This volume contains a snapshot of some features of the Internet that may be fruitfully approached using a complex systems perspective, meaning using interdisciplinary tools and methods to tackle the subject area.

This volume contains a snapshot of some features of the Internet that may be fruitfully approached using a complex systems perspective, meaning using interdisciplinary tools and methods to tackle the subject area.

This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.

With the growing maturity of information and communication technologies, systems have been interconnected within growing networks, yielding new services through a combination of the system functionalities. This leads to an increasing complexity that has to be managed in order to take advantage of these system integrations. This book provides key answers as to how such systems of systems can be engineered and how their complexity can be mastered. After reviewing some definitions on systems of systems engineering, the book focuses on concrete applications and offers a survey of the activities and techniques that allow engineering of complex systems and systems of systems. Case studies, ranging from emergency situations such as Hurricane Katrina and its crisis management or a generic scenario of a major traffic accident and its emergency response, to the establishment of a scientific basis in the Antarctic region illustrate key factors of success and traps to avoid in order to cope with such situations.

Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and to provide a communications platform facilitating an exchange of concepts, ideas and needs between the scientists and technologist and complex system modelers. On the application side, the book focuses on modeling and simulation of natural and man-made complex systems. On the computing technology side, emphasis is placed on the distributed computing approaches, but supercomputing and other novel technologies are also considered.

The book on complex systems, sustainability, and innovation explores a broad set of ideas and presents some of the state-of-the-art research in this field concisely in six chapters. In a complex system, it is difficult to know exactly how the individual components contribute to an observed behavior and the extent of each component's contributions. It is the interactions of the individual components that determine the emergent functionalities. This makes it difficult to understand and predict the behavior of complex systems and hence the effects of any innovations in this field. This necessitates for the emergence of a new age of innovations with the main focus on user orientation and sustainability. This book explores some of the complex systems and their dependence on the environment to provide a long-term perspective, aiding innovations and supporting a sustainable society. The intended audience of this book will mainly consist of researchers, research students, and practitioners in the field of complex systems and sustainability.

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.