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The growing popularity of cloud and multimedia services is dramatically increasing the traffic volume that each data center needs to handle. This is driving the demand for highly scalable, flexible, and energy-efficient networks inside data centers, in particular for the edge tier, which requires a large number of interconnects and consumes the dominant part of the overall power. Optical fiber communication is widely recognized as the highest energy- and cost-efficient technique to offer ultra-large capacity for telecommunication networks. It has also been considered as a promising transmission technology for future data center applications. Taking into account the characteristics of the traffic generated by the servers, such as locality, multicast, dynamicity, and burstiness, the emphasis of the research on data center networks has to be put on architectures that leverage optical transport to the greatest possible extent. However, no feasible solution based on optical switching is available so far for handling the data center traffic at the edge tier. Therefore, apart from conventional optical switching, we investigate a completely different paradigm, passive optical interconnects, and aim to explore the possibility for optical interconnects at the top of the rack. In this article, we present three major types of passive optical interconnects and carry out a performance assessment with respect to the ability to host data center traffic, scalability, optical power budget, complexity of the required interface, cost, and energy consumption. Our results have verified that the investigated passive optical interconnects can achieve a significant reduction of power consumption and maintain cost at a similar level compared to its electronic counterpart. Furthermore, several research directions on passive optical interconnects have been pointed out for future green data centers.

Quantum key distribution (QKD) systems have already reached a reasonable level of maturity. However, a smooth integration and a wide adoption of commercial QKD systems in metropolitan area networks has still remained challenging because of technical and economical obstacles. Mainly the need for dedicated fibers and the strong dependence of the secret key rate on both loss budget and background noise in the quantum channel hinder a practical, flexible and robust implementation of QKD in current and next-generation optical metro networks.

In the Internet of Things (IoT), a huge number of sensors, actuators and other equipment for data acquisition and processing will be interconnected by means of an omnipresent communication network able to efficiently support heterogeneous transmission technologies and applications. On the one hand, advanced optical communication systems, which already play a significant role in modern networks, are currently evolving to meet very high requirements of modern applications. On the other hand, there are already many ways to utilize optical components and effects for building precise, efficient, and reliable sensors. Thus, optical technologies have the potential to greatly help in realizing future smart infrastructures and systems. This paper gives an overview of currently available and emerging optical technologies for sensing and communication applications and reviews their possible application in the context of the IoT for realizing smart systems and infrastructures.

To address the urgent need for high-capacity, scalable and energy-efficient data center solutions, we propose a novel data center network architecture realized by combining broadcast-and-select approach with elastic channel spacing technology. We demonstrate that the proposed architecture is able to scale efficiently with the number of servers and offers lower energy consumption at a competitive cost compared to the existing solutions.

In recent years, human activity recognition (HAR) has gained importance in several domains such as surveillance, recognizing indoor and outdoor activities, and providing active and assisted living environments in smart homes and healthcare services. In all these scenarios, audio-, video- and image-based processing algorithms have been applied as well as systems using wearable sensors. This scoping review focuses on audio- and video-based activity recognition systems for healthcare applications. We provide a comprehensive overview of these systems and technologies and discuss their complexity, performance, robustness, stage of development, scalability as well as achievable privacy and security levels. Additionally, we present and discuss datasets that are designed for the evaluation of these activity recognition systems. Although a number of robust approaches have already been proposed, they still pose challenges when it comes to integrating them in larger systems or into clinical practice. We identify challenges for application of audio- and video-based HAR systems in real-word healthcare scenarios, draw recommendations and conclusions based on comparisons of existing approaches, and analyze future trends.