Recent Advances and Future Trends in Nanophotonics

Nanophotonics has emerged as a multidisciplinary frontier of science and engineering. Due to its high potential to contribute to breakthroughs in many areas of technology, nanophotonics is capturing the interest of many researchers from different fields. This Special Issue of Applied Sciences on “Recent advances and future trends in nanophotonics” aims to give an overview on the latest developments in nanophotonics and its roles in different application domains. Topics of discussion include, but are not limited to, the exploration of new directions of nanophotonic science and technology that enable technological breakthroughs in high-impact areas mainly regarding diffraction elements, detection, imaging, spectroscopy, optical communications, and computing

Nonlinear Dynamics of Semiconductor Lasers and Their Applications

Semiconductor lasers are key components in many optical systems due to their advantages, including their small size, low cost, high efficiency, and low power consumption. It is well-known that semiconductor lasers under external perturbations, such as optical injection, optical feedback, or delayed coupling can exhibit a large variety of complex dynamical behaviors. Nowadays, cutting-edge engineering applications based on the complex dynamics of diode lasers are being conducted in areas, such as optical communications, optical signal processing, encoded communications, neuro-inspired ultra-fast optical computing devices, microwave signal generation, RADAR and LIDAR applications, biomedical imaging, and broadband spectroscopy. The prospects for these applications are even more exciting with the advent of photonic integrated circuits. This Special Issue focuses on theoretical and experimental advances in the nonlinear dynamics of semiconductor lasers subject to different types of external perturbations

Trustworthiness in Mobile Cyber Physical Systems

Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

Fog-enabled Edge Learning for Cognitive Content-Centric Networking in 5G

By caching content at network edges close to the users, the content-centric networking (CCN) has been considered to enforce efficient content retrieval and distribution in the fifth generation (5G) networks. Due to the volume, velocity, and variety of data generated by various 5G users, an urgent and strategic issue is how to elevate the cognitive ability of the CCN to realize context-awareness, timely response, and traffic offloading for 5G applications. In this article, we envision that the fundamental work of designing a cognitive CCN (C-CCN) for the upcoming 5G is exploiting the fog computing to associatively learn and control the states of edge devices (such as phones, vehicles, and base stations) and in-network resources (computing, networking, and caching). Moreover, we propose a fog-enabled edge learning (FEL) framework for C-CCN in 5G, which can aggregate the idle computing resources of the neighbouring edge devices into virtual fogs to afford the heavy delay-sensitive learning tasks. By leveraging artificial intelligence (AI) to jointly processing sensed environmental data, dealing with the massive content statistics, and enforcing the mobility control at network edges, the FEL makes it possible for mobile users to cognitively share their data over the C-CCN in 5G. To validate the feasibility of proposed framework, we design two FEL-advanced cognitive services for C-CCN in 5G: 1) personalized network acceleration, 2) enhanced mobility management. Simultaneously, we present the simulations to show the FEL's efficiency on serving for the mobile users' delay-sensitive content retrieval and distribution in 5G.Comment: Submitted to IEEE Communications Magzine, under review, Feb. 09, 201

Prolog to the section on wireless communications technology

The authors take a look at the existing 3G systems in service and investigate the capabilities of 4G, and while the theoretical throughput of these cellular systems is expected to be high, the future promises to offer more technological improvements and innovations.<br/