Managing the Web of Things - Product Image

Managing the Web of Things

  • ID: 3947060
  • Book
  • 482 Pages
  • Elsevier Science and Technology
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Managing the Web of Things: Linking the Real World to the Web presents a consolidated and holistic coverage of engineering, management, and analytics of the Internet of Things. The web has gone through many transformations, from traditional linking and sharing of computers and documents (i.e., Web of Data), to the current connection of people (i.e., Web of People), and to the emerging connection of billions of physical objects (i.e., Web of Things).

With increasing numbers of electronic devices and systems providing different services to people, Web of Things applications present numerous challenges to research institutions, companies, governments, international organizations, and others. This book compiles the newest developments and advances in the area of the Web of Things, ranging from modeling, searching, and data analytics, to software building, applications, and social impact.

Its coverage will enable effective exploration, understanding, assessment, comparison, and the selection of WoT models, languages, techniques, platforms, and tools. Readers will gain an up-to-date understanding of the Web of Things systems that accelerates their research.

  • Offers a comprehensive and systematic presentation of the methodologies, technologies, and applications that enable efficient and effective management of the Internet of Things
  • Provides an in-depth analysis on the state-of-the-art Web of Things modeling and searching technologies, including how to collect, clean, and analyze data generated by the Web of Things
  • Covers system design and software building principles, with discussions and explorations of social impact for the Web of Things through real-world applications
  • Acts as an ideal reference or recommended text for graduate courses in cloud computing, service computing, and more
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Part 1: Modeling and Searching 1. Ontologies and context modeling for the Web of Things 2. The Anatomy of An Intent Based Search and Crawler Engine for the Web of Things 3. Modeling RESTful Web of Things Services 4. A Semantic-Rich Approach to IoT Using the Generalized World Entities Paradigm

Part 2: System Building and Practices 6. A WoT Testbed for Research and Course Projects 7. Using Reference Architectures for Design and Evaluation of Web of Things Systems 8. Efficient and Secure Pull Requests for Emergency Cases Using a Mobile Access Framework

Part 3: Data Integration and Analytics 9. Automatic Integration and Querying of Semantic Rich Heterogeneous Data 10. Building Entity Graphs for the Web of Things Management 11. Building Interoperable and Cross-Domain Semantic Web of Things Applications 12. Web of Things Data Storage

Part 4: Applications, Security and Social Impact 14. Security Issues of the Web of Things 15. A Web of Fitness "Things”: An Exploration of Social Impacts & Vulnerable Populations

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Sheng, Michael
Quan Z. (?Michael) Sheng is currently a full Professor and Head of Department of Computing, at Macquarie University. Prof. Sheng has more than 10 years' research and development experience in the Internet of Things (IoT) and related areas such as service-oriented computing, radio frequency identification (RFID), sensor networks, and big data analytics. He has published more than 280 publications in these areas and is one of the top-ranked authors in the "World Wide Web" research area according to Microsoft Academic Search. Prof. Michael Sheng is the recipient to a number of prestigious awards including ARC Future Fellowship in 2014, Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003).
Qin, Yongrui
Yongrui Qin is currently a Lecturer at School of Computing and Engineering, University of Huddersfield, United Kingdom. His main research interests include the Internet of Things, Graph Data Management, Data Stream Processing, Data Mining, Information Retrieval, Semantic Web, Computer Networks, and Mobile Computing. Dr. Qin has published more than 40 refereed technical papers, including publications in prestigious journals, such as IEEE Trans. on Parallel Distributed Systems, World Wide Web Journal, Journal of Network and Computer Applications, and IEEE Internet Computing, as well as top international conferences, such as SIGIR, EDBT, CIKM, WISE, DASFAA, and SSDBM.
Yao, Lina
Lina Yao is currently a Lecturer at School of Computer Science and Engineering, the University of New South Wales. Her research interest lies in Data Mining, Internet of Things Analytics, Ubiquitous Computing, and Service Computing. Her work has published in a wide range of prestigious journals such as ACM Trans. on Intelligent Systems and Technology (TIST), ACM Trans. on Internet Technology (TOIT), IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Trans. on Knowledge Discovery and Engineering (TKDE), IEEE Internet Computing, ACM Trans. on Knowledge Discovery (TKDD) and IEEE Trans. on Services Computing (TSC), as well as top international conferences such as SIGIR, ICDM, UbiComp, CIKM and ICSOC. She is the recipient of Australian Research Council Discovery Early Career Researcher Award (2015) and is recognized as Inaugural Vice Chancellor's Women's Research Excellence Award (2015).
Benatallah, Boualem
Boualem Benatallah is currently a Scientia Professor at the School of Computer Science and Engineering, the University of New South Wales. Prof. Benatallah's research focuses on Web service protocol analysis and management, enterprise services integration, large scale data sharing, cloud computing, and the Internet of Things (IoT). He is the leader of the Service Oriented Computing research group and has more than 220 research papers in leading international journals and conference proceedings. Prof. Benatallah's research has been heavily cited by his international peers. He has more than 14,000 citations with an H-index of 52, according to Google Scholar.
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