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Multilayer networks is a rising topic in Network Science which characterizes the structure and the function of complex systems formed by several interacting networks. Multilayer networks research has been propelled forward by the wide realm of applications in social, biological and infrastructure networks and the large availability of network data, as well as by the significance of recent results, which have produced important advances in this rapidly growing field. This book presents a comprehensive account of this emerging field. It provides a theoretical introduction to the main results of multilayer network science.
This book provides the basis of a formal language and explores its possibilities in the characterization of multiplex networks. Armed with the formalism developed, the authors define structural metrics for multiplex networks. A methodology to generalize monoplex structural metrics to multiplex networks is also presented so that the reader will be able to generalize other metrics of interest in a systematic way. Therefore, this book will serve as a guide for the theoretical development of new multiplex metrics. Furthermore, this Brief describes the spectral properties of these networks in relation to concepts from algebraic graph theory and the theory of matrix polynomials. The text is rounded off by analyzing the different structural transitions present in multiplex systems as well as by a brief overview of some representative dynamical processes. Multiplex Networks will appeal to students, researchers, and professionals within the fields of network science, graph theory, and data science.
This book unifies and consolidates methods for analyzing multilayer networks arising from the social and physical sciences and computing.
The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization. In this Synthesis Lecture, we provide an overview and structured analysis of contemporary multilayer network visualization. This is not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those solving problems within application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer network visualization, as well as tools, tasks, and analytic techniques from within application domains. We also identify the research opportunities and examine outstanding challenges for multilayer network visualization along with potential solutions and future research directions for addressing them.
Network thinking and network analysis are rapidly expanding features of ecological research. Network analysis of ecological systems include representations and modelling of the interactions in an ecosystem, in which species or factors are joined by pairwise connections. This book provides an overview of ecological network analysis including generating processes, the relationship between structure and dynamic function, and statistics and models for these networks. Starting with a general introduction to the composition of networks and their characteristics, it includes details on such topics as measures of network complexity, applications of spectral graph theory, how best to include indirect species interactions, and multilayer, multiplex and multilevel networks. Graduate students and researchers who want to develop and understand ecological networks in their research will find this volume inspiring and helpful. Detailed guidance to those already working in network ecology but looking for advice is also included.
The scientific study of networks - computer, social, and biological - has received an enormous amount of interest in recent years. However, the network approach has been applied to the field of animal behaviour relatively late compared to many other biological disciplines. Understanding social network structure is of great importance for biologists since the structural characteristics of any network will affect its constituent members and influence a range of diverse behaviours. These include finding and choosing a sexual partner, developing and maintaining cooperative relationships, and engaging in foraging and anti-predator behavior. This novel text provides an overview of the insights that network analysis has provided into major biological processes, and how it has enhanced our understanding of the social organisation of several important taxonomic groups. It brings together researchers from a wide range of disciplines with the aim of providing both an overview of the power of the network approach for understanding patterns and process in animal populations, as well as outlining how current methodological constraints and challenges can be overcome. Animal Social Networks is principally aimed at graduate level students and researchers in the fields of ecology, zoology, animal behaviour, and evolutionary biology but will also be of interest to social scientists.
Networks are convenient mathematical models to represent the structure of complex systems, from cells to societies. In the last decade, multilayer network science – the branch of the field dealing with units interacting in multiple distinct ways, simultaneously – was demonstrated to be an effective modeling and analytical framework for a wide spectrum of empirical systems, from biopolymers networks (such as interactome and metabolomes) to neuronal networks (such as connectomes), from social networks to urban and transportation networks. In this Element, a decade after one of the most seminal papers on this topic, the authors review the most salient features of multilayer network science, covering both theoretical aspects and direct applications to real-world coupled/interdependent systems, from the point of view of multilayer structure, dynamics and function. The authors discuss potential frontiers for this topic and the corresponding challenges in the field for the next future.
Building Switched Networks provides a comprehensive, technical survey of the networking technologies that comprise the core of evolving LAN and WAN infrastructures. This book gives you essential background information, clear descriptions of relevant technologies, and an understanding of how those technologies will be employed throughout networks in the near future. In particular, the text focuses on developments that support our increasing demand for network bandwidth - multilayer switching delivery guarantees, and multicasting - and examines performance issues, resource allocation, network policy, and network services.
This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Applied Mathematics, and co-Director of MACSI, at the University of Limerick, Ireland.
The science of networks represented a substantial change in the way we see natural and technological phenomena. Now we have a better understanding that networks are, in most cases, networks of networks or multi-layered networks. This book provides a summary of the research done during one of the largest and most multidisciplinary projects in network science and complex systems (Multiplex). The science of complex networks originated from the empirical evidence that most of the structures of systems such as the internet, sets of protein interactions, and collaboration between people, share (at least qualitatively) common structural properties. This book examines how properties of networks that interact with other networks can change dramatically. The authors show that, dependent on the properties of links that interconnect two or more networks, we may derive different conclusions about the function and the possible vulnerabilities of the overall system of networks. This book presents a series of novel theoretical results together with their applications, providing a comprehensive overview of the field.