What comes after optical-bypass network? A study on optical-computing-enabled network

A new architectural paradigm, named, optical-computing-enabled network, is proposed as a potential evolution of the currently used optical-bypass framework. The main idea is to leverage the optical computing capabilities performed on transitional lightpaths at intermediate nodes and such proposal reverses the conventional wisdom in optical-bypass network, that is, separating in-transit lightpaths in avoidance of unwanted interference. In optical-computing-enabled network, the optical nodes are therefore upgraded from conventional functions of add-drop and cross-connect to include optical computing / processing capabilities. This is enabled by exploiting the superposition of in-transit lightpaths for computing purposes to achieve greater capacity efficiency. While traditional network design and planning algorithms have been well-developed for optical-bypass framework in which the routing and resource allocation is dedicated to each optical channel (lightpath), more complicated problems arise in optical-computing-enabled architecture as a consequence of intricate interaction between optical channels and hence resulting into the establishment of the so-called integrated / computed lightpaths. This necessitates for a different framework of network design and planning to maximize the impact of optical computing opportunities. In highlighting this critical point, a detailed case study exploiting the optical aggregation operation to re-design the optical core network is investigated in this paper. Numerical results obtained from extensive simulations on the COST239 network are presented to quantify the efficacy of optical-computing-enabled approach versus the conventional optical-bypass-enabled one.

K-Nearest Neighbors based Shock Advice Algorithm for Automated External Defibrillators

Shockable rhythms, namely ventricular fibrillation and ventricular tachycardia, are the main cause of sudden cardiac arrests, which can be detected quickly by the automated external defibrillator (AED) devices. In this paper, a simple but effective algorithm is proposed as the shock advice algorithm applied in AED. The proposed algorithm consists of K-nearest neighbor classifier and an optimal set of 36 features, which are extracted from original ECG and shockable, non-shockable signals using modified variational mode decomposition technique. Cross-validation procedure and sequential forward feature selection are carefully applied to select an optimal set from entire feature space. The performance results show that the MVMD is the key element for SCA detection performance, and the proposed algorithm is simpler while remaining relatively high detection performance compared to previous publications.

A pragmatic approach for designing transparent WDM optical networks with multi-objectives

In facing with the explosive Internet traffic growth, optical transport networks based on WDM technologies forming the core part of Internet infrastructure carrying multi-Tb/s has to be re-considered from both designing, planning, operation and management perspectives to attain greater efficiency. Thanks to the convergence of significant advances in optical transmission technologies, and photonic switching, transparent (all-optical) architecture has come into practice, paving the way for eliminating the over-utilization of costly optical-electrical-optical (O-E-O) interfaces and hence, yielding remarkable savings of cost and energy consumption compared to opaque architecture. Traditional designs for transparent optical networks based on single-objective optimization model aiming at optimizing solely a single performance metric appears to be insufficient to capture the nuances of practical designs while conventional multi-objective approach tends to reach (non-) optimal solutions. Different from existing works, we present a new framework for multi-objective WDM network designs capturing several goals on one hand and on the other hand, achieving optimal solutions. Moreover, our proposal exploits the characteristics of each constituent objectives to lay the foundation for setting up weight coefficient so that the order of optimization is guaranteed. Equally important, our proposal is pragmatic in the sense that the complexity of the optimization model remains the same as the single-objective model while the quality of solution has been greatly improved. We have extensively tested realistic optical core networks topologies, that is, COST239 and NSFNET, with various network traffic conditions and it turns out that our design brings about a saving of wavelength link usage up to roughly $28\%$ in the most favorable cases while $14\%$ is expected for the least favorable cases.

On Development of Efficient Data Acquisition Systems and Parameter Extraction Technique for DFB Lasers

Distributed Feedback Laser plays a key role as a light source component in optical fiber communication systems ranging from metro, long-haul to submarine one thanks to its competitive features of superior narrow spectral width and wavelength cohesion. Characterizing such lasers via obtaining their electrical and spectral data and extracting their internal parameters therefore remains a critical task in designing and troubleshooting optical fiber systems. This paper presents first an agile framework for a rapid collection of laser data via automatic measurement and second an efficient approach for extracting laser internal parameters.