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[null,"1.","Record Nr.",null,"UNISALENTO991002149629707536"]
[null,null,"Autore",null,"Pons y Umbert, Adolfo"]
[null,null,"Titolo",null,"Organizacion y funcionamiento de las Cortes segun las constituciones espanolas / Adolfo Pons y Umbert ; [Presentacion del autor y su obra de Claro J. Fernandez-Carnicero Gonzalez]"]
[null,null,"Pubbl/distr/stampa",null,"Madrid : Congreso de los diputados, 1992"]
[null,null,"ISBN",null,"8479430346"]
[null,null,"Descrizione fisica",null,"xvii, lxxxiv, 773 p ; 23 cm."]
[null,null,"Collana",null,"Textos parlamentarios clasicos ; 4"]
[null,null,"Classificazione",null,"C-XIV/D"]
[null,null,"Soggetti",null,"Spagna - Storia Costituzionale"]
[null,null,"Lingua di pubblicazione",null,"Spagnolo"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9911019242903321"]
[null,null,"Autore",null,"Sheluhin O. I (Oleg Ivanovich)"]
[null,null,"Titolo",null,"Self-similar processes in telecommunications / / Oleg I. Sheluhin, Sergey M. Smolskiy, Andrey V. Osin"]
[null,null,"Pubbl/distr/stampa",null,"Chichester, England ; ; Hoboken, NJ, : Wiley, c2007"]
[null,null,"ISBN",null,"9786612346156"]
[{"$nulls":4},"9781282346154"]
[{"$nulls":4},"1282346156"]
[{"$nulls":4},"9780470062098"]
[{"$nulls":4},"0470062096"]
[{"$nulls":4},"9780470062104"]
[{"$nulls":4},"047006210X"]
[null,null,"Descrizione fisica",null,"1 online resource (336 p.)"]
[null,null,"Disciplina",null,"621.382"]
[{"$nulls":4},"621.382150151922"]
[null,null,"Soggetti",null,"Telecommunication systems - Mathematical models"]
[{"$nulls":4},"Internetworking (Telecommunication)"]
[{"$nulls":4},"Self-similar processes"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Foreword -- About the authors -- Acknowledgements -- 1 Principal Concepts of Fractal Theory and Self-Similar Processes -- 1.1 Fractals and Multifractals -- 1.1.1 Fractal Dimension of a Set -- 1.1.2 Multifractals -- 1.1.3 Fractal Dimension D0 and Informational Dimension D1 -- 1.1.4 Legendre Transform -- 1.2 Self-Similar Processes -- 1.2.1 Definitions and Properties of Self-Similar Processes -- 1.2.2 Multifractal Processes -- 1.2.3 Long-Range and Short-Range Dependence -- 1.2.4 Slowly Decaying Variance -- 1.3 'Heavy Tails' -- 1.3.1 Distribution with 'Heavy Tails' (DHT) -- 1.3.2 'Heavy Tails' Estimation -- 1.4 Hurst Exponent Estimation -- 1.4.1 Time Domain Methods of Hurst Exponent Estimation -- 1.4.2 Frequency Domain Methods of Hurst Exponent -- Estimation -- 1.5 Hurst Exponent Estimation Problems -- 1.5.1 Estimation Problems -- 1.5.2 Nonstationarity Problems -- 1.5.3 Computational Problems -- 1.6 Self-Similarity Origins in Telecommunication Traffic -- 1.6.1 User's Behaviour -- 1.6.2 Data Generation Data Structure and Its Search -- "]
[{"$nulls":4},"1.6.3 Traffic Aggregation -- 1.6.4 Means of Network Control -- 1.6.5 Control Mechanisms based on Feedback -- 1.6.6 Network Development -- References -- 2 Simulation Methods for Fractal Processes -- 2.1 Fractional Brownian Motion -- 2.1.1 RMD Algorithm for FBM Generation -- 2.1.2 SRA Algorithm for FBM Generation -- 2.2 Fractional Gaussian Noise -- 2.2.1 FFT Algorithm for FGN Synthesis -- 2.2.2 Advantages and Shortcomings of FBM/FGN Models -- in Network Applications -- 2.3 Regression Models of Traffic -- 2.3.1 Linear Autoregressive (AR) Processes -- 2.3.2 Processes of Moving Average (MA) -- 2.3.3 Autoregressive Models of Moving Average, ARMA#p; q -- 2.3.4 Fractional Autoregressive Integrated Moving Average -- (FARIMA) Process -- 2.3.5 Parametric Estimation Methods -- 2.3.6 FARIMA#p,d,q Process Synthesis -- 2.4 Fractal Point Process -- 2.4.1 Statistical Characteristics of the Point Process -- 2.4.2 Fractal Structure of FPP -- 2.4.3 Methods of FPP Formation."]
[{"$nulls":4},"2.5 Fractional Levy Motion and its Application to Network -- Traffic Modelling -- 2.5.1 Fractional Levy Motion and Its Properties -- 2.5.2 Algorithm of Fractional Levy Motion Modelling -- 2.5.3 Fractal Traffic Formation Based on FLM -- 2.6 Models of Multifractal Network Traffic -- 2.6.1 Multiplicative Cascades -- 2.6.2 Modified Estimation Method of Multifractal Functions -- 2.6.3 Generation of Traffic the Multifractal Model -- 2.7 LRD Traffic Modelling with the Help of Wavelets -- 2.8 M/G/1Model -- 2.8.1 M/G/1Model and Pareto Distribution -- 2.8.2 M/G/1Model and Log-Normal Distribution -- References -- 3 Self-Similarity of Real Time Traffic -- 3.1 Self-Similarity of Real Time Traffic Preliminaries -- 3.2 Statistical Characteristics of Telecommunication Real Time Traffic -- 3.2.1 Measurement Organization -- 3.2.2 Pattern of TN Traffic -- 3.3 Voice Traffic Characteristics -- 3.3.1 Voice Traffic Characteristics at the Call Layer -- 3.3.2 Voice Traffic Characteristics at the Packet Layer -- 3.4 Multifractal Analysis of Voice Traffic -- 3.4.1 Basics -- 3.4.2 Algorithm for the Partition Function Sm#q Calculation -- 3.4.3 Multifractal Properties of Multiplexed Voice Traffic -- 3.4.4 Multifractal Properties of Two-Component Voice Traffic -- 3.5 Mathematical Models of VoIP Traffic -- 3.5.1 Problem Statement -- 3.5.2 Voice Traffic Models at the Call Layer -- 3.5.3 Estimation of Semi-Markovian Model Parameters and the Modelling -- Results of the Voice Traffic at the Call Layer -- 3.5.4 Mathematical Models of Voice Traffic at the Packets Layer -- 3.6 Simulation of the Voice Traffic -- 3.6.1 Simulation Structure -- 3.6.2 Parameters Choice of Pareto Distributions for Voice -- Traffic Source in ns2 -- 3.6.3 Results of Separate Sources Modelling -- 3.6.4 Results of Traffic Multiplexing for the Separate -- ON/OFF Sources -- 3.7 Long-Range Dependence for the VBR-Video -- 3.7.1 Distinguished Characteristics of Video Traffic -- 3.7.2 Video Conferences -- 3.7.3 Video Broadcasting -- 3.7.4 MPEG Video Traffic."]
[{"$nulls":4},"3.7.5 Nonstationarity of VBR Video Traffic -- 3.8 Self-Similarity Analysis of Video Traffic -- 3.8.1 Video Broadcasting Wavelet Analysis -- 3.8.2 Numerical Results -- 3.8.3 Multifractal Analysis -- 3.9 Models and Modelling of Video Sequences -- 3.9.1 Nonstationarity Types for VBR Video Traffic -- 3.9.2 Model of the Video Traffic Scene Changing Based on the -- Shifting Level Process -- 3.9.3 Video Traffic Models in the Limits of the Separate Scene -- 3.9.4 Fractal Autoregressive Models of p-Order -- 3.9.5 MPEG Data Modelling Using I, P and B Frames Statistics -- 3.9.6 ON/OFF Model of the Video Sequences -- 3.9.7 Self-Similar Norros Model -- 3.9.8 Hurst Exponent Dependence on N -- References -- 4 Self-Similarity of Telecommunication Networks Traffic -- 4.1 Problem Statement -- 4.2 Self-Similarity and 'Heavy Tails' in Lan Traffic -- 4.2.1 Experimental Investigations of Ethernet Traffic Self-"]
[{"$nulls":4},"Similar -- Structure -- 4.2.2 Estimation of Testing Results -- 4.3 Self-Similarity of WAN Traffic -- 4.3.1 WAN Traffic at the Application Level -- 4.3.2 Some Limiting Results for Aggregated WAN Traffic -- 4.3.3 The Statistical Analysis of WAN Traffic at the -- Application Level -- 4.3.4 Multifractal Analysis of WAN Traffic -- 4.4 Self-Similarity of Internet Traffic -- 4.4.1 Results of Experimental Studies -- 4.4.2 Stationarity Analysis of IP Traffic -- 4.4.3 Nonstationarity of Internet Traffic -- 4.4.4 Scaling Analysis -- 4.5 Multilevel ON/OFF Model of Internet Traffic -- 4.5.1 Problem Statement -- 4.5.2 Estimation of Parameters and Model Parameterization -- 4.5.3 Parallel Buffer Structure for Active Queue Control -- References -- 5 Queuing and Performance Evaluation of Telecommunication -- Networks under Traffic Self-Similarity Conditions -- 5.1 Traffic Fractality Influence Estimate on Telecommunication -- Networks Queuing -- 5.1.1 Monofractal Traffic -- 5.1.2 Communication System Model and the Packet Loss Probability -- Estimate for the Asymptotic Self-Similar Traffic Described by."]
[{"$nulls":4},"Pareto Distribution -- 5.1.3 Queuing Model with Fractal Levy Motion -- 5.1.4 Estimate of the Effect of Traffic Multifractality Effect on Queuing -- 5.2 Estimate of Voice Traffic Self-Similarity Effects on the iP Networks -- Input Parameter Optimization -- 5.2.1 Problem Statement -- 5.2.2 Simulation Structure -- 5.2.3 Estimate of the Traffic Self-Similarity Influence on QoS -- 5.2.4 TN input Parameter Optimization for Given QoS Characteristics -- 5.2.5 Conclusions -- 5.3 Telecomminication Network Parameters Optimization Using the Tikhonov -- Regularization Approach -- 5.3.1 Problem Statement -- 5.3.2 Telecommunication Network Parameter Optimization on the Basis of -- the Minimization of the Discrepancy Functional of QoS Parameters -- 5.3.3 Optimization Results -- 5.3.4 TN Parameter Optimization on the Basis of Tikhonov -- Functional Minimization -- 5.3.5 Regularization Results -- 5.3.6 Conclusions -- 5.4 Estimation of the Voice Traffic Self-Similarity Influence on QoS -- with Frame Relay Networks -- 5.4.1 Pocket Delay at Transmission through the Frame Relay Network -- 5.4.2 Frame Relay Router Modelling -- 5.4.3 Simulation Results -- 5.5 Bandwidth Prediction in Telecommunication Networks -- 5.6 Congestion Control of Self-Similar Traffic -- 5.6.1 Unimodal Ratio Loading/Productivity -- 5.6.2 Selecting Aggressiveness Control (SAC) Scheme -- References -- Appendix A List of Symbols -- Appendix B List of Acronyms -- Index."]
[null,null,null,"Sommario/riassunto","For the first time the problems of voice services self-similarity are discussed systematically and in detail with specific examples and illustrations. 'Self-Similar Processes in Telecommunications' considers the self-similar (fractal and multifractal) models of telecommunication traffic and efficiency based on the assumption that its traffic has fractal or multifractal properties (is self-similar). The theoretical aspects of the most well-known traffic models demonstrating self-similar properties are discussed in detail and the comparative analysis of the different models' efficiency for self-similar traffic is presented. This book demonstrates how to use self-similar processes for designing new telecommunications systems and optimizing existing networks so as to achieve maximum efficiency and serviceability. The approach is rooted in theory, describing the algorithms (the logical arithmetical or computational procedures that define how a task is performed) for modeling these self-similar processes. However, the language and ideas are essentially accessible for those who have a general knowledge of the subject area and the advice is highly practical: all models, problems and solutions are illustrated throughout using numerous real-world examples. Adopts a detailed, theoretical, yet broad-based "]
[{"$nulls":4},"and practical mathematical approach for designing and operating numerous types of telecommunications systems and networks so as to achieve maximum efficiency . Places the subject in context, describing the current algorithms that make up the fractal or self-similar processes while pointing to the future development of the technology . Offers a comparative analysis of the different types of self-similar process usage within the context of local area networks, wide area networks and in the modeling of video traffic and mobile communications networks . Describes how mathematical models are used as a basis for building numerous types of network, including voice, audio, data, video, multimedia services and IP (Internet Protocol) telephony The book will appeal to the wide range of specialists dealing with the design and exploitation of telecommunication systems. It will be useful for the post-graduate students, lecturers and researchers connected with communication networks disciplines."]
[null,"3.","Record Nr.",null,"UNINA9911007172303321"]
[null,null,"Autore",null,"Imran Muhammad Ali"]
[null,null,"Titolo",null,"The Role of 6G and Beyond on the Road to Net-Zero Carbon"]
[null,null,"Pubbl/distr/stampa",null,"Stevenage : , : Institution of Engineering & Technology, , 2023"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"1-83724-445-6"]
[{"$nulls":4},"1-5231-6310-0"]
[{"$nulls":4},"1-83953-737-X"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (274 pages)"]
[null,null,"Collana",null,"Telecommunications Series"]
[null,null,"Disciplina",null,"363.738746"]
[null,null,"Soggetti",null,"6G mobile communication systems"]
[{"$nulls":4},"Sustainable development"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Title -- Copyright -- Contents -- About the editors -- Preface -- 1 The role of mobile communication in achieving net zero: the current status -- 1.1 Efforts from the industry -- 1.2 Main sectors, use cases -- 1.2.1 Transportation -- 1.2.2 Energy -- 1.2.3 Industry/manufacturing -- 1.2.4 Agritech/farming -- 1.3 ICT and mobile networks as actors of power consumption -- 1.4 Challenges and possible solutions in reaching Net Zero Emissions in Telco infrastructures -- 1.5 Conclusions -- References -- 2 6G radio hardware-contributing to the net‒zero target -- 2.1 Introduction -- 2.2 Cell-free massive MIMO -- 2.2.1 Energy efficiency in CF mMIMO -- 2.3 Reconfigurable intelligent surfaces -- 2.4 Reconfigurable intelligent edges -- 2.5 Wireless power harvesting -- 2.6 Manufacturing sustainable hardware for 6G and beyond -- 2.7 Conclusion -- References -- 3 The role of 6G and beyond for urban air mobility and utilising space systems for road to net-zero carbon -- 3.1 Introduction -- 3.1.1 Smart mobility in mobile networks -- 3.1.2 Airborne network evolution -- 3.2 Role of ISTN in the future 6G-based urban air mobility: vision and architecture -- 3.2.1 Airspace division and radio network planning -- 3.2.2 Envisaged 6G technologies for UAM -- 3.2.3 Uncharted frequency bands -- 3.2.4 Intelligent reflecting surfaces -- 3.2.5 Massive intelligence -- 3.2.6 Low Earth orbit satellite backhaul -- 3.2.7 Quantum computing -- 3.3 KPIs for enabling 6G AWN mobility -- 3.3.1 Retainability -- 3.3.2 Mobility -- 3.4 Challenges, threats, and "]
[{"$nulls":4},"opportunities -- 3.5 The role of UAVs in the future mobile networks and their unique characteristics -- 3.5.1 UAV characteristics -- 3.5.2 Applications and use cases of UAVs -- 3.6 Solutions for space systems utilising for reaching global net-zero target -- 3.7 Conclusions -- References."]
[{"$nulls":4},"4 Sustainable RF wireless power transfer and energy harvesting and their applications -- 4.1 RF power harvesting and conversion methods -- 4.1.1 Device-level considerations: rectifiers -- 4.1.2 Antenna topologies and simultaneous wireless information and power transfer -- 4.2 Sustainable wearable and biomedical applications and approaches -- 4.2.1 Materials and fabrication process -- 4.2.2 Safety consideration and practical deployment -- 4.3 Emerging systems and applications -- 4.4 Summary and conclusions -- References -- 5 Long distance power transmission -- 5.1 Introduction -- 5.2 UAV-assisted wireless networking -- 5.2.1 Brief state-of-the-art -- 5.3 Reconfigurable intelligent surfaces (RIS) -- 5.3.1 Brief state-of-the-art -- 5.4 RIS and UAV cooperation in wireless networking -- 5.4.1 Brief state-of-the-art -- 5.5 Satellite communications -- 5.5.1 Brief state-of-the-art -- 5.6 Role of machine learning as an enabler -- 5.7 Summary -- References -- 6 Energy-efficient architectures for 6G networks -- 6.1 Overview of 6G networks -- 6.1.1 6G and technical requirements -- 6.1.2 Candidate technologies -- 6.2 Artificial intelligence and edge computing for energy savings in 6G -- 6.3 Zero-energy devices and 6G networks -- 6.4 Climate change and societal transformations -- 6.5 6G and future smart power systems -- 6.5.1 Microgrids and distribution networks -- 6.5.2 Renewable energy integration -- 6.5.3 Improved grid resilience -- 6.6 Case study 1: 6G and demand response -- 6.7 Case study 2: power system frequency control with EV networks -- 6.8 Conclusions -- References -- 7 Energy-efficient UAV communication and deployment -- 7.1 Introduction -- 7.1.1 UAV deployment -- 7.1.2 UAV energy efficiency -- 7.1.3 UAV-assisted index modulation -- 7.1.4 Contributions -- 7.2 IM-UAV communication system -- 7.2.1 Review of the concept of IM."]
[{"$nulls":4},"7.2.2 Proposed IM-UAV system model -- 7.2.3 Channel model -- 7.2.4 UAV deployment for the IM-UAV communication system -- 7.2.5 Low-complexity detection -- 7.3 Simulation results -- 7.4 Conclusion -- References -- 8 Cooperative intelligent transport systems for net-zero -- 8.1 Overview of ITS worldwide -- 8.2 Construction and design of VANETs -- 8.2.1 V2I communications -- 8.2.2 V2V communications -- 8.2.3 An overview of VANET protocol stacks -- 8.3 Security and privacy objectives -- 8.3.1 Privacy requirements -- 8.3.2 Security requirements -- 8.4 Challenges and security concerns -- 8.5 Towards 6G-based V2X communication -- 8.5.1 Revolutionary technologies for 6G-V2X -- 8.5.2 Evolutionary technologies for 6G-V2X -- 8.6 Conclusions -- References -- 9 Intelligent reflective surfaces (IRSs) for green networks -- 9.1 Smart radio environment and IRS -- 9.2 Overview of IRS technology, its properties, and how it works -- 9.2.1 IRS structure and control mechanism -- 9.2.2 IRS passive beamforming -- 9.3 IRS applications -- 9.3.1 IRS-assisted B5G and 6G networks -- 9.3.2 IRS-enabled smart cities and IoT networks -- 9.3.3 IRS for wireless power transfer -- 9.3.4 IRS-assisted UAV networks -- 9.4 IRS vs. active solutions: an environmental point of view -- 9.4.1 Power efficiency -- 9.4.2 Sustainable infrastructure -- 9.5 Conclusion and future research directions -- References -- 10 Energy efficient optical receivers for next generation non-terrestrial communication networks -- 10.1 Introduction -- 10.1.1 Motivation behind using a detector array receiver in free-space optical communications -- 10.1.2 Detector arrays in free-space optics: a background literature review -- 10.1.3 "]
[{"$nulls":4},"Energy savings with a detector array receiver -- 10.1.4 Model assumptions -- 10.1.5 Organization of the chapter -- 10.2 Symbol detection performance of an array of detectors."]
[{"$nulls":4},"10.2.1 Combining schemes with an array of detectors -- 10.3 Angle-of-arrival tracking with an array of detectors -- 10.4 Joint symbol detection and tracking with a detector array receiver -- 10.5 A brief complexity analysis -- 10.6 Experimental results and comments -- 10.7 Conclusion -- References -- 11 The role of 6G in green energy generation -- 11.1 Introduction -- 11.2 Advantages of 6G technology for green energy generation -- 11.3 Edge computing and energy systems -- 11.4 6G edge computing and SGs -- 11.4.1 Self-healing in SGs -- 11.4.2 Forecasting in SGs -- 11.4.3 Wireless charging in SGs -- 11.5 6G supporting edge AI -- 11.6 6G and SGs challenges -- 11.7 6G supporting P2P trading -- 11.7.1 6G P2P in VPPs -- 11.8 6G and energy Internet -- 11.9 Conclusion -- References -- Conclusion -- Paving the way to a net-zero carbon future with 6G -- Index."]
[null,null,null,"Sommario/riassunto","This book focuses on the potential of 6G to further expedite the achievement of net-zero. The authors cover the latest research efforts made in utilising 6G technology to solve real societal problems and to thought provoke researchers and scientists in proposing innovative ideas on how 6G can help with the fight against climate change."]