My T. Thai – författare

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

Wireless sensor networks are being employed in a variety applications ra- ing from medical to military, and from home to industry. The principle aim of this book is to provide a reference tool for the increasing number of scientists who depend upon sensor networks in some way. The book is organized into several sections, each including chapters exploring a speci?c topic. Wireless sensor networks are attracting great attention and there are many research topics yet to be studied. In this book, the topics covered include n- work design and modelling, network management, data management, security and applications. The articles presented in the book are expository, but of a scholarly nature, including the appropriate history background, a review of the state-of-the-art thinking relative to the topic, as well as a discussion of unsolved problems that are of special interest. The target readers of this book include the researchers in computer s- ence, computer engineering, and applied mathematics, as well as students in these subjects. Specialists as well as general readers will ?nd the articles st- ulating and helpful. Book Organization The book is organized into ?ve sections. Section I introduces the design and modelling of sensor networks. Chapter 1, by Iyer, Kulkarni, Mhatre, and Rosenberg, presents a taxonomy of wireless sensor networks, based on their application level objectives, tra–c characteristics and data delivery requi- ments. Popa and Lewis in Chapter 2 describe some algorithms for systematic exploration of unknown environments using a mobile wireless sensor network.

Wireless sensor networks are being employed in a variety applications ra- ing from medical to military, and from home to industry. The principle aim of this book is to provide a reference tool for the increasing number of scientists who depend upon sensor networks in some way. The book is organized into several sections, each including chapters exploring a speci?c topic. Wireless sensor networks are attracting great attention and there are many research topics yet to be studied. In this book, the topics covered include n- work design and modelling, network management, data management, security and applications. The articles presented in the book are expository, but of a scholarly nature, including the appropriate history background, a review of the state-of-the-art thinking relative to the topic, as well as a discussion of unsolved problems that are of special interest. The target readers of this book include the researchers in computer s- ence, computer engineering, and applied mathematics, as well as students in these subjects. Specialists as well as general readers will ?nd the articles st- ulating and helpful. Book Organization The book is organized into ?ve sections. Section I introduces the design and modelling of sensor networks. Chapter 1, by Iyer, Kulkarni, Mhatre, and Rosenberg, presents a taxonomy of wireless sensor networks, based on their application level objectives, tra–c characteristics and data delivery requi- ments. Popa and Lewis in Chapter 2 describe some algorithms for systematic exploration of unknown environments using a mobile wireless sensor network.

Group Testing Theory in Network Security explores a new branch of group testing theory with an application which enhances research results in network security. This brief presents new solutions on several advanced network security problems and mathematical frameworks based on the group testing theory, specifically denial-of-service and jamming attacks. A new application of group testing, illustrated in this text, requires additional theories, such as size constraint group testing and connected group testing. Included in this text is a chapter devoted to discussing open problems and suggesting new solutions for various network security problems. This text also exemplifies the connection between mathematical approaches and practical applications to group testing theory in network security. This work will appeal to a multidisciplinary audience with interests in computer communication networks, optimization, and engineering.

Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network.Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences.Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network.Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks.A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

This book presents recent developments and results found by participants of the Third International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 16-18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems.Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more.Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more.

This book presents recent developments and results found by participants of the Third International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 16-18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems.Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more.Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more.

Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network.Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences.Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network.Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks.A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics.The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

This book constitutes the refereed proceedings of the 7th International Conference on Computational Data and Social Networks, CSoNet 2018, held in Shanghai, China, in December 2018.The 44 revised full papers presented in this book toghether with 2 extended abstracts, were carefully reviewed and selected from 106 submissions. The topics cover the fundamental background, theoretical technology development, and real-world applications associated with complex and data network analysis, minimizing in uence of rumors on social networks, blockchain Markov modelling, fraud detection, data mining, internet of things (IoT), internet of vehicles (IoV), and others.

This handbook aims to serve as a one-stop, reliable source of reference, with curations of survey and expository contributions on the state-of-the-art in Blockchain technology. Part 4 (Decentralized Finance) is devoted to a high-impact application of Blockchain to finance, the sector that has most benefitted from this technology.

This handbook aims to serve as a one-stop, reliable source of reference, with curations of survey and expository contributions on the state-of-the-art in Blockchain technology. Part 4 (Decentralized Finance) is devoted to a high-impact application of Blockchain to finance, the sector that has most benefitted from this technology.

This handbook aims to serve as a one-stop, reliable resource, including curated surveys and expository contributions on federated learning. First introduced in 2016, federated learning allows devices to collaboratively learn a shared model while keeping raw data localized, thus promising to protect data privacy.

This handbook aims to serve as a one-stop, reliable resource, including curated surveys and expository contributions on federated learning. It covers a comprehensive range of topics, providing the reader with technical and non-technical fundamentals, applications, and extensive details of various topics. The readership spans from researchers and academics to practitioners who are deeply engaged or are starting to venture into the realms of trustworthy federated learning. First introduced in 2016, federated learning allows devices to collaboratively learn a shared model while keeping raw data localized, thus promising to protect data privacy. Since its introduction, federated learning has undergone several evolutions. Most importantly, its evolution is in response to the growing recognition that its promise of collaborative learning is inseparable from the imperatives of privacy preservation and model security. The resource is divided into four parts. Part 1 (Security and Privacy) explores the robust defense mechanisms against targeted attacks and addresses fairness concerns, providing a multifaceted foundation for securing Federated Learning systems against evolving threats. Part 2 (Bilevel Optimization) unravels the intricacies of optimizing performance in federated settings. Part 3 (Graph and Large Language Models) addresses the challenges in training Graph Neural Networks and ensuring privacy in Federated Learning of natural language models. Part 4 (Edge Intelligence and Applications) demonstrates how Federated Learning can empower mobile applications and preserve privacy with synthetic data.

This book constitutes the refereed proceedings of the 4th International Conference on Computational Social Networks, CSoNet 2015, held in Beijing, China, in August 2015.The 23 revised full papers and 3 short papers presented together with 2 extended abstracts were carefully reviewed and selected from 101 submissions and cover topics on social information diffusion; network clustering and community structure; social link prediction and recommendation; and social network structure analysis.

This book constitutes the refereed proceedings of the 22nd International Conference on Computing and Combinatorics, COCOON 2016, held in Ho Chi Minh City, Vietnam, in August 2016. The papers cover various topics including: Theory and Algorithms; Parameterized Complexity and Algorithms; Scheduling Algorithms and Circuit Complexity;

The papers in this volume were selected for presentation at the 16th Annual InternationalComputing and CombinatoricsConference (COCOON 2010), held duringJuly19-21,2010inNhaTrang,Vietnam.Previousmeetingsofthisconf- encewereheldinSingapore(2002),BigSky(2003),JejuIsland(2004),Kunming (2005), Taipei (2006), Alberta (2007), Dalian (2008) and New York (2009). COCOON 2010 provided a forum for researchers working in the areas of - gorithms, theory of computation, computational complexity, and combinatorics related to computing. In all, 133 papers were submitted from 40 countries and regions, of which 54 were accepted.Authors of the submitted papers were from Australia (10), Bangladesh (11), Belgium (1), Canada (23), Chile (1), China (20), Colombia (1), Czech Republic (6), Denmark (1), France (25), France(1), Germany (13), Greece (2), Hong Kong (7), Hungary (2), India (18), Indonesia (8),IslamicRepublicofIran(2),Ireland(1),Israel(6),Italy(6),Japan(31),- publicofKorea(4),Malaysia(1),TheNetherlands(2),NewZealand(2),Norway (3), Pakistan (1), Poland (1), Portugal (1), Russian Federation (3), Singapore (6), Slovakia (1), Spain (7), Sweden (2), Taiwan (19), Thailand (2), UK (2), USA (44), and Vietnam (15). The submitted papers wereevaluated by an internationalTechnical Program Committee (TPC). Each paper was evaluated by at least three TPC members, with possible assistance of the external referees, as indicated by the referee list found in the proceedings. Some of these 54 accepted papers will be selected for publication in a special issue of Algorithmica, Journal of Combinatorial - timization,and Discrete Mathematics, Algorithms, and Application under the standard refereeing procedure.In addition to the selected papers, the conf- ence also included two invited presentations by Manuel Blum (Carnegie Mellon University) and Oscar H. Ibarra (University of California Santa Barbara).