Scale-Free Networks

Complex Webs in Nature and Technology

Scale-Free Networks

Many different systems both in nature and in technology can be described by means of networks of interconnected components. Despite their different aspects, all of them share similar mathematical properties. In this book we explain how to recognize these features and why these different systems develop this common structure.

Power Laws, Scale-Free Networks and Genome Biology

Power Laws, Scale-Free Networks and Genome Biology

Power Laws, Scale-free Networks and Genome Biology deals with crucial aspects of the theoretical foundations of systems biology, namely power law distributions and scale-free networks which have emerged as the hallmarks of biological organization in the post-genomic era. The chapters in the book not only describe the interesting mathematical properties of biological networks but moves beyond phenomenology, toward models of evolution capable of explaining the emergence of these features. The collection of chapters, contributed by both physicists and biologists, strives to address the problems in this field in a rigorous but not excessively mathematical manner and to represent different viewpoints, which is crucial in this emerging discipline. Each chapter includes, in addition to technical descriptions of properties of biological networks and evolutionary models, a more general and accessible introduction to the respective problems. Most chapters emphasize the potential of theoretical systems biology for discovery of new biological phenomena.

Computational Science -- ICCS 2005

5th International Conference, Atlanta, GA, USA, May 22-25, 2005, Proceedings

Computational Science -- ICCS 2005

The three-volume set LNCS 3514-3516 constitutes the refereed proceedings of the 5th International Conference on Computational Science, ICCS 2005, held in Atlanta, GA, USA in May 2005. The 464 papers presented were carefully reviewed and selected from a total of 834 submissions for the main conference and its 21 topical workshops. The papers span the whole range of computational science, ranging from numerical methods, algorithms, and computational kernels to programming environments, grids, networking, and tools. These fundamental contributions dealing with computer science methodologies and techniques are complemented by papers discussing computational applications and needs in virtually all scientific disciplines applying advanced computational methods and tools to achieve new discoveries with greater accuracy and speed.

The Logistic Map and the Route to Chaos

From the Beginnings to Modern Applications

The Logistic Map and the Route to Chaos

This title is included in the Springer Complexity program

Large Scale Networks

Modeling and Simulation

Large Scale Networks

This book offers a rigorous analysis of the achievements in the field of traffic control in large networks, oriented on two main aspects: the self-similarity in traffic behaviour and the scale-free characteristic of a complex network. Additionally, the authors propose a new insight in understanding the inner nature of things, and the cause-and-effect based on the identification of relationships and behaviours within a model, which is based on the study of the influence of the topological characteristics of a network upon the traffic behaviour. The effects of this influence are then discussed in order to find new solutions for traffic monitoring and diagnosis and also for traffic anomalies prediction. Although these concepts are illustrated using highly accurate, highly aggregated packet traces collected on backbone Internet links, the results of the analysis can be applied for any complex network whose traffic processes exhibit asymptotic self-similarity, perceived as an adaptability of traffic in networks. However, the problem with self-similar models is that they are computationally complex. Their fitting procedure is very time-consuming, while their parameters cannot be estimated based on the on-line measurements. In this aim, the main objective of this book is to discuss the problem of traffic prediction in the presence of self-similarity and particularly to offer a possibility to forecast future traffic variations and to predict network performance as precisely as possible, based on the measured traffic history.

Unifying Themes in Complex Systems

Vol VI: Proceedings of the Sixth International Conference on Complex Systems

Unifying Themes in Complex Systems

In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. "Unifying Themes in Complex Systems" is a well established series of carefully edited conference proceedings that serve the purpose of documenting and archiving the progress of cross-fertilization in this field. About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex systems and its application for the betterment of society. NECSI hosts the International Conference on Complex Systems and publishes the NECSI Book Series in conjunction with Springer Publishers.

Centrality Metrics for Complex Network Analysis: Emerging Research and Opportunities

Emerging Research and Opportunities

Centrality Metrics for Complex Network Analysis: Emerging Research and Opportunities

As network science and technology continues to gain popularity, it becomes imperative to develop procedures to examine emergent network domains, as well as classical networks, to help ensure their overall optimization. Centrality Metrics for Complex Network Analysis: Emerging Research and Opportunities is a pivotal reference source for the latest research findings on centrality metrics and their broader applications for different categories of networks including wireless sensor networks, curriculum networks, social networks etc. Featuring extensive coverage on relevant areas, such as complex network graphs, node centrality metrics, and mobile sensor networks, this publication is an ideal resource for students, faculty, industry practitioners, and business professionals interested in theoretical concepts and current developments in network domains.

The Structure and Dynamics of Networks:

The Structure and Dynamics of Networks:

From the Internet to networks of friendship, disease transmission, and even terrorism, the concept--and the reality--of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields--including mathematics, physics, computer science, sociology, and biology--have been pursuing these questions and building a new "science of networks." This book brings together for the first time a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field. The book is organized into four sections, each preceded by an editors' introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science--the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science.