Principles and Applications of Distributed Event-Based Systems showcases event-based systems in real-world applications. Containing expert international contributions, this advanced publication provides professionals, researchers, and students in systems design with a rich compendium of latest applications in the field.
This dissertation thesis presents an approach enabling the modelling and quality-of-service prediction of event-based systems at the architecture-level. Applying a two-step model refinement transformation, the approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques.
With the rapid expansion of the Internet over the last 20 years, event-based distributed systems are playing an increasingly important role in a broad range of application domains, including enterprise management, environmental monitoring, information dissemination, finance, pervasive systems, autonomic computing, collaborative working and learning, and geo-spatial systems. Many different architectures, languages and technologies are being used for implementing event-based distributed systems, and much of the development has been undertaken independently by different communities. However, a common factor is an ever-increasing complexity. Users and developers expect that such systems are able not only to handle large volumes of simple events but also to detect complex patterns of events that may be spatially distributed and may span significant periods of time. Intelligent and logic-based approaches provide sound foundations for addressing many of the research challenges faced and this book covers a broad range of recent advances, contributed by leading experts in the field. It presents a comprehensive view of reasoning in event-based distributed systems, bringing together reviews of the state-of-the art, new research contributions, and an extensive set of references. It will serve as a valuable resource for students, faculty and researchers as well as industry practitioners responsible for new systems development.
Data management has evolved over the years from being strictly associated with database systems, through active databases, to become a topic that has grown beyond the scope of a single field encompassing a large range of subjects, such as distributed systems, event-driven systems, and peer-to-peer and streaming systems. The present collection of works, which sheds light on various facets of data management, is dedicated to Prof. Alejandro Buchmann on the occasion of his 60th birthday. His scientific path looks back on more than thirty years of successful academic life and high-impact research. With this book we celebrate Prof. Buchmann's vision and achievements.
This book presents original contributions on the theories and practices of emerging Internet, data and web technologies and their applicability in businesses, engineering and academia. The Internet has become the most proliferative platform for emerging large-scale computing paradigms. Among them, data and web technologies are two most prominent paradigms, and manifest in a variety of forms such as data centers, cloud computing, mobile cloud, mobile web services and so on. Together, these technologies form a digital ecosystem based on the data cycle, from capturing to processing, analysis and visualization. The investigation of various research and development issues in this digital ecosystem is made all the more important by the ever-increasing needs of real-life applications, which involve storing and processing large amounts of data. As a key feature, the book addresses advances in the life-cycle exploitation of data generated from the digital ecosystem, and data technologies that create value for businesses, moving toward a collective intelligence approach. Given its scope, the book offers a valuable reference guide for researchers, software developers, practitioners and students interested in the field of data and web technologies.
This book presents the latest innovative research findings, methods, and development techniques related to intelligent social networks and collaborative systems, intelligent networking systems, mobile collaborative systems, and secure intelligent cloud systems. Offering both theoretical and practical perspectives, it also reveals synergies among various paradigms in the multi-disciplinary field of intelligent collaborative systems. With the rapid development of the Internet, we are experiencing a shift from the traditional sharing of information and applications as the main purpose of the Web to an emergent paradigm that places people at the very centre of networks, making full use of their connections, relations, and collaboration. Social networks also play a major role in the dynamics and structure of intelligent Web-based networking and collaborative systems. Virtual campuses, communities and organizations strongly leverage intelligent networking and collaborative systems through a wide variety of formal and informal electronic relations, such as business-to-business, peer-to-peer, and many types of online collaborative learning interactions, including the emerging e-learning systems. This has resulted in entangled systems that need to be managed efficiently and autonomously. In addition, while the latest powerful technologies based on grid and wireless infrastructures as well as cloud computing are currently greatly enhancing collaborative and networking applications, they are also facing new challenges. The principal purpose of the research and development community is to stimulate research that will lead to the creation of responsive environments for networking and, in the long term, the development of adaptive, secure, mobile, and intuitive intelligent systems for collaborative work and learning.
This book presents the latest research findings and innovative theoretical and practical research methods and development techniques related to the emerging areas of information networking and their applications. Today’s networks and information systems are evolving rapidly, and there are several new trends and applications, such as wireless sensor networks, ad hoc networks, peer-to-peer systems, vehicular networks, opportunistic networks, grid and cloud computing, pervasive and ubiquitous computing, multimedia systems, security, multi-agent systems, high-speed networks, and web-based systems. These networks have to deal with the increasing number of users, provide support for different services, guarantee the QoS, and optimize the network resources, and as such there are numerous research issues and challenges that need to be considered and addressed.
This book gathers 12 of the most promising papers presented at the 15th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2017) held on June 7–9, 2017 at the University of Greenwich, London, UK. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science, to share their experiences and to exchange new ideas and information in a meaningful way. The book also presents research findings regarding all aspects (theory, applications and tools) of computer and information science, and discusses the practical challenges encountered along the way and the solutions adopted to solve them.
Stream processing is a novel distributed computing paradigm that supports the gathering, processing and analysis of high-volume, heterogeneous, continuous data streams, to extract insights and actionable results in real time. This comprehensive, hands-on guide combining the fundamental building blocks and emerging research in stream processing is ideal for application designers, system builders, analytic developers, as well as students and researchers in the field. This book introduces the key components of the stream computing paradigm, including the distributed system infrastructure, the programming model, design patterns and streaming analytics. The explanation of the underlying theoretical principles, illustrative examples and implementations using the IBM InfoSphere Streams SPL language and real-world case studies provide students and practitioners with a comprehensive understanding of such applications and the middleware that supports them.
