To support bursty traffic on the Internet (and especially WWW) efficiently, optical burst switching (OBS) is proposed as a way to streamline both protocols and hardware in building the future gener...

Optical burst switching (OBS) - a new paradigm for an optical Internet

The emerging software defined networking (SDN) paradigm separates the data plane from the control plane and centralizes network control in an SDN controller. Applications interact with controllers to implement network services, such as network transport with quality of service. SDN facilitates the virtualization of network functions so that multiple virtual networks can operate over a given installed physical network infrastructure. Due to the specific characteristics of optical (photonic) communication components and the high optical transmission capacities, SDN-based optical networking poses particular challenges, but holds also great potential. In this article, we comprehensively survey studies that examine the SDN paradigm in optical networks; in brief, we survey the area of software defined optical networks (SDONs). We mainly organize the SDON studies into studies focused on the infrastructure layer, the control layer, and the application layer. Moreover, we cover SDON studies focused on network virtualization, as well as SDON studies focused on the orchestration of multilayer and multidomain networking. Based on the survey, we identify open challenges for SDONs and outline future directions.

Software Defined Optical Networks (SDONs): A Comprehensive Survey

While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. The growing interest in applying unsupervised learning techniques in networking stems from their great success in other fields, such as computer vision, natural language processing, speech recognition, and optimal control (e.g., for developing autonomous self-driving cars). In addition, unsupervised learning can unconstrain us from the need for labeled data and manual handcrafted feature engineering, thereby facilitating flexible, general, and automated methods of machine learning. The focus of this survey paper is to provide an overview of applications of unsupervised learning in the domain of networking. We provide a comprehensive survey highlighting recent advancements in unsupervised learning techniques, and describe their applications in various learning tasks, in the context of networking. We also provide a discussion on future directions and open research issues, while identifying potential pitfalls. While a few survey papers focusing on applications of machine learning in networking have previously been published, a survey of similar scope and breadth is missing in the literature. Through this timely review, we aim to advance the current state of knowledge, by carefully synthesizing insights from previous survey papers, while providing contemporary coverage of the recent advances and innovations.

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Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges

This review covers photonic crystal cavities (PCCs) and their applications in optical sensors, with a particular focus on the structures of different PCCs. For each kind of optical sensor, the specific measurement principle, structure of PCC, and the corresponding sensing properties are all presented in detail. The summary of the reported works and the corresponding results demonstrate that it is possible to realize miniature and high-sensitive optical sensors due to the ultra-compact size, excellent resonant properties, and flexibility in structural design of PCCs. Finally, the key problems and new directions of PCCs for sensing applications are discussed.

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A review for optical sensors based on photonic crystal cavities

We have designed and fabricated a directed logic architecture consisting of two silicon microring resonators that can perform XOR and XNOR operations. The microring resonators are modulated through thermo-optic effect. Two electrical modulating signals applied to the microring resonators represent the two operands of the logical operation. The logical function is evaluated through the directed propagation of light in the device, and the result is represented by the output optical signal. Both XOR and XNOR operations at 20 kbits are demonstrated.

Demonstration of directed XOR/XNOR logic gates using two cascaded microring resonators

We propose ultra compact all-optical XOR, XNOR, NAND and OR gates based on photonic crystal multi-mode interference waveguides for binary-phase-shift-keyed signals. The logic gates have been simulated and analyzed by finite difference time domain method. The extinction ratio between the ON state and the OFF state for XOR, XNOR, NAND and OR gates are more than 28.6 dB, 28.6 dB, 25 dB and 26.6 dB in the whole C-band, respectively. The proposed structure can achieve logical function when the radius of all rods is fabricated with relaxed error tolerance within −10% to 30% from designed parameters. The device possesses ultra compact size with approximately 6.9 μm×6.7 μm. The proposed logic gates may potentially be used as key components in all-optical information networks for processing binary-phase-shift-keyed signals.

Design of ultra compact all-optical XOR, XNOR, NAND and OR gates using photonic crystal multi-mode interference waveguides

Sensitivities (S) and quality factors (Q) have been trade-offs in label-free optical resonator sensors, and optimal geometry that maximizes both factors is under active development. In this paper, we demonstrate that the nanoslotted parallel multibeam cavity possesses unexplored high S and high Q. We achieve S>800  nm/RIU (refractive index unit) and Q>107 in liquid at telecom wavelength range when absorption is neglected. To the best of our knowledge, this is the first geometry that features both high S and Q factors, and thus is potentially an ideal platform for refractive index-based biochemical sensing.

Design of simultaneous high-Q and high-sensitivity photonic crystal refractive index sensors

In this paper, we demonstrate a photonic crystal (PhC) stress sensor with high sensitivity in two orthogonal directions. The stress sensor consists of an aslant lattice-shifted resonant cavity shoulder-coupled to two terminated Γ – K waveguides. The linear relationship between the shifts of resonant wavelength and applied stress in double directions is calculated with the finite element method (FEM) and finite difference time domain (FDTD) simulations. With the simulations, we demonstrate that the stress sensitivity of 7.5 nm/μN in horizontal direction and 10 nm/μN in vertical direction is achieved, respectively, and a stress detection limit is approximately of 58 nN and 44 nN in horizontal and vertical direction for this device, respectively.

Photonic crystal stress sensor with high sensitivity in double directions based on shoulder-coupled aslant nanocavity

High-bandwidth and low-loss photonic crystal power-splitter with parallel output based on the integration of Y-junction and waveguide bends

A novel nanoscale torsion-free photonic crystal pressure sensor is demonstrated and its performances are theoretically investigated. The proposed sensor device consists of PhC waveguide and side-coupled piston-type microcacity. By using finite-element method (FEM) and three dimensional finite difference time domain technologies (3D-FDTD), the dependence of optical properties of resonant mode on the applied strain is systematically studied. Linear relationships between the applied strain and the shift in the resonant wavelength of the cavity are obtained. The pressure sensitivity as high as 0.50 nm/nN is observed. The minimum detectable pressure variation is estimated to be as small as 0.68 nN. Compared to ring-resonator based pressure sensor achieved an equivalent sensitivity, the sensor size presented in this work is reduced by three orders of magnitude. In addition, a flexible design of pressure sensor array is demonstrated in the end.

Yuefeng Ji

Papers

Design of ultra compact all-optical XOR, XNOR, NAND and OR gates using photonic crystal multi-mode interference waveguides

Design of simultaneous high-Q and high-sensitivity photonic crystal refractive index sensors

Photonic crystal stress sensor with high sensitivity in double directions based on shoulder-coupled aslant nanocavity

High-bandwidth and low-loss photonic crystal power-splitter with parallel output based on the integration of Y-junction and waveguide bends

Nanoscale torsion-free photonic crystal pressure sensor with ultra-high sensitivity based on side-coupled piston-type microcavity