Transceivers and Spectrum Usage Minimization in Few-Mode Optical Networks

Metro-Area networks are likely to create the right conditions for the deployment of few-mode transmission (FMT) due to limited metro distances and rapidly increasing metro traffic. To address the new network design problems arising with the adoption of FMT, integer linear programming (ILP) formulations have already been developed to optimally assign modulation formats, baud rates, and transmission modes to lightpaths, but these formulations lack scalability, especially when they incorporate accurate constraints to capture inter-modal coupling. In this paper, we propose a heuristic approach for the routing, modulation format, baud rate and spectrum allocation in FMT networks with arbitrary topology, accounting for inter-modal coupling and for distance-Adaptive reaches of few-mode (specifically, up to five modes) signals generated by either full multi-in multi-out (MIMO) or low-complexity MIMO transceivers and for two different switching scenarios (i.e., spatial full-joint and fractional-joint switching). In our illustrative numerical analysis, we first confirm the quasi-optimality of our heuristic by comparing it to the optimal ILP solutions, and then we use our heuristic to identify which switching scenario and FMT transceiver technology minimize spectrum occupation and transceiver costs, depending on the relative costs of transceiver equipment and dark fiber leasing

On Refining Design Patterns for Smart Contracts: A use case on water management

The need for a Blockchain Oriented Software Engineering (BOSE) has been recognized in several research papers. Design Patterns are considered among the main and compelling areas to be developed in BOSE. Anyway, design patterns need to be enhanced with some additional fields to better support the specific needs of Blockchain development. In this paper, we discuss the use of Solidity design patterns applied to a water management use case and we introduce specific fields in their description, aiming at offering to Blockchain developers more support in the critical decisions to build efficient decentralized applications

Big Energy Data Management for Smart Grids—Issues, Challenges and Recent Developments

Urban areas suffer from tremendous pressure to cope with increasing population in a city. A smart city is a technological solution that integrates engineering and information systems to assist in managing these scarce resources. A smart city comprises several intelligent services such as smart grids, smart education, smart transportation, smart buildings, smart waste management and so on. Among all these, smart grids are the nucleus of all the facilities because these provide sustainable electrical supply for other smart services to operate seamlessly. Smart grids integrate information and communication technologies (ICT) into traditional energy grids, thereby capturing massive amounts of data from several devices like smart meters, sensors, and other electrical infrastructuresSCADA. The data collected in smart grids are heterogeneous and require data analytic techniques to extract meaningful information to make informed decisions. We term this enormous amount of data as big energy data. This book chapter discusses progress in the field of big energy data by enlisting different studies that cover several data management aspects such as data collection, data preprocessing, data integration, data storage, data analytics, data visualisation and decision-making. We also discuss various challenges in data management and report recent progress in this field. Finally, we present open research areas in big data managementBig data management especially in relation to smart grids