used for all methods. The proposed framework is compared with DQN and PPO over different swarm densities. Results show that TRC‐MAPPO achieves a higher packet delivery ratio, lower end‐to‐end delay, and more efficient energy behaviour, particularly in dense deployments. These findings indicate that topology‐aware cooperative learning can provide a scalable and practical solution for reliable UAV communication in future intelligent aerial and 6G‐enabled networks.

Ensuring reliable transmission and secure communication remains a critical challenge for next-generation wireless networks, particularly in the context of sixth-generation (6G) and Internet of Things (IoT) systems. This paper investigates the reliability and physical layer security of active reconfigurable intelligent surface (ARIS)-assisted dual-hop relaying in non-orthogonal multiple access (NOMA) networks over Nakagami-mfading channels. We develop a comprehensive system model where a base station communicates with two users via a relay and an ARIS, in the presence of a potential eavesdropper. Closed-form expressions for outage probability (OP) and intercept probability (IP) are derived for both near and far users, capturing the effects of ARIS configuration, power allocation, and channel fading. Extensive Monte Carlo simulations confirm the accuracy of the analytical results and reveal that increasing the number of ARIS elements, optimizing amplification factors, and carefully allocating power can significantly enhance both reliability and secrecy performance. The findings provide valuable insights for the design of robust and secure ARIS-assisted NOMA networks in practical wireless environments.

The advent of next-generation Internet of Things (IoT) networks necessitates communication capabilities characterized by ultra-reliability and low latency (URLLC) and energy efficiency requirements that traditional wireless designs frequently struggle to satisfy under practical constraints. In this context, realizing symbiotic IoT networks using mutualism backscattering technologies with short-packet transmissions has emerged as a viable solution to achieve the goals of net zero for sustainable IoT network deployment while satisfying URLLC conditions. Following that, this paper first develops theoretical frameworks for evaluating the performance of short packet transmissions in uplink symbiotic systems by deriving formulas for the block error rate (BLER) and total symbiotic ergodic rate under two diversity techniques, namely selection combining with maximal-ratio combining (SC-MRC) and full maximal-ratio combining (Full-MRC). Then, we scale up this considered system for large-scale IoT networks, where we propose an energy-aware resource allocation method using successive convex approximation (SCA) techniques for multi-user scenarios while adhering to URLLC conditions. Finally, simulation results are provided to validate the developed theoretical analyses as well as demonstrate how our proposed optimization solution achieves substantial improvements in energy efficiency performance. These findings lay a robust groundwork for developing scalable and dependable communication systems in future energy-efficient IoT eras.

In this article, we describe a novel active reconfigurable repeater-aided nonorthogonal multiple access networks within the context of the Internet of Things. The study focuses on a scenario, where a source simultaneously transmits public information to an untrusted user and a covert signal to a legitimate user in the surveillance of an external warden or eavesdropper. We develop comprehensive analytical and optimization frameworks to evaluate the reliability, security, and covertness of the proposed system’s performance, measuring three respective key metrics: 1) outage probability (OP); 2) secrecy OP (SOP); and 3) detection error probability (DEP). First, we derive exact closed-form and asymptotic expressions for OP, SOP in internal and external eavesdropping scenarios, and DEP in external monitoring situations. Based on an asymptotic analysis of the OP, we propose two optimization methods for power allocation (PA) to achieve fairness in outage among users: 1) a convex approximation method and 2) an approximate closed-form solution. We then introduce an alternative method for optimizing PA to improve SOP in both eavesdropping scenarios while maintaining minimal OP requirements. In addition, we propose an effective approach for determining the warden’s detection threshold to minimize the DEP, with low complexity and fast convergence, thereby improving communications covertness. Finally, we validate the theoretical and optimization frameworks through extensive Monte Carlo simulations, exploring the impact of key system parameters on each performance metric.

This work investigates the covertness and security performance of Internet-of-Things (IoTs) networks under Rayleigh fading environments. Specifically, a cellular source transmits covert information to cell-edge users with the assistance of an IoT master node, employing a coordinated direct and relay transmission strategy combined with non-orthogonal multiple access (NOMA). This approach not only enhances spectrum utilization but also generates friendly interference to complicate a warden’s surveillance or an eavesdropper’s decoding efforts. From a covertness perspective, we derive exact closed-form expressions for the detection error probability (DEP) under arbitrary judgment thresholds. We then identify the optimal judgment threshold for the worst-case scenario, at which the warden minimizes its DEP performance. Accordingly, we determine the effective region for user power allocation (PA) in NOMA transmission that satisfies the DEP constraint. From a security perspective, we derive analytical expressions for the secrecy outage probability under two eavesdropping strategies using selection combining and maximal ratio combining. Based on this analysis, we propose an adaptive PA scheme that maximizes covert rate while ensuring the quality-of-service (QoS) requirements of legitimate users, the system’s minimum covertness requirements, and supporting successive interference cancellation (SIC) procedures. Furthermore, we design an adaptive PA scheme that maximizes the secrecy rate while ensuring the QoS requirements of legitimate users and SIC conditions. Numerical results demonstrate the accuracy of the analytical framework, while the proposed optimization strategies effectively adjust PA coefficients to maximize either the covert rate or the secrecy rate.

In this study, we investigate the trade-off between reliability and security in unmanned aerial vehicle (UAV) communications systems, considering a UAV-terrestrial network aided by a relay powered by a dedicated power beacon. For this system, we derive the outage probability (OP) under both exact and approximate frameworks and compute the approximations in the closed-form expressions. For the security aspect, we also derive the intercept probability (IP) under exact and approximated frameworks. To minimize the IP, a friendly jamming technique is employed whereby the power beacon constantly broadcasts artificial noise (AN) toward an eavesdropper. Based on the derived mathematical framework, we then formulate a bi-objective optimization problem by jointly minimizing the OP and IP with respect to the UAV’s position and the time-switching (TS) ratio. A suitable algorithm, named non-dominated sorting genetic algorithm version II (NSGA-II), is deployed to obtain the sub-optimal solution. Finally, numerical results are presented to verify the accuracy of the proposed mathematical framework and the superiority of jointly minimizing both the OP and IP using only the channel statistics.

This study investigates a two-way relaying non-orthogonal multiple access (TWR-NOMA) enabled Internet-of-Things (IoT) network, in which two NOMA users communicate via an IoT access point (IAP) relay using a decode-and-forward (DF) protocol. A power beacon (PB) is used to power the IAP to address the IAP's limited lifetime due to energy constraints. Since co-channel interference (CCI) is inevitable in IoT systems, this effect is also studied in the proposed system to improve practicality. Based on the proposed system model, the closed-form equations for the exact and asymptotic outage probability (OP) and ergodic data (ED) of the NOMA users' signals are first derived to describe the performance of TWR-NOMA systems. The system's diversity order and throughput are then evaluated according to the derived results. To further improve the system's performance, a low-complexity strategy 2D golden section search (GSS) is performed, subject to power allocation (PA) and time-switching (TS) factors, to optimize the outage performance. Finally, a deep learning design with minimal computing complexity and precision OP prediction is established for a real-time IoT network configuration. The numerical results are discussed and analyzed in terms of the effects of the CCI, the TS ratio, the PA factor, the fading parameter on the OP, system throughput, and ED.

This article proposes an integration of multiple reconfigurable intelligent surfaces (RISs) with a relay to enhance the performance of a low-power wide-area (LPWA) network. Specifically, besides using the traditional relaying approach to assist the transmission between an Internet of Things (IoT) sensor and a gateway, multiple RISs are also utilized to boost the intermediate links between the IoT sensor and the relay and between the relay and the gateway. We mathematically derive the analytical expressions of average outage probability (AOP) and average symbol error probability (ASEP) of this multiple-RIS-relay aided LPWA network over Nakagami-$m$fading channels. The performance of the proposed network is also compared with the performance of the relay-aided LPWA network without using RISs. The analytical results show that the exploitation of RISs can greatly enhances the performance of the LPWA network. Thus, the multiple-RIS-relay aided LPWA network can operate at the high frequency band for long range transmission. Moreover, the effect of various important factors such as the location of the RISs, the Nakagami-$m$parameters, the data transmission rate, and the modulation scheme on the performance of the multiple-RIS-relay aided LPWA network are also investigated in practical scenarios.

Radio-frequency (RF) energy harvesting (EH) in wireless relaying networks has attracted considerable recent interest, especially for supplying energy to relay nodes in the Internet of Things (IoT) systems to assist the information exchange between a source and a destination. Moreover, limited hardware, computational resources, and energy availability of IoT devices have raised various security challenges. To this end, physical-layer security (PLS) has been proposed as an effective alternative to cryptographic methods for providing information security. In this study, we propose a PLS approach for simultaneous wireless information and power transfer (SWIPT)-based half-duplex (HD) amplify-and-forward (AF) relaying systems in the presence of an eavesdropper. Furthermore, we take into account both static power splitting relaying (SPSR) and dynamic power splitting relaying (DPSR) to thoroughly investigate the benefits of each one. To further enhance secure communication, we consider multiple friendly jammers to help prevent wiretapping attacks from the eavesdropper. More specifically, we provide a reliability and security analysis by deriving closed-form expressions of outage probability (OP) and intercept probability (IP), respectively, for both the SPSR and DPSR schemes. Then, simulations are also performed to validate our analysis and the effectiveness of the proposed schemes. Specifically, numerical results illustrate the nontrivial tradeoff between reliability and security of the proposed system. In addition, we conclude from the simulation results that the proposed DPSR scheme outperforms the SPSR-based scheme in terms of OP and IP under the influences of different parameters on system performance.

Simultaneous wireless information and power transfer (SWIPT) and full-duplex (FD) communications have emerged as prominent technologies in overcoming the limited energy resources in Internet of Things (IoT) networks and improving their spectral efficiency (SE). This article investigates the outage and throughput performance for a decode-and-forward (DF) relay SWIPT system, which consists of one source, multiple relays, and one destination. The relay nodes in this system can harvest energy from the source’s signal and operate in the FD mode. A suboptimal, low-complexity, yet efficient relay selection scheme is also proposed. Specifically, a single relay is selected to convey information from a source to a destination so that it achieves the best channel from the source to the relays. An analysis of outage probability (OP) and throughput performed on two relaying strategies, termed static power splitting-based relaying (SPSR) and optimal dynamic power splitting-based relaying (ODPSR), is presented. Notably, we considered independent and nonidentically distributed (i.n.i.d.) Rayleigh fading channels, which pose new challenges in obtaining analytical expressions. In this context, we derived exact closed-form expressions of the OP and throughput of both SPSR and ODPSR schemes. We also obtained the optimal power splitting ratio of ODPSR for maximizing the achievable capacity at the destination. Finally, we present extensive numerical and simulation results to confirm our analytical findings. Both simulation and analytical results show the superiority of ODPSR over SPSR.

Named data networking (NDN) is a disruptive yet promising architecture for the future Internet, in which the content diffusion mechanisms are shifted from the conventional host-centric to content-centric ones so that the data delivery can be significantly improved. After a decade of research and development, NDN and the related NDN forwarding daemon implementations are now mature enough to enable stakeholders, such as telcos, to consider them for a real deployment. Consequently, NDN and IP will likely cohabit, and the future Internet may be formed of isolated administrative domains, each deploying one of these two network paradigms. The security question of the resulting architecture naturally arises. In this paper, we consider the case of denial of service. Even though the interest flooding attack (IFA) has been largely studied and mitigated through NACK packets in pure NDN networks, we demonstrate in this paper through experimental assessments that there are still some ways to mount such an attack, and especially in the context of coupling NDN with IP, which can hardly be addressed by current solutions. Subsequently, we leverage the hypothesis testing theory to develop a generalized likelihood ratio test adapted to evolve IFA attacks. Simulations show the relevance of the proposed model for guaranteeing the prescribed probability of false alarm and highlight the trade-off between detection power and delay. Finally, we consider a real deployment scenario where NDN is coupled with IP to carry HTTP traffic. We show that the model of IFA attacks is not very accurate in practice and further develops a sequential detector to keep a high detection accuracy. By considering data from the testbed, we show the efficiency of the overall detection method.

In this paper, we derived the analytical expressions of the system performance (in term outage probability and throughput) of the power splitting half-duplex power beacon-assisted energy harvesting relay network in both amplify-and-forward and decode-and-forward modes. Moreover, the analytical results are also demonstrated and convinced by using Monte-Carlo simulation. The numerical results demonstrated and convinced the analytical and the simulation results are matched well with each other in connection with all possible system parameters.

Named Data Networking (NDN) is the most mature proposal of the Information Centric Networking paradigm, a clean-slate approach for the Future Internet. Although NDN was designed to tackle security issues inherent to IP networks natively, newly introduced security attacks in its transitional phase threaten NDN's practical deployment. Therefore, a security monitoring plane for NDN is indispensable before any potential deployment of this novel architecture in an operating context by any provider. We propose an approach for the monitoring and anomaly detection in NDN nodes leveraging Bayesian Network techniques. A list of monitored metrics is introduced as a quantitative measure to feature the behavior of an NDN node. By leveraging the hypothesis testing theory, a micro detector is developed to detect whenever the metric significantly changes from its normal behavior. A Bayesian network structure that correlates alarms from micro detectors is designed based on the expert knowledge of the NDN specification and the NFD implementation. The relevance and performance of our security monitoring approach are demonstrated by considering the Content Poisoning Attack (CPA), one of the most critical attacks in NDN, through numerous experiment data collected from a real NDN deployment.

The energy harvesting amplify-and-forward full-duplex relaying network over the dissimilar fading environments in imperfect CSI condition is investigated. In this system model, the energy, and information are transferred from the source to the relay nodes by the power splitting protocol with helping of the full-duplex relay node. Firstly, the outage probability, achievable throughput, and the optimal power splitting factor in terms of the analytical mathematical expressions were proposed, analyzed, and demonstrated. Furthermore, the system performance of the proposed model on the connection with all system parameters is rigorously studied. Finally, the numerical results demonstrated and convinced one that the analytical and the simulation results are matched well with each other for all system parameter values using Monte-Carlo simulation. The results show that the system performance degrades significantly but is still in a permissible interval while the channel estimation error increases and the system performance of the mixing scenarios is better in comparison with the Rayleigh-Rayleigh scenario.

We investigate the system performance of a two‐way amplify‐and‐forward (AF) energy harvesting relay network over the Rician fading environment. For details, the delay‐limited (DL) and delay‐tolerant (DT) transmission modes are proposed and investigated when both energy and information are transferred between the source node and the destination node via a relay node. In the first stage, the analytical expressions of the achievable throughput, ergodic capacity, the outage probability, and symbol error ratio (SER) were proposed, analyzed, and demonstrated. After that, the closed‐form expressions for the system performance are studied in connection with all system parameters. Moreover, the analytical results are also demonstrated by Monte Carlo simulation in comparison with the closed‐form expressions. Finally, the research results show that the analytical and the simulation results agree well with each other in all system parameters.

Information Centric Networking (ICN) is seen as a promising solution to re-conciliate the Internet usage with its core architecture. However, to be considered as a realistic alternative to IP, ICN must evolve from a pure academic proposition deployed in test environments to an operational solution in which security is assessed from the protocol design to its running implementation. Among ICN solutions, Named Data Networking (NDN), together with its reference implementation NDN Forwarding Daemon (NFD), acts as the most mature proposal but its vulnerability against the Content Poisoning Attack (CPA) is considered as a critical threat that can jeopardize this architecture. So far, existing works in that area have fallen into the pit of coupling a biased and partial phenomenon analysis with a proposed solution, hence lacking a comprehensive understanding of the attack's feasibility and impact in a real network. In this paper, we demonstrate through an experimental measurement campaign that CPA can easily and widely affect NDN. Our contribution is threefold: (1) we propose three realistic attack scenarios relying on both protocol design and implementation weaknesses; (2) we present their implementation and evaluation in a testbed based on the latest NFD version; and (3) we analyze their impact on the different ICN nodes (clients, access and core routers, content provider) composing a realistic topology.

Confronting the changing demand of users, the current Internet is revealing its limitations. Information Centric Network (ICN) are Future Internet proposals which are based on named data objects. In order to actually replace its predecessor, ICN must be able to resist existent threats in the current Internet, especially the Denial of Service (DoS) attack. In this paper, we focus on Interest flooding - a new type of DoS attack in Content Centric Network (CCN). Several solutions for this threat have been introduced, but they do not solve the problem in a satisfying way because of some drawbacks in either their detection performance, scalability support or restricted scenario of usage. Our goal is to design a reliable, low resources-consuming detection method against Interest flooding attack in CCN. A detection scheme must be attended since a lot of resources consumed by unnecessarily continuous countermeasure can be saved by a dependable detector. Like no other detectors in proposed solutions, our detector is based on statistical hypotheses testing theory. The achieved result is a low resources-consuming detector that can be deployed globally on each CCN router. The false alarm probability of our detector can be controlled at will. Its statistical power can be theoretically established and evaluated precisely. To validate our contribution, numerical results show the relevance of the proposed approach and the sharpness of theoretical results.