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Design your networks to successfully manage their growing complexity Network professionals have often been told that today’s modern control planes would simplify their networks. The opposite has happened: Technologies like SDN and NFV, although immensely valuable, are exacerbating complexity instead of solving it. Navigating Network Complexity is the first comprehensive guide to managing this complexity in both deployment and day-to-day operations. Russ White and Jeff Tantsura introduce modern complexity theory from the standpoint of the working network engineer, helping you apply it to the practical problems you face every day. Avoiding complex mathematical models, they show how to characterize network complexity, so you can understand it and control it. The authors examine specific techniques and technologies associated with network control planes, including SDNs, fast reroute, segment routing, service chaining, and cloud computing. They reveal how each of these affects network design and complexity and help you anticipate causes of failure in highly complex systems.
The Domain Name System (DNS) enables user-friendly alphanumeric namesâ€"domain namesâ€"to be assigned to Internet sites. Many of these names have gained economic, social, and political value, leading to conflicts over their ownership, especially names containing trademarked terms. Congress, in P.L. 105-305, directed the Department of Commerce to request the NRC to perform a study of these issues. When the study was initiated, steps were already underway to address the resolution of domain name conflicts, but the continued rapid expansion of the use of the Internet had raised a number of additional policy and technical issues. Furthermore, it became clear that the introduction of search engines and other tools for Internet navigation was affecting the DNS. Consequently, the study was expanded to include policy and technical issues related to the DNS in the context of Internet navigation. This report presents the NRC's assessment of the current state and future prospects of the DNS and Internet navigation, and its conclusions and recommendations concerning key technical and policy issues.
Development processes need to engage effectively with complex system dynamics. Navigating Complexity in International Development offers detail case studies of interventions which articulate clear methodological underpinnings and draws out the implications both for development, practise and practitioners.
Complex systems analysis has become a fascinating topic in modern research on non-linear dynamics, not only in the physical sciences but also in the life sciences and the social sciences. After the era of bifurcation theory, chaos theory, syn- getics, resilience analysis, network dynamics and evolutionary thinking, currently we observe an increasing interest in critical transitions of dynamic real-world systems in many disciplines, such as demography, biology, psychology, economics, earth sciences, geology, seismology, medical sciences, and so on. The relevance of this approach is clearly re?ected in such phenomena as traf?c congestion, ?nancial crisis, ethnic con?icts, eco-system breakdown, health failures, etc. This has prompted a world-wide interest in complex systems. Geographical space is one of the playgrounds for complex dynamics, as is witnessed by population movements, transport ?ows, retail developments, urban expansion, lowland ?ooding and so forth. All such dynamic phenomena have one feature in common: the low predictability of uncertain interrelated events occurring at different interconnected spatio-temporal scale levels and often originating from different disciplinary backgrounds. The study of the associated non-linear (fast and slow) dynamic transition paths calls for a joint research effort of scientists from different disciplines in order to understand the nature, the roots and the con- quences of unexpected or unpredictable changes in complex spatial systems.
Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
Across organisations and communities there are leaders who manage to get things done through their ability to understand how a network of individuals connect, who to talk to and how to bring people together in the right constellation of effort. These are "network leaders". Network Leadership enables readers to identify and make the most of informal social and organisational networks in order to challenge the status quo effectively and facilitate greater engagement and productivity. Not only will the research in these chapters help you become a better leader and manager of your own team or department, it will also help make you a better network leader, effecting positive change across teams, and departmental and organisational boundaries. Leaders who facilitate action do so through four key practices: they understand the social systems in which they work; they have convening power, uncovering and connecting underlying movements and giving voice to something that is worth listening to; they lead beyond their formal authority; and they possess the power of restless persuasion and a capacity to thrive in complexity and crises. This book is invaluable reading for those who have mastered the basics of leadership but wish to take the next steps. It is particularly relevant to organisations and managers dealing with the geographic separation of business units, change, innovation, matrix management, project or portfolio management and other cross-departmental projects.
This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks – illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains.
Network Science is the emerging field concerned with the study of large, realistic networks. This interdisciplinary endeavor, focusing on the patterns of interactions that arise between individual components of natural and engineered systems, has been applied to data sets from activities as diverse as high-throughput biological experiments, online trading information, smart-meter utility supplies, and pervasive telecommunications and surveillance technologies. This unique text/reference provides a fascinating insight into the state of the art in network science, highlighting the commonality across very different areas of application and the ways in which each area can be advanced by injecting ideas and techniques from another. The book includes contributions from an international selection of experts, providing viewpoints from a broad range of disciplines. It emphasizes networks that arise in nature—such as food webs, protein interactions, gene expression, and neural connections—and in technology—such as finance, airline transport, urban development and global trade. Topics and Features: begins with a clear overview chapter to introduce this interdisciplinary field; discusses the classic network science of fixed connectivity structures, including empirical studies, mathematical models and computational algorithms; examines time-dependent processes that take place over networks, covering topics such as synchronisation, and message passing algorithms; investigates time-evolving networks, such as the World Wide Web and shifts in topological properties (connectivity, spectrum, percolation); explores applications of complex networks in the physical and engineering sciences, looking ahead to new developments in the field. Researchers and professionals from disciplines as varied as computer science, mathematics, engineering, physics, chemistry, biology, ecology, neuroscience, epidemiology, and the social sciences will all benefit from this topical and broad overview of current activities and grand challenges in the unfolding field of network science.
The Art of Network Architecture Business-Driven Design The business-centered, business-driven guide to architecting and evolving networks The Art of Network Architecture is the first book that places business needs and capabilities at the center of the process of architecting and evolving networks. Two leading enterprise network architects help you craft solutions that are fully aligned with business strategy, smoothly accommodate change, and maximize future flexibility. Russ White and Denise Donohue guide network designers in asking and answering the crucial questions that lead to elegant, high-value solutions. Carefully blending business and technical concerns, they show how to optimize all network interactions involving flow, time, and people. The authors review important links between business requirements and network design, helping you capture the information you need to design effectively. They introduce today’s most useful models and frameworks, fully addressing modularity, resilience, security, and management. Next, they drill down into network structure and topology, covering virtualization, overlays, modern routing choices, and highly complex network environments. In the final section, the authors integrate all these ideas to consider four realistic design challenges: user mobility, cloud services, Software Defined Networking (SDN), and today’s radically new data center environments. • Understand how your choices of technologies and design paradigms will impact your business • Customize designs to improve workflows, support BYOD, and ensure business continuity • Use modularity, simplicity, and network management to prepare for rapid change • Build resilience by addressing human factors and redundancy • Design for security, hardening networks without making them brittle • Minimize network management pain, and maximize gain • Compare topologies and their tradeoffs • Consider the implications of network virtualization, and walk through an MPLS-based L3VPN example • Choose routing protocols in the context of business and IT requirements • Maximize mobility via ILNP, LISP, Mobile IP, host routing, MANET, and/or DDNS • Learn about the challenges of removing and changing services hosted in cloud environments • Understand the opportunities and risks presented by SDNs • Effectively design data center control planes and topologies
This book gathers high-quality, peer-reviewed research papers presented at the Second International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2019), held in Kiev, Ukraine on 26–27 January 2019, and jointly organized by the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” and the International Research Association of Modern Education and Computer Science. The papers discuss state-of-the-art topics and advances in computer science; neural networks; pattern recognition; engineering techniques; genetic coding systems; deep learning and its medical applications; and knowledge representation and its applications in education. Given its scope, the book offers an excellent resource for researchers, engineers, management practitioners, and graduate and undergraduate students interested in computer science and its applications in engineering and education.