Complex Networks

The users of such systems, located at different (geographical or managerial) network cluster may have a limited access to the system’s services and resources, and different, often conflicting, expectations and requirements. An optimal energy utilization has reached to a point that many information technology (IT) managers and corporate executives are all up in arms to identify scalable solution that can reduce electricity consumption (so that the total cost of operation is minimized) of their respective large-scale computing systems and simultaneously improve upon or maintain the current throughput of the system.The recent evolutionary and general metaheuristic-based solutions for energy optimization in data processing, scheduling, resource allocation, and communication in modern computational grids, could and network computing are presented along with several important conventional technologies to cover the hot topics from the fundamental theory of the ‘’green computing’’ concept and to describe the basic architectures of systems.

The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality. Software Engineering Research, Management and Applications 2012.  The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.

  The papers were chosen based on review scores submitted by members of the program committee, and underwent further rigorous rounds of review. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems..Computer and Information Science 2012 Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.

  The purpose of the 11th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2012) was held on May 30-1June1, 2012 in Shanghai, China is to bring together scientist, engineers, computer users, students to share their experiences and exchange new ideas, and research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them   The conference organizers selected the best 20 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.Computer and Information Science 2012 Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.

. But modern network research could show that the majority of nodes of real networks is very low connected, and, by contrast, there exists some nodes of very extreme connectivity (hubs). This sample of works in this book gives as a taste of what is in the horizon such controlling the dynamics of a network and in the network, using social interactions to improve urban planning, ranking in music, and the understanding knowledge transfer in influence networks.

Since year 2000, scientists on artificial and natural intelligences started to study chance discovery - methods for discovering events/situations that significantly affect decision making. Readers may urge us to list the fourth, fifth, sixth, … but let us stop here and open this book.g.   joined this field and interacted with cognitive/computational scientists in workshops on chance discovery, to obtain breakthroughs by stimulating each other.

  The current theories coupled with the availability of data makes the field of Complex Networks (sometimes called Network Sciences) one of the most promising interdisciplinary disciplines of today. But modern network research could show that the majority of nodes of real networks is very low connected, and, by contrast, there exists some nodes of very extreme connectivity (hubs).

. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve.Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth.

But modern network research could show that the majority of nodes of real networks is very low connected, and, by contrast, there exists some nodes of very extreme connectivity (hubs).Complex Networks In the last decade we have seen the emergence of a new inter-disciplinary field concentrating on the understanding large networks which are dynamic, large, open, and have a structure that borders order and randomness. Traditionally, real networks were supposed to have a majority of nodes of about the same number of connections around an average.

In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting from a single cell interacting with its environment, eventually including a changing local neighbourhood of other cells.