The explosive growth of mobile data traffic demands scalable, resilient, and energy-efficient solutions for content dissemination, particularly at the network edge. In this context, 5G networks can rely on Outband Device-to-Device (O-D2D) communications, using technologies such as Wi-Fi Direct, to offload infrastructure, enhance coverage at the cell edge, and enable proximity-based services. However, O-D2D communications face critical challenges related to peer discovery, reliable data retrieval over lossy wireless links, and energy efficiency constraints. In this paper, we propose a novel framework that integrates Named Data Networking (NDN) and Chinese Remainder Theorem (CRT)-based fragmentation to support autonomous O-D2D content delivery. By leveraging name-based forwarding and in-network caching, NDN facilitates distributed content retrieval, making it inherently suited for dynamic and infrastructure-less D2D environments. CRT-based fragmentation, on the other hand, enhances reliability and energy efficiency by allowing data reconstruction from partial fragment sets, mitigating the effects of packet losses typical of wireless links. We implement the proposed architecture in ndnSIM v2.9, extending the NDN forwarding plane to support CRT-based multi-source data retrieval. Simulation results demonstrate that our solution significantly improves content delivery and energy efficiency compared to existing NDN retrieval schemes, particularly under lossy wireless conditions.

With the growing integration of biometric recognition systems into high-security and large-scale deployment scenarios, it is becoming increasingly important to ensure their robustness under realistic operational constraints. This implies designing solutions able to withstand potential adversarial threats that could affect their integrity and accountability, and also taking into account requirements of real-world operating systems such as limited availability of bandwidth and memory for data transmission and storage. Hence, the proposed study deals with presentation attack detection (PAD) for iris recognition, evaluating the effectiveness of Transformer-based frameworks at detecting spoofing attacks relying on fabricated or artificial biometric evidences. More specifically, we focus on the effects of image compression on the quality of iris images and on the resulting PAD performance, considering both traditional techniques such as JPEG as well as next-generation learning-based image codecs such as JPEG AI. We then examine the feasibility of mitigating compression-induced performance degradation by fine-tuning the adopted models on compressed images, achieving improvements in terms of half total error rate between 5% and 10% for images compressed at the worst JPEG and JPEG AI qualities. We also evaluate the generalizability of the developed solutions by testing them on learning-based codecs not considered during training, to check whether similar PAD-relevant artifacts are introduced by different compressions. Furthermore, we investigate the redundancy within the embeddings generated by the employed detectors, and demonstrated it is possible to significantly compress them while preserving the achievable PAD performance. Overall, the study provides a systematic analysis of iris PAD under compression constraints, offering insights into model adaptation, cross-codec robustness, and representation efficiency in scenarios where visual data coding plays a central role.

In industrial wireless sensors networks (IWSNs) deployments, data management and processing tasks are often delegated to centralized computing facilities. Albeit providing an abundance of resources, these solutions impose several drawbacks, stemming from the higher latency they may introduce, as well as from security/privacy issues. To deal with these shortcomings, in this article, we propose an architecture designed for industrial monitoring duties, based on the Fog computing paradigm. In particular, we devised a Fog layer to host a data aggregation algorithm based on singular value decomposition (SVD). Considering a real-world case study about a distributed monitoring system for industrial motors, the benefits of the proposed solution in terms of network performances, i.e., latency and packet delivery ratio, are analyzed using the OMNET++ simulator. Besides, the system implements a set of security mechanisms at different levels (i.e., IWSN, Fog, and Cloud). In particular, we propose a new lightweight and energy-efficient ciphering algorithm for resource-constrained industrial motes. According to our experiments, the new algorithm reduces energy consumption by a factor of three compared to Advanced Encryption Standard-128.

Recently, Industrial Wireless Sensor Networks (IWSN) have gained a lot of interest from both research and industry communities as an evolution of WSN specifically tailored for Industry 4.0 applications and their requirements. Thanks to the set of benefits IWSN technology introduces, it is considered to be a sustainable solution for industrial system monitoring. Yet, this approach has several drawbacks stemming from the limited resources (i.e., compute and storage) available on-board network devices. Although Cloud-based WSN data management solutions are widely adopted, issues related to this approach persist (e.g., high latency, bandwidth consumption, storage costs). This paper introduces an innovative platform enhancing IWSN architectures by adding a processing layer at the network edge: an approach that follows the Fog Computing paradigm. Remote management and programmability of the Fog layer are only some of the most challenging requirements. We show how our approach is suitable for industrial scenarios by applying it to a representative use case, i.e., the monitoring of asynchronous electric motors.

Abstract Support of Voice over Internet Protocol (VoIP) services in wireless mesh networks requires implementation of efficient policies to support low‐delay data delivery. Multipath routing is typically supported in wireless mesh networks at the network level to provide high fault tolerance and load balancing because links in the proximity of the wireless mesh gateways can be very stressed and overloaded, thus causing scarce performance. As a consequence of using multipath solutions, lower delay and higher throughput can be supported also when a given path is broken because of mobility or bad channel conditions, and alternative routes are available. This can be a relevant improvement especially when assuming that real‐time traffic, such as VoIP, travels into the network. In this paper, we address the problem of Quality of Service (QoS) support in wireless mesh networks and propose a multipath routing strategy that exploits the Mean Opinion Score (MOS) metric to select the most suitable paths for supporting VoIP applications and performing adaptive load balancing among the available paths to equalize network traffic. Performance results assess the effectiveness of the proposed approach when compared with other existing methodologies. Copyright © 2015 John Wiley & Sons, Ltd.

In recent years, Storage as a Service Cloud gained popularity among both companies and private users. However, security and interoperability issues still have to be adequately faced and solved. In this work, we propose a simple, secure, and privacy-preserving architecture for inter-Cloud data sharing. The proposed solution relies on open standards for both sharing and communication mechanisms, thus ensuring durability, robustness, and compatibility of the approach in the current Internet.

This paper deals with a novel forwarding scheme for wireless sensor networks aimed at combining low computational complexity and high performance in terms of energy efficiency and reliability. The proposed approach relies on a packet-splitting algorithm based on the Chinese Remainder Theorem (CRT) and is characterized by a simple modular division between integers. An analytical model for estimating the energy efficiency of the scheme is presented, and several practical issues such as the effect of unreliable channels, topology changes, and MAC overhead are discussed. The results obtained show that the proposed algorithm outperforms traditional approaches in terms of power saving, simplicity, and fair distribution of energy consumption among all nodes in the network.

In this paper we propose a routing approach aimed at enhancing the quality of Voice-over-IP (VoIP) transmissions in multipath Wireless Mesh Networks. The proposed approach executes a path switching based on the estimation of the Mean Opinion Score (MOS) for each available path of the mesh network. Performance results conducted through simulations show that the proposed approach, when compared to a random choice of the available paths, is highly effective in improving the performance of the VoIP calls in both static and dynamic scenarios.

The main aim of this paper is to generalize and improve a recently proposed forwarding technique based on the Chinese Remainder Theorem (CRT). The proposed technique outperforms more traditional approaches in terms of both energy efficiency and fair distribution of energy consumption, and requires very few changes to the commonly used forwarding schemes for its implementation. In particular, in this paper it is shown how to apply the CRT-based forwarding method on a realistic wireless network where unreliable erasure channels are considered together with topological changes. Furthermore, an analytical model for the novel forwarding technique has been derived and the trade-off between reliability and energy saving has been investigated.

In this paper we discuss the use of the Chinese Remainder Theorem (CRT) for a novel forwarding scheme in wireless sensor networks. The proposed approach is characterized by a computationally simple packet splitting procedure able to reduce the energy needed for transmission and increase the network lifetime accordingly. Simulation results show that the proposed algorithm outperforms more traditional approaches in terms of both energy efficiency and fair distribution of energy consumption among all nodes in the network.

This paper presents a theoretical result in the context of realizing high-speed hardware for parallel CRC checksums. Starting from the serial implementation widely reported in the literature, we have identified a recursive formula from which our parallel implementation is derived. In comparison with previous works, the new scheme is faster and more compact and is independent of the technology used in its realization. In our solution, the number of bits processed in parallel can be different from the degree of the polynomial generator. Last, we have also developed high-level parametric codes that are capable of generating the circuits autonomously when only the polynomial is given.