As the Internet of Things (IoT) rapidly expands, there is a growing need for advanced routing solutions that accommodate constrained devices and diverse network requirements. Traditional single-metric routing approaches typically focused on parameters such as delay, hop count, or Maximum Transmission Unit (MTU), lack the adaptability required by IoT environments where energy efficiency, bandwidth considerations, and security constraints must be balanced. A more flexible protocol could improve network performance and prolong device lifetimes. To this aim, building on the extensibility of AODVv2, we developed and integrated a multi-metric routing protocol into the ns-3 simulator. Our implementation allows for the prioritization of multiple factors, such as residual battery levels, node reliability, and hop count, through a customizable metric ordering. Using Type-Length-Value (TLV) encoding, the protocol seamlessly incorporates additional metrics without compromising existing functionalities. Experimental results demonstrate that our multi-metric AODVv2 outperforms the original AODVv2 in terms of network performance, reduces energy consumption, and enhances the overall network longevity, thus providing significant benefits for IoT network management. Our released code paves the way for the programmability of other routing metric systems, including battery discharge rates, and the development of dynamic trust adjustment mechanisms for robust and adaptive routing.

Current literature has identified several issues with centralized mobility management in 5G-based Intelligent Transportation Systems (ITS), where 5G-enabled vehicles are expected to exhibit varying mobility patterns. So, distributed mobility management (DMM), where control plane mobility anchors work in a distributed fashion, is of keen interest to current researchers. Although existing DMM solutions, such as distributed mobile IPv6 (DMIPv6), distributed proxy MIPv6 (DPMIPv6), distributed mobility management software defined networking (SDN-DMM), distributed routing (D-Routing), and their derivatives appear to work fine in evolving 5G-based ITS, they cannot be applied directly. Further, to gauge their adaptability to different ITS scenarios, a thorough investigation of their performances is very much needed. Our key contributions in this paper include investigating DMM issues in 5G-based ITS scenarios, porting DMM schemes in 5G ITS, and developing a Markov model to evaluate handoff performance. The results show that DMIPv6 and DPMIPv6 outperform SDN-DMM and D-Routing in terms of end-to-end delay and signaling cost, with the latter increasing delay by 6-23% and signaling cost by 135% and 78%, respectively. However, SDN-DMM and D-Routing excel in packet loss ratio (15-20% lower), throughput (20-25% higher), and packet delivery cost (40% lower). In edge cloud flow mobility, SDN-DMM and D-Routing show better packet loss ratio as packet loss is caused by servers’ sensitive application delays rather than handoffs.

The Internet of Things is emerging as a key concept, defining a network of interconnected devices capable of seamless data collection, exchange, and analysis. However, due to their emphasis on simplicity, these devices are often vulnerable to malware attacks. This study examines the potential of machine learning methods, specifically in the context of Federated Learning, to enhance privacy protection and to benefit from IoT’s decentralized nature, such as the low overhead traffic. The proposed approach is a federated machine learning algorithm based on a central aggregator and several clients. The study aims to conduct a comprehensive analysis using the IOT-23 dataset, which contains real and labeled instances of malware infections. The test outcomes demonstrate that the proposed approach outperforms centralized approaches regarding the global area under the precision-recall curve (AUPRC) and variance, with a significance level of 0.05.

Machine learning (ML) has emerged as a compelling approach to identify attacks in network traffic security. Existing malware detection strategies often concentrate on specific facets, such as efficient data collection, particular types of malware, or handling data scarcity. While valid, these strategies typically overlook the potential for minimizing sample size, focusing instead on data augmentation. This work introduces a novel method to determine the minimum sample size necessary to achieve a specified accuracy level, measured by the F1 score derived from the confusion matrix. We focus on TCP header traffic data transformed into images through flow-splitting techniques for multi-class traffic classification. In addition, we introduce a diffusion model to generate new synthetic traffic images and show that our method outperforms existing techniques in terms of stability and predictability. This study also compares the effectiveness of synthetic image augmentation using Generative Adversarial Networks (GANs) and Denoising Diffusion Probabilistic Models (DDPM) in improving image recognition and classification accuracy.

The adoption of Extended Reality (XR) technology has been hindered by the need for high-bandwidth and low-latency networks to provide immersive experiences. Head-mounted devices used in XR are still heavy and not portable, limiting the potential of XR applications in various contexts. In this paper, we propose EdgeVerse, a multi-user XR system that leverages edge computing and extended Berkeley Packet Filter (eBPF) to offload computation, thereby reducing the dependency on high-bandwidth networks in support of XR applications. Our approach enables lightweight clients, such as devices with an edge browser, making XR more accessible to users. The key design of EdgeVerse focuses on offloading the connection and network synchronization of multiple XR users at the edge. We used an XDP bidirectional router that processes XR traffic faster to enhance user interaction, responsiveness, and immersive experience. To establish the practicality of our approach, we evaluate our results on a prototype that indicates improved response times and reduced latency with respect to baseline solutions.

The Internet of Things (IoT) paradigm is assumed to be a major component in the present and future Internet, with forecasts claiming a humongous number of devices connected in the near future, and applications fields spanning from agriculture, to healthcare. Despite this, the standardization efforts have not yet resulted in widely adopted standards, and the market is fragmented into multiple solutions both at physical and communication protocol levels. Moreover, IoT systems exacerbate the usual test bed limitations, e.g., scalability (very large number of devices), hardware compatibility, space, and price. Due to the above problems, simulation tools become an extremely interesting tool for studying IoT systems both for academia (new algorithms), standardization (new protocols), and industry (what-if analysis). In this paper we will discuss what are the most relevant features and models that a simulation tool like ns-3 should prioritize to enable the above-mentioned needs from academia, standardization, and industry, and if they are achievable in the short, medium, or long term.

Low-Power and Lossy Networks (LLNs) are based on constrained devices. Energy conservation is one of the main constraints, and the traditional IPv6 Neighbor Discovery Protocol (IPv6-NDP) was neither designed nor suitable to cope with it. This inefficiency arises from non-transitive wireless links and heavy multicast transmission, sometimes rendering it impractical in LLNs. Substantial work has been done by the Internet Engineering Task Force (IETF) to optimize the IPv6-ND protocol, known as IPv6 over Low power Wireless Personal Area Network - Neighbor Discovery Protocol (6LoWPAN-NDP). Despite these improvements, full implementation is yet to be achieved in commercial, open-source, or proprietary sectors. In this article, we debate both Neighbor Discovery Protocols (NDPs), examining various aspects. We implemented 6LoWPAN-NDP in a well-known ns3 simulator. We discuss the complexity of 6LoWPAN-NDP and see why open-source, commercial, or proprietary sectors have not widely adopted it. We present how both protocols function optimally in meshunder and non-meshunder scenarios. We present results and analysis of both NDPs control messages’ behavior. At the same time, data traffic is turned on and off, and we demonstrate the operational behavior of Link-local Unicast Address (LUA) and Global Unicast Address (GUA) in meshunder and non-meshunder scenarios. The presented implementation can be helpful in enabling large-scale simulations and evaluating scenario-specific protocol parameters, along with protocol extensions.

This paper analyzes the end-to-end delay performance in an edge-computing scenario where a set of Internet of Things devices (IoTDs) access the computation facilities of an Edge Node by means of a 5G based network. In particular, the paper deals with a two power levels slotted Aloha non-orthogonal-multiple-access (NOMA) scheme and formulates a stochastic end-to-end delay bound, in terms of complementary cumulative probability distribution, by resorting to the application of the martingale theory. In order to validate the proposed analysis, the paper proposes comparisons between the achieved analytical predictions and actual values derived by resorting to extensive computer simulations. Furthermore, the well known Boole bound has been formulated and compared with the proposed Martingale approach to highlight the better behavior of the proposed solution.

Securing Internet of Things (IoT) devices and protecting their applications from privacy leaks is a challenge, due to their weak (computational and storage) capabilities, and their proximity with sensitive data. Considering the resource-constrains of such devices, their long lifetime, and the intermittent connections, classical security approaches are often too difficult or impractical to apply. Moving target defense is an established technique whose goal is to lower the attack surface to malicious users by constantly modifying device footprint. Changing the address to an IoT device without privacy leaks is, however, a nontrivial task. In this paper, we propose a novel method to perform a network-wide (Internet protocol and medium access control) address shuffling procedure, called address shuffling algorithm with HMAC (AShA), which is simple to implement, and whose network overhead is minimal. To demonstrate its effectiveness, we analyze our approach via theoretical analysis and simulations. Our analysis shows how AShA parameters can be adapted to various network sizes while our simulations results show how AShA can be used to successfully perform a global collision-free address renewal on networks of more than 2000 nodes using 16-bit addresses.

This paper proposes a channel allocation scheme for Wide-Area Low-Rate Wireless Personal Area Networks (LR-WPAN) based on a cooperative centralized spectrum sensing approach. We refer here to a three-tiers LR-WPAN architecture, where we can distinguish the sensor devices level, the Child-coordinators level and, finally, the super LR-WPAN coordinator level. In the proposed scheme, channels allocation is performed by the LR-WPAN coordinator upon receiving the spectrum sensing reports from the Child-coordinators. The performance of the proposed scheme is evaluated in terms of resulting detection probability and throughput, in a scenario where Industrial, Scientific and Medical (ISM) bands are saturated and different LR-WPANs compete to the channel access. Performance comparisons with a classical scheme where the channel allocation is accomplished without performing spectrum sensing, are also presented in order to highlight the advantages of the proposed scheme.

With the increasing use of Wireless Sensor Networks, the privacy of the user is of main concern. The sensors maintain a layer 2 address that lasts for the node lifetime. As a consequence, an eavesdropper can easy trace the user and his activities, even in case the nodes send ciphered traffic.We propose a 6LoWPAN-ND extension to improve privacy and overcome the traceability of the user. With our method all the nodes change periodically all their addresses, both at layer 2 and 3. The method requires a small overhead and leverages on existing 6LoWPAN messages. The security is analyzed to show the effectiveness of our work and its energy requirements.

Recently, the self organization approach has been incorporated into the 3rd Generation Partnership Project (3GPP) standards in order to implement mechanisms such as auto configuration, auto healing, and self optimization of the deployed network architecture. However, the Self Organization Networks (SONs) functionalities in Long Term Evolution (LTE) do not include Heterogeneous Networks (HetNets) scenarios that involve trusted non-3GPP access points (e.g., trusted Wi-Fi networks). Moreover, fulfill Quality of Experience (QoE) for users on a perapplication base, it is not the goal of SON. In this paper, we will focus on the requirements for the next-generation SON, which should aim at assisting the Mobile Network Operator (MNO) in order to maintain the QoE by using per-flow optimization, taking into account the latest proposals about data offloading and the simultaneous use of multiple interfaces.

ABSTRACT This paper proposes a new method of data authentication and encryption for distributed networks supporting mobile software agents. Software agents are a valuable instrument in wireless distributed monitoring networks, because they can be used to concentrate monitoring efforts in certain areas where an event is taking place. In this way, events can be tracked in a dynamic and efficient way. Mobile agents have to send messages to each other in order to coordinate their actions, and those messages need to be secured by crypto credentials. However, when agents are moved over wireless networks, how can credentials be protected from sniffing by an attacker, besides layer II encryption? Moreover, if a rogue agent is injected in the network, is it possible to limit the damages it can produce? The proposed approach bridges mediated RSA with the trusted platform modules, in order to provide an efficient and secure communication between agents. The communication is secured using indeed Identity based cryptography, while maintaing the compatibility with standard RSA and eliminating the mediator introduced by mediated RSA. We will show that this approach is convenient in terms of traffic overhead, perfectly applicable to existing trusted platform modules specifications and able to limit damages that both external and internal attackers can produce to the network. Copyright © 2013 John Wiley & Sons, Ltd.

This paper deals with the issue of reliably transmission of short messages through satellite. The problem is of paramount importance for emergency and alerting scenarios. In particular, we propose a novel efficient Network Coding (NC) communication scheme aiming to improve the delivery probability of the transmitted information messages. A suitable analytical approach has been developed in order to highlight the performance of the proposed NC scheme and to allow its optimization. The accuracy of the proposed approach has been validated by resorting to computer simulations. Performance comparisons with the classical NC scheme are also presented here to highlight the advantages of the proposed NC scheme in the case of AWGN and Rician communication channels.

This work focuses on providing effective end-to-end (E2E) communications for critical monitoring applications through Wireless Sensor Networks. In particular, the case of frequent disconnection and reconnection has been analyzed, deriving effective routing strategies to cope with this problem. Basing on a recent IETF draft scheme, namely RPL, capable of accommodating several practical situations, a novel approach, called eN Route (NR), has been proposed. In particular, it relies on a two tier network architecture with a hybrid tree-mesh topology, which can be locally rearranged depending on link failures, mainly due to mobility. This is done in a completely distributed way by maintaining a specific neighbor table built only by sniffing data messages to not increase the signaling overhead. The proposed solutions functionalities have been described and compared in terms of connectivity efficiency, E2E path length distribution and E2E latency statistic, giving also some figures on overhead. The analyses have shown NR to achieve better results in in terms of network connectivity latency and overhead, despite some drawbacks, even though RPL is able to achieve comparable performance at the expenses of higher signaling overhead. As a consequence, it has been pointed out the way RPL future releases can profit from NR approach to improve performance.

This paper deals with the allocation of resources and the creation of distribution trees for P2P video streaming. Assuming that the video distribution is based on a multiple description codec (MDC), the proposed approach performs jointly the two tasks, in a completely distributed client-based fashion, by means of an evolutionary (socially inspired) game played by all peers. The key idea of the evolutionary game is that each peer continuously measures its own utility (i.e., video quality) and, by periodical comparison with other randomly chosen peers, tries to mimic the behavior (i.e., resource allocation and video distributors) of peers with higher utility. Extensive simulation experiments by Peersim have been carried out in order to assess the performance of the proposed technique. The obtained results have highlighted remarkable benefits in terms of scalability, fast adaptation to churning, high degree of cooperation among peers and self-organization of the distribution multi-tree network.

Are P2P systems and applications here to stay? Or are they a bright meteor whose destiny is to disappear soon? In this paper we try to give a positive answer to the first question, highlighting reasons why the P2P paradigm should become an integral part of computing and communication services and not only oddities for Cyber-geeks.

The paper studies the performance of the bandwidth request procedure for a proactive digital video broadcasting - return channel satellite (DVB- RCS) terminal in comparison with a reactive one. The proactive terminal uses an adaptive predictor to forecast the future input traffic flow along with a predictive bandwidth controller to generate bandwidth requests according to a receding horizon policy. On the other hand, the reactive terminal generates requests, at the end of each frame, depending on the current queue lengths [1] [2]. The simulated scenario involves adaptive coding and modulation (ACM) techniques and Quality of Service (QoS) management. Simulation experiments highlight the effectiveness of the proactive bandwidth control under different traffic load and channel conditions.

In modern wireless communication systems, power control plays a fundamental role for efficient resource utilization, in particular in the systems where the users share the same bandwidth at the same time. In such systems, in fact, many users transmit over the same radio channel using the same frequency band and time slots so that the signal of an individual user becomes interference for the other users. Hence the transmission power levels need to be smartly manipulated so as to achieve an adequate quality of service for as many users as possible and, thus, an efficient network utilization. Conventional power control algorithms adopt the Signal-to-Interference-plus-Noise Ratio (SINR) as controlled variable and neglect the important effects of the manipulated control variables (transmission powers) and of the retransmission mechanism on the queueing dynamics. In this paper, we pursue a different queue-based approach which takes into account the queueing dynamics and adopts the queue size as controlled variable. In particular, a novel queue-based power control algorithm with low on-line computational burden is proposed and its performance is evaluated both theoretically and via simulation experiments.

In modern wireless communication systems, power control plays a fundamental role for efficient resource utilization, in particular in the systems where the users share the same bandwidth at the same time. In such systems, in fact, many users transmit over the same radio channel using the same frequency band and time slots so that the signal of an individual user becomes interference for the other users. Hence the transmission power levels need to be smartly manipulated so as to achieve an adequate quality of service for as many users as possible and, thus, an efficient network utilization. Conventional power control algorithms adopt the Signal-to-Interference-plus-Noise Ratio (SINR) as controlled variable and neglect the important effects of the manipulated control variables (transmission powers) and of the retransmission mechanism on the queueing dynamics. In this paper, we pursue a different queue-based approach which takes into account the queuing dynamics and adopts the queue size as controlled variable. In particular, a novel queue-based power control algorithm with low on-line computational burden is proposed and its performance is evaluated both theoretically and via simulation experiments.

Wireless networks that support client mobility have to face the challenge of providing a secure, performant handoff between different access points. IEEE 802.1X [1] model provides a secure mechanism used by many standard protocols to securely generate keying material between two peer hosts when one of the two is accessing the network for first time, but that is hardly usable for reauthentication during handoff procedures without loss of performance. This paper deals with the proposal of a novel scheme to transport authentication credentials during handoff that uses a two-way only exchange with the backend authentication server maintaining the security of the system. As a high-level method it can be applied to different types of network, such as IEEE 802.11i [2] infrastructure or ad-hoc mode networks in a mesh environment.

The paper presents a novel approach for dynamic bandwidth allocation (DBA) in GEO satellite networks based on adaptive predictive control. In the proposed DBA scheme each satellite gateway (SG) uses an adaptive predictor to forecast the future input traffic flow along with a predictive bandwidth controller to generate a bandwidth request to the network control center (NCC) according to a receding-horizon policy, via solution of an optimal control problem. A multi-service traffic scenario is considered with a careful eye to guarantee differentiated quality of service requirements. Simulation experiments demonstrate that the DBA technique proposed in this work outperforms fixed allocation as well as existing DBA methods.

In modern satellite communication systems, the quality of service (QoS) management has became a crucial topic due to the increasing interest in multimedia traffic. The actual trends consider the satellite networks as an integrated part of the terrestrial data networks. In IP networks, the differentiated service (DiffServ) approach seems to be the best that satisfies the QoS constraints, due to its end-to-end philosophy. Actual trend considers the satellite on-board switching capabilities for managing multibeam inputs and outputs. In particular this paper deals with the proposal of a new cellular neural network (CNN) for the on-board switching problem to reduce the computational complexity; several traffic classes, according to the DiffServ approach, have been considered and the switch takes into account their priority, queue length and time spent inside queues. Numerical results have shown that the performance is similar to the optimal switching solution of the flexible cellular neural network. Simulation results have been driven with a memoryless distribution and heavy-tailed distribution for several input buffer size and switch dimension.

This paper deals with a modified version of the packet reservation multiple-access (PRMA) protocol suitable for integration of real-time (voice) and best effort (data) traffic in low Earth orbit (LEO) satellite communication systems. The proposed scheme differs from previous alternatives on the method adopted to handle access requests for voice and data terminals, and to transmit data messages. An analytical approach is proposed and validated in the case of voice and classical (i.e., geometric distributed) data traffic in order to derive system performance in terms of mean data message delay and voice packet dropping probability. However, in order to better highlight the advantages of the proposed approach typical interactive and background traffics types have been also considered. Performance comparisons with previous proposed PRMA protocols for voice and data transmission in LEO satellite communication systems are also shown in order to highlight the better behavior of the proposed scheme. Finally, a brief discussion concerning the extension of the proposed S-PRMA protocol to the case of different satellite communication systems is also provided.

This paper deals with the application of hybrid automatic repeat request (H-ARQ) techniques to reliable data communications in wireless 3G networks, whose typical applications have to match accurate quality of service (QoS) requirements. A common approach to guarantee such services enhances the H-ARQ features by exploiting turbo codes error correction capabilities. This paper, following the previous approach, investigates the further benefits achievable by developing a strategy that establishes a connection between packet retransmissions and decoding results. Two kinds of these techniques, belonging to soft recombining schemes, are proposed and applied, respectively, to consecutive received packet replicas, or to decoding algorithm outputs, in both cases, without remarkable hardware complexity increase. By means of analytical derivations and simulations, focused on a typical universal mobile telecommunication system (UMTS) environment, a noticeable bit error rate (BER) and, then, frame error rate (FER) improvements have been shown. For the proposed schemes, whenever communications suffer from low signal to noise ratio (SNR) values, significant link throughput increase is also pointed out. As a consequence, these techniques can assure a lower packet delivery delay, besides avoiding transmitted power wasting, if compared with protocols commonly used in wired networks.

This paper deals with the application of hybrid automatic repeat request (H-ARQ) techniques to reliable data communications in wireless 3G networks. Basically, retransmission of coded data is endowed with soft combining schemes applied, respectively, to packet replicas, or to decoding algorithm outputs. By means of analytical derivations and simulations on UMTS environment, a noticeable bit error rate (BER) and, then, frame error rate (FER) improvements have been shown. A significant link throughput increase is also pointed out with a consequent reduced packet delivery delay and power wasting.