As software and computer hardware grows in complexity, networks have grown to match. The increasing scale, complexity, heterogeneity, and dynamism of communication networks, resources, and applications has made distributed computing systems brittle, unmanageable, and insecure. Internet and Distributed Computing Advancements: Theoretical Frameworks and Practical Applications is a vital compendium of chapters on the latest research within the field of distributed computing, capturing trends in the design and development of Internet and distributed computing systems that leverage autonomic principles and techniques. The chapters provided within this collection offer a holistic approach for the development of systems that can adapt themselves to meet requirements of performance, fault tolerance, reliability, security, and Quality of Service (QoS) without manual intervention.

The main objective of pervasive computing systems is to create environments where computers become invisible by being seamlessly integrated and connected into our everyday environment, where such embedded computers can then provide inf- mation and exercise intelligent control when needed, but without being obtrusive. Pervasive computing and intelligent multimedia technologies are becoming incre- ingly important to the modern way of living. However, many of their potential applications have not yet been fully realized. Intelligent multimedia allows dynamic selection, composition and presentation of the most appropriate multimedia content based on user preferences. A variety of applications of pervasive computing and - telligent multimedia are being developed for all walks of personal and business life. Pervasive computing (often synonymously called ubiquitous computing, palpable computing or ambient intelligence) is an emerging ?eld of research that brings in revolutionary paradigms for computing models in the 21st century. Pervasive c- puting is the trend towards increasingly ubiquitous connected computing devices in the environment, a trend being brought about by a convergence of advanced el- tronic - and particularly, wireless - technologies and the Internet. Recent advances in pervasive computers, networks, telecommunications and information technology, along with the proliferation of multimedia mobile devices - such as laptops, iPods, personal digital assistants (PDAs) and cellular telephones - have further stimulated the development of intelligent pervasive multimedia applications. These key te- nologiesarecreatingamultimediarevolutionthatwillhavesigni?cantimpactacross a wide spectrum of consumer, business, healthcare and governmental domains.

These proceedings gather outstanding research papers presented at the Second International Conference on Data Engineering 2015 (DaEng-2015) and offer a consolidated overview of the latest developments in databases, information retrieval, data mining and knowledge management. The conference brought together researchers and practitioners from academia and industry to address key challenges in these fields, discuss advanced data engineering concepts and form new collaborations. The topics covered include but are not limited to: * Data engineering * Big data * Data and knowledge visualization * Data management * Data mining and warehousing * Data privacy & security * Database theory * Heterogeneous databases * Knowledge discovery in databases * Mobile, grid and cloud computing * Knowledge management * Parallel and distributed data * Temporal data * Web data, services and information engineering * Decision support systems * E-Business engineering and management * E-commerce and e-learning * Geographical information systems * Information management * Information quality and strategy * Information retrieval, integration and visualization * Information security * Information systems and technologies

This book unfolds ways to transform data into innovative solutions perceived as new remarkable and meaningful value. It offers practical views of the concepts and techniques readers need to get the most out of their large-scale research and data mining projects. It strides them through the data-analytical thinking, circumvents the difficulty in deciphering complex data systems and obtaining commercialization value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad spectrum, an interdisciplinary field of scientific methods and processes. The book, Recent Advances in Soft Computing and Data Mining, delivers sufficient knowledge to tackle a wide range of issues seen in complex systems. This is done by exploring a vast combination of practices and applications by incorporating these two domains. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must choose the best design to approach the problem with the most efficient tools and techniques. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must understand the design choice and options of these approaches, thus to better appreciate the concepts, tools, and techniques used.

This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

Advances such as cloud computing and streaming multimedia are steadily increasing the demand on network resources, and telecommunications providers must ensure that their networks are managed effectively in order to ensure that Internet and mobile users remain satisfied with their quality of service. Network and Traffic Engineering in Emerging Distributed Computing Applications focuses on network management and traffic engineering for Internet and distributed computing technologies, as well as present emerging technology trends and advanced platforms. This premier reference source for academics, students, researchers, readers, and knowledge seekers puts together some of the critical aspects of Internet and distributed systems.

Addressing the applications of computational intelligence algorithms in energy, this book presents a systematic procedure that illustrates the practical steps required for applying bio-inspired, meta-heuristic algorithms in energy, such as the prediction of oil consumption and other energy products. Contributions include research findings, projects, surveying work and industrial experiences that describe significant advances in the applications of computational intelligence algorithms in energy. For easy understanding, the text provides practical simulation results, convergence and learning curves as well as illustrations and tables. Providing a valuable resource for undergraduate and postgraduate students alike, it is also intended for researchers in the fields of computational intelligence and energy.

This book offers a systematic overview of the concepts and practical techniques that readers need to get the most out of their large-scale data mining projects and research studies. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. Presenting the outcomes of International Conference on Soft Computing and Data Mining (SCDM-2017), held in Johor, Malaysia on February 6-8, 2018, it provides a well-balanced integration of soft computing and data mining techniques. The two constituents are brought together in various combinations of applications and practices. To thrive in these data-driven ecosystems, researchers, engineers, data analysts, practitioners, and managers must understand the design choice and options of soft computing and data mining techniques, and as such this book is a valuable resource, helping readers solve complex benchmark problems and better appreciate the concepts, tools, and techniques employed.

This book constitutes the refereed proceedings of the International Symposium on Security in Computing and Communications, SSCC 2015, held in Kochi, India, in August 2015. The 36 revised full papers presented together with 13 short papers were carefully reviewed and selected from 157 submissions. The papers are organized in topical sections on security in cloud computing; authentication and access control systems; cryptography and steganography; system and network security; application security.

This book addresses the adoption of intelligent algorithms for resolving challenges in different aspects of the society such as sport, cyber-security, COVID-19 pandemic, advertising, driving, smart environment-sensors, blockchain, cloud computing, and health. In addition, the book also covers machine learning fundamentals such as feature selection. The book presents practical simulation results and different illustrations in different chapters for easy understanding of concepts and approaches. The types of contributions in the book are as follows: original research, survey, and theoretical insight that describe advancement in the adoption of technique for resolving the broad range of challenges. Researchers, undergraduates, postgraduates, and industry experts will find the book as a valuable resource that bridges theory and practice.

This book unfolds ways to transform data into innovative solutions perceived as new remarkable and meaningful value. It offers practical views of the concepts and techniques readers need to get the most out of their large-scale research and data mining projects. It strides them through the data-analytical thinking, circumvents the difficulty in deciphering complex data systems and obtaining commercialization value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad spectrum, an interdisciplinary field of scientific methods and processes. The book, Recent Advances in Soft Computing and Data Mining, delivers sufficient knowledge to tackle a wide range of issues seen in complex systems. This is done by exploring a vast combination of practices and applications by incorporating these two domains. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must choose the best design to approach the problem with the most efficient tools and techniques. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must understand the design choice and options of these approaches, thus to better appreciate the concepts, tools, and techniques used.

This book features selected papers from the 6th International Conference on Mathematics and Computing (ICMC 2020), organized by Sikkim University, Gangtok, Sikkim, India, during September 2020. It covers recent advances in the field of mathematics, statistics, and scientific computing. The book presents innovative work by leading academics, researchers, and experts from industry.

This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.

This book constitutes best selected research papers presented at the International Applied Soft Computing and Communication Networks (ACN 2019) held in Trivandrum, Kerala, India during December 18 - 21, 2019. The papers are organized in topical sections on real time and multimedia communications, security and privacy, network management and software-defined networks, Internet of Things (IoT) and cyber-physical systems, intelligent distributed systems, mobile computing and vehicle communications, surveillance networks and visual intelligence, and emerging topics. The book is a reference for researchers and scientists engaged in various fields of intelligent systems.

This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.

This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.

This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to be able to secure our cyberfuture. The approaches and findings described in this book are of interest to businesses and governments seeking to secure our data and underpin infrastructures, as well as to individual users.