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Reconfigurable linear optical processors can be used to perform linear transformations and are instrumental in effectively computing matrix–vector multiplications required in each neural network layer. In this paper, we characterize and compare two thermally tuned photonic integrated processors realized in silicon-on-insulator and silicon nitride platforms suited for extracting feature maps in convolutional neural networks. The reduction in bit resolution when crossing the processor is mainly due to optical losses, in the range 2.3–3.3 for the silicon-on-insulator chip and in the range 1.3–2.4 for the silicon nitride chip. However, the lower extinction ratio of Mach–Zehnder elements in the latter platform limits their expressivity (i.e., the capacity to implement any transformation) to 75%, compared to 97% of the former. Finally, the silicon-on-insulator processor outperforms the silicon nitride one in terms of footprint and energy efficiency.

Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.

In recent years, the adoption of innovative technologies in maritime transport and logistics systems has become a key aspect towards their development and growth, especially due to the complex and heterogeneous nature of the maritime environment. On the other hand, Internet of Things (IoT) solutions are gaining importance in the shipping industry thanks to the huge number of distributed cameras and sensors in modern ships, cargoes and sea ports, which can be exploited to improve safety, costs and productivity. This paper presents an experimental evaluation of a maritime platform, which enables a wide range of 5G-based services in the context of logistics and maritime transportation. Its core is a Narrow Band (NB)-IoT framework used to run massive IoT services on top of a hybrid terrestrial–satellite network and feed a OneM2M platform with significant data on maritime transport to develop high-level and value-added logistic applications on top. Among the many different services that could be provided by the maritime platform, we focus on the cargo-ship container tracking use case through the Global Tracking System, which allows for continuous container monitoring all over the seas in a port-to-port service scenario. The results of the experimental tests illustrate the capacity of the platform in managing the high number of messages transmitted by the container tracking devices (i.e., more than 3000) and its efficiency in limiting the average maximum latency and packet loss below 5.5 s and 0.9%, respectively.

The spreading diffusion of wireless devices and the crowded coexistence of multimedia applications greedy of bandwidth and with strict requirements stress the service provisioning offered by wireless technologies. WiFi is a reference for wireless connectivity and it requires a continuous evolution of its mechanism in order to follow increasingly demanding service needs. In particular, despite the evolution of physical layer, some critical contexts, such as industrial networks, telemedicine, telerehabilitation, and virtual training, require further refined improvements in order to ensure the respect of strict real-time service requirements. In this paper an in-depth analysis of Dynamic TXOP HCCA (DTH) MAC enhanced centralized scheduler is illustrated and it is further refined introducing a new improvement, DTH with threshold. DTH and DTH with threshold can be integrated with preexisting centralized schedulers in order to improve their performances, without any overprovisioning that can negatively impact on the admission control feasibility test. Indeed, without modifying the centralized scheduler policy, they combine together the concepts of reclaiming transmission time and statistical estimation of the traffic profile in order to provide, at each polling, an instantaneous transmission time tailored to the variable traffic requirements, increasing, when necessary, the service data rate. These mechanisms can coexist with advanced physical layer-based solutions, providing the required service differentiation. Experimental results and theoretical analysis, based on elastic scheduler theory, show that they are effective especially in the case of Variable Bit Rate traffic streams in terms of transmission queues length, packets loss, delay, and throughput.

Here's an authoritative, cutting-edge resource that gives you a thorough understanding of CDMA transmission and detection. It offers practical guidance in designing interference-reducing multi-user receivers for mobile radio systems and multi-user adaptive modems for accessing satellite earth stations. The book provides in-depth descriptions of CDMA principles, and of linear and non-linear multi-user detection, and covers the fine details of the realization of a linear multi-user receiver. Extensively supported with over 300 equations and more than 95 illustrations, the book enables you to devise accurate system models of both a cellular TD-CDMA radio interface and an asynchronous satellite radio interface. It allows you to choose among different architectural solutions for both linear multi-user receivers to be operated in TD-CDMA radio systems and adaptive linear CDMA receivers in satellite asynchronous CDMA systems.

Beyond fifth-generation (B5G) networks aim to support high data rates, low-latency applications, and massive machine communications. Artificial Intelligence/Machine Learning (AI/ML) can help to improve B5G network performance and efficiency. However, dynamic service demands of B5G use cases cause AI/ML model performance degradation, resulting in Service Level Agreements (SLA) violations, over- or under-provisioning of resources, etc. Retraining is essential to address the performance degradation of the AI/ML models. Existing threshold and periodic retraining approaches have potential disadvantages, such as SLA violations and inefficient resource utilization for setting a threshold parameter in a dynamic environment. This paper proposes a novel approach that predicts when to retrain AI/ML models using Generative Artificial Intelligence. The proposed predictive approach is evaluated for a Quality of Service Prediction use case on the Open Radio Access Network (O-RAN) Software Community platform and compared to the predictive approach based on the classifier and a threshold approach. Also, a realtime dataset from the Colosseum testbed is considered to evaluate Network Slicing (NS) use case with the proposed predictive approach. The results show that the proposed predictive approach outperforms both the classifier-based predictive and threshold approaches.

Multi-band optical transmission promises to extend the lifetime of currently deployed networks. We propose a provisioning scheme tailored for multi-band systems. We show how it attains a considerable reduction of the blocking probability, despite GSNR penalties in C-band, achieving a fourfold increase in accommodated traffic.

We propose the use of blockchain for the ratification of QoT performance in multi-domain networks, where a transparent lightpath traverses several domains. End-to-end QoT is guaranteed by transferring \"OSNR blocks\" among domains' controllers. Experimental demonstration shows the feasibility of the method and its scalability.

Impressive data processing and storage capabilities have been reached through the continuous technological improvement in integrated circuits. Computing platforms of different types offer tremendous computing and storage capabilities, suitable for scientific and business applications. A notable example is given by supercomputers, the fastest computing platforms, used for running highly calculation-intensive applications in the field of physics, astronomy, mathematics, and life science. As computing platforms scale (that is., increase in the number of servers and in the computational capacity), the requisites of high throughput and low latency are becoming more difficult to achieve and ensure. The increase in the size of computing platforms also causes a dramatic increase in power consumption, which may seriously impair further scaling. This chapter explains how photonic technologies can help meet the two crucial challenges of interconnection networks for computing platforms, namely, the scalability and energy efficiency. It discusses State-of-the-art photonic technologies suitable for connecting and replacing the electronic switches.

BackgroundHip fractures (HF) are a major issue worldwide. We aimed at evaluating the practices in delivering care to patients with HF among several Italian Orthogeriatric centers.MethodsThe study took place from February 2016 to July 2018. Seven performance indicators (pre-surgical cognitive assessment, surgery performed ≤ 48 h from fracture, removal of urinary catheter/absence of delirium/start of physiotherapy on the first post-operative day, prescription of bone protection at discharge, and discharge toward rehabilitation) were collected.ResultsThe 14 participating hospitals totally recruited 3.017 patients. Patients were old (median age 86 years; Inter Quartile Range [IQR] 80–90), mostly females (77%). Nearly 55% of them were already impaired in mobility and about 10% were nursing home residents. Median time-to-surgery was 41 h (IQR 23–62). Models of care greatly varied among centers, only 49.3% of patients being co-managed by geriatricians and orthopedics. There was high variability across centers in four indicators (“pre-surgical cognitive assessment”, “bone protection prescription”, “use of urinary catheter” and “start of physiotherapy”), moderate in two indicators (“surgery performed ≤ 48 h from fracture” and “discharge toward rehabilitation” and low in one (“absence of delirium on day following surgery”). Comparison with international studies suggests very different ways of providing care to HF Italian patients.ConclusionsThe study results suggest high inter-center variability in the key-performance indicators, and different approaches in providing care to our HF patients in comparison to other countries. A National debate on the topic is required in Italy to harmonize practices of orthogeriatric care.