This book aims to bring together researchers and practitioners from diverse disciplines-from sociology, biology, physics, and computer science-who share a passion to better understand the interdependencies within and across systems. This volume contains contributions presented at the 11th International Conference on Complex Networks (CompleNet) in Exeter, United Kingdom, 31 March - 3 April 2020. CompleNet is a venue for discussing ideas and findings about all types of networks, from biological, to technological, to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.

Intelligent Distributed Computing - IDC Symposium Series was started as an initiative of research groups from: (i) Systems Research Institute, Polish Academy of Sciences in Warsaw, Poland and(ii)SoftwareEngineeringDepartmentoftheUniversity ofCraiova, Craiova, Romania.IDCaimsatbringingtogetherresearchersandpractitionersinvolved in all aspects of intelligent and distributed computing to allow cross-fertilization and search for synergies of ideas and to enable advancement of research in these exciting sub- elds of computer science. Intelligent Distributed Computing 2008 - IDC 2008 wasthe secondeventin thisseries. IDC2008was hostedbyDipartimentodiIngegneria Informatica e delle Telecomunicazioni, Universita di Catania, Italia during September 18-19, 2008. This book represents the peer-reviewed proceedings of the IDC 2008. We received 58submissionsfrom24countries.Each submissionwas carefullyreviewedby at least 3 membersofthe ProgramCommittee.Acceptanceandpublicationwere judgedbased on the relevanceto the symposiumthemes, clarity of presentation, originalityand accuracy of results and proposed solutions. Finally 20 regular papers and 12 short papers were selected for presentationand were includedin this volume, resultingin acceptancerates of 34.48 % for regular papers and 55.17 % for regular and short papers. The book contains also 3 invited papers authored by well-known researchers in the eld. The 35 contributions in this book address many topics related to intelligent d- tributedcomputing, systemsandapplications, including: adaptivityandlearning;agents and multi-agent systems; argumentation; auctions; case-based reasoning; collaborative systems; data structures; distributed algorithms; formal modeling and veri cation; - netic and immune algorithms; grid computing; information extraction, annotation and integration; network and security protocols; mobile and ubiquitous computing; onto- gies and metadata; P2P computing; planning; recommender systems; rules; semantic Web; services and processes; trust and social computing;virtual organizations;wireless networks; XML technolog

This book contains contributions in the area of Network Science, presented at the 14th International Conference on Complex Networks (CompleNet), 24-28 April, 2023 in Aveiro, Portugal. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems.  CompleNet is a venue to discuss ideas and findings about all types networks, from biological, to technological, to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate. The audience of the work are professionals and academics working in Network Science, a highly-multidisciplinary field.

Elucidating the spatial and temporal dynamics of how things connect has become one of the most important areas of research in the 21st century. Network science now pervades nearly every science domain, resulting in new discoveries in a host of dynamic social and natural systems, including: how neurons connect and communicate in the brain, how information percolates within and among social networks, the evolution of science research through co-authorship networks, the spread of epidemics and many other complex phenomena. Over the past decade, advances in computational power have put the tools of network analysis in the hands of increasing numbers of scientists, enabling more explorations of our world than ever before possible. Information science, social sciences, systems biology, ecosystems ecology, neuroscience and physics all benefit from this movement, which combines graph theory with data sciences to develop and validate theories about the world around us. This book brings together cutting-edge research from the network science field and includes diverse and interdisciplinary topics such as: modeling the structure of urban systems, behavior in social networks, education and learning, data network architecture, structure and dynamics of organizations, crime and terrorism, as well as network topology, modularity and community detection.

Though the reductionist approachto biology and medicine has led to several imp- tant advances, further progresses with respect to the remaining challenges require integration of representation, characterization and modeling of the studied systems along a wide range of spatial and time scales. Such an approach, intrinsically - lated to systems biology, is poised to ultimately turning biology into a more precise and synthetic discipline, paving the way to extensive preventive and regenerative medicine [1], drug discovery [20] and treatment optimization [24]. A particularly appealing and effective approach to addressing the complexity of interactions inherent to the biological systems is provided by the new area of c- plex networks [34, 30, 8, 13, 12]. Basically, it is an extension of graph theory [10], focusing on the modeling, representation, characterization, analysis and simulation ofcomplexsystemsbyconsideringmanyelementsandtheirinterconnections.C- plex networks concepts and methods have been used to study disease [17], tr- scription networks [5, 6, 4], protein-protein networks [22, 36, 16, 39], metabolic networks [23] and anatomy [40].

This book aims to bring together researchers and practitioners from diverse disciplines-from sociology, biology, physics, and computer science-who share a passion to better understand the interdependencies within and across systems. This volume contains contributions presented at the 11th International Conference on Complex Networks (CompleNet) in Exeter, United Kingdom, 31 March - 3 April 2020. CompleNet is a venue for discussing ideas and findings about all types of networks, from biological, to technological, to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.

Elucidating the spatial and temporal dynamics of how things connect has become one of the most important areas of research in the 21st century. Network science now pervades nearly every science domain, resulting in new discoveries in a host of dynamic social and natural systems, including: how neurons connect and communicate in the brain, how information percolates within and among social networks, the evolution of science research through co-authorship networks, the spread of epidemics and many other complex phenomena. Over the past decade, advances in computational power have put the tools of network analysis in the hands of increasing numbers of scientists, enabling more explorations of our world than ever before possible. Information science, social sciences, systems biology, ecosystems ecology, neuroscience and physics all benefit from this movement, which combines graph theory with data sciences to develop and validate theories about the world around us. This book brings together cutting-edge research from the network science field and includes diverse and interdisciplinary topics such as: modeling the structure of urban systems, behavior in social networks, education and learning, data network architecture, structure and dynamics of organizations, crime and terrorism, as well as network topology, modularity and community detection.

Though the reductionist approachto biology and medicine has led to several imp- tant advances, further progresses with respect to the remaining challenges require integration of representation, characterization and modeling of the studied systems along a wide range of spatial and time scales. Such an approach, intrinsically - lated to systems biology, is poised to ultimately turning biology into a more precise and synthetic discipline, paving the way to extensive preventive and regenerative medicine [1], drug discovery [20] and treatment optimization [24]. A particularly appealing and effective approach to addressing the complexity of interactions inherent to the biological systems is provided by the new area of c- plex networks [34, 30, 8, 13, 12]. Basically, it is an extension of graph theory [10], focusing on the modeling, representation, characterization, analysis and simulation ofcomplexsystemsbyconsideringmanyelementsandtheirinterconnections.C- plex networks concepts and methods have been used to study disease [17], tr- scription networks [5, 6, 4], protein-protein networks [22, 36, 16, 39], metabolic networks [23] and anatomy [40].

Intelligent Distributed Computing - IDC Symposium Series was started as an initiative of research groups from: (i) Systems Research Institute, Polish Academy of Sciences in Warsaw, Poland and(ii)SoftwareEngineeringDepartmentoftheUniversity ofCraiova, Craiova, Romania.IDCaimsatbringingtogetherresearchersandpractitionersinvolved in all aspects of intelligent and distributed computing to allow cross-fertilization and search for synergies of ideas and to enable advancement of research in these exciting sub- elds of computer science. Intelligent Distributed Computing 2008 - IDC 2008 wasthe secondeventin thisseries. IDC2008was hostedbyDipartimentodiIngegneria Informatica e delle Telecomunicazioni, Universita di Catania, Italia during September 18-19, 2008. This book represents the peer-reviewed proceedings of the IDC 2008. We received 58submissionsfrom24countries.Each submissionwas carefullyreviewedby at least 3 membersofthe ProgramCommittee.Acceptanceandpublicationwere judgedbased on the relevanceto the symposiumthemes, clarity of presentation, originalityand accuracy of results and proposed solutions. Finally 20 regular papers and 12 short papers were selected for presentationand were includedin this volume, resultingin acceptancerates of 34.48 % for regular papers and 55.17 % for regular and short papers. The book contains also 3 invited papers authored by well-known researchers in the eld. The 35 contributions in this book address many topics related to intelligent d- tributedcomputing, systemsandapplications, including: adaptivityandlearning;agents and multi-agent systems; argumentation; auctions; case-based reasoning; collaborative systems; data structures; distributed algorithms; formal modeling and veri cation; - netic and immune algorithms; grid computing; information extraction, annotation and integration; network and security protocols; mobile and ubiquitous computing; onto- gies and metadata; P2P computing; planning; recommender systems; rules; semantic Web; services and processes; trust and social computing;virtual organizations;wireless networks; XML technolog

This book contains contributions presented at the 13th International Conference on Complex Networks (CompleNet), April 19-22, 2022. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines-from sociology, biology, physics, and computer science-who share a passion to better understand the interdependencies within and across systems. CompleNet is a venue to discuss ideas and findings about all types of networks, from biological to technological and to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.

This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Complex Networks, CompleNet 2010, which was held in Rio de Janeiro, Brazil, in October 2010. The 21 revised papers presented were carefully reviewed and selected from 48 submissions. The topics covered include: 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.