Reasoning in Event-Based Distributed Systems

Reasoning in Event-Based Distributed Systems

Author: Sven Helmer

Publisher: Springer Science & Business Media

Published: 2011-06-17

Total Pages: 318

ISBN-13: 364219723X

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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.


Reasoning in Event-Based Distributed Systems

Reasoning in Event-Based Distributed Systems

Author: Sven Helmer

Publisher: Springer

Published: 2011-03-29

Total Pages: 318

ISBN-13: 3642197248

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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.


Trustworthiness in Mobile Cyber Physical Systems

Trustworthiness in Mobile Cyber Physical Systems

Author: Kyungtae Kang

Publisher: MDPI

Published: 2021-08-30

Total Pages: 190

ISBN-13: 3036510869

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Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS.


Collective Intelligence for Smart Cities

Collective Intelligence for Smart Cities

Author: Chun HO WU

Publisher: Elsevier

Published: 2022-05-26

Total Pages: 248

ISBN-13: 0128202750

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Collective Intelligence for Smart Cities begins with an overview of the fundamental issues and concepts of smart cities. Surveying the current state-of-the-art research in the field, the book delves deeply into key smart city developments such as health and well-being, transportation, safety, energy, environment and sustainability. In addition, the book focuses on the role of IoT cloud computing and big data, specifically in smart city development. Users will find a unique, overarching perspective that ties together these concepts based on collective intelligence, a concept for quantifying mass activity familiar to many social science and life science researchers.Sections explore how group decision-making emerges from the consensus of the collective, collaborative and competitive activities of many individuals, along with future perspectives. - Provides collective intelligence-based solutions to enhance smart city well-being - Recommends strategies to ensure smart city sustainability and optimization, including smart transportation - Considers cloud-based data processing approaches for managing data collected from smart city applications - Uses case studies to shows successful application in a variety of smart city contexts


Advances in Knowledge Discovery and Management

Advances in Knowledge Discovery and Management

Author: Bruno Pinaud

Publisher: Springer

Published: 2017-10-09

Total Pages: 154

ISBN-13: 3319654063

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This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of “Knowledge Discovery and Management” (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories. The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC’2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.


Anomaly Detection and Complex Event Processing Over IoT Data Streams

Anomaly Detection and Complex Event Processing Over IoT Data Streams

Author: Patrick Schneider

Publisher: Academic Press

Published: 2022-01-07

Total Pages: 408

ISBN-13: 0128238194

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Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to eHealth and Patient Data Monitoring presents advanced processing techniques for IoT data streams and the anomaly detection algorithms over them. The book brings new advances and generalized techniques for processing IoT data streams, semantic data enrichment with contextual information at Edge, Fog and Cloud as well as complex event processing in IoT applications. The book comprises fundamental models, concepts and algorithms, architectures and technological solutions as well as their application to eHealth. Case studies, such as the bio-metric signals stream processing are presented –the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches including the Hierarchical Temporal Memory and Deep Learning algorithms. The book discusses adaptive solutions to IoT stream processing that can be extended to different use cases from different fields of eHealth, to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenarios. The book ends with a discussion on ethics, emerging research trends, issues and challenges of IoT data stream processing. - Provides the state-of-the-art in IoT Data Stream Processing, Semantic Data Enrichment, Reasoning and Knowledge - Covers extraction (Anomaly Detection) - Illustrates new, scalable and reliable processing techniques based on IoT stream technologies - Offers applications to new, real-time anomaly detection scenarios in the health domain


New Horizons for a Data-Driven Economy

New Horizons for a Data-Driven Economy

Author: José María Cavanillas

Publisher: Springer

Published: 2016-04-04

Total Pages: 312

ISBN-13: 3319215698

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In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.


Semantic Web

Semantic Web

Author: Michael Workman

Publisher: Springer

Published: 2015-08-27

Total Pages: 234

ISBN-13: 3319166581

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This book examines recent developments in semantic systems that can respond to situations and environments and events. The contributors to this book cover how to design, implement and utilize disruptive technologies. The editor discusses the two fundamental sets of disruptive technologies: the development of semantic technologies including description logics, ontologies and agent frameworks; and the development of semantic information rendering and graphical forms of displays of high-density time-sensitive data to improve situational awareness. Beyond practical illustrations of emerging technologies, the editor proposes to utilize an incremental development method called knowledge scaffolding –a proven educational psychology technique for learning a subject matter thoroughly. The goal of this book is to help readers learn about managing information resources, from the ground up and reinforcing the learning as they read on.


Enterprise Big Data Engineering, Analytics, and Management

Enterprise Big Data Engineering, Analytics, and Management

Author: Atzmueller, Martin

Publisher: IGI Global

Published: 2016-06-01

Total Pages: 293

ISBN-13: 1522502947

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The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.


Big Data Computing

Big Data Computing

Author: Rajendra Akerkar

Publisher: CRC Press

Published: 2013-12-05

Total Pages: 562

ISBN-13: 1466578386

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Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix