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The International Workshop on Complex Networks—CompleNet
(www.complenet.org)—was initially proposed in 2008 with the first workshop
taking place in 2009. The initiative was the result of efforts from researchers
from the Bio-Complex Laboratory in the Department of Computer Sciences at
Florida Institute of Technology, USA, and the Dipartimento di Ingegneria Elettrica,
Elettronica e Informatica, Universit`a di Catania, Italy. CompleNet aims
at bringing together researchers and practitioners working on areas related to
complex networks. In the past two decades we have been witnessing an exponential
increase in the number of publications in this field. From biological systems
to computer science, from economic to social systems, complex networks are becoming
pervasive in many fields of science. It is this interdisciplinary nature of
complex networks that CompleNet aims at addressing. CompleNet 2010 was the
second event in the series and was hosted by the N´ucleo de Transferˆencia de
Technologia at the Federal University of Rio de Janeiro (UFRJ) during October
13–15, 2010.
This book includes the peer-reviewed list of works presented at CompleNet
2010. Submissions were accepted either as a paper or as an abstract (presentation
only). We received 48 submissions from 18 countries. Each submission was
reviewed by at least three members of the Program Committee. Acceptance was
judged based on the relevance to the symposium themes, clarity of presentation,
originality and accuracy of results and proposed solutions. After the review
process, eight papers and nine short papers were selected for presentation. We
also invited 24 abstracts for presentation only. In this volume we have included
the 21 papers and short papers plus a very selected number of abstracts. The
authors of abstracts were invited to submit a paper after their presentation at
CompleNet and the papers went through a second round of peer revision.
The 21 contributions in this book address many topics related to complex networks
including: community structure, network metrics, network models, effect
of topology to epidemics, algorithms to classify networks, self-organized algorithms
applied to complex networks, as well as many applications of complex
networks in biology, image analysis, software development, traffic congestion,
language and speech, sensor networks, and synchronization. |
