Internet of Things: Principles and Paradigms captures the state-of-the-art research in Internet of Things, its applications, architectures, and technologies. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. The Internet of Things (IoT) paradigm promises to make any electronic devices part of the Internet environment. This new paradigm opens the doors to new innovations and interactions between people and things that will enhance the quality of life and utilization of scarce resources.
To help realize the full potential of IoT, the book addresses its numerous challenges and develops the conceptual and technological solutions for tackling them. These challenges include the development of scalable architecture, moving from closed systems to open systems, designing interaction protocols, autonomic management, and the privacy and ethical issues around data sensing, storage, and processing.
Key Features
- Addresses the main concepts and features of the IoT paradigm
- Describes different architectures for managing IoT platforms
- Provides insight on trust, security, and privacy in IoT environments
- Describes data management techniques applied to the IoT environment
- Examines the key enablers and solutions to enable practical IoT systems
- Looks at the key developments that support next generation IoT platforms
- Includes input from expert contributors from both academia and industry on building and deploying IoT platforms and applications
- List of Contributors
- About the Editors
- Preface
- Acknowledgments
- Part I: IoT ecosystem concepts and architectures
- Chapter 1: Internet of Things: an overview
- Abstract
- 1.1. Introduction
- 1.2. Internet of Things definition evolution
- 1.3. IoT architectures
- 1.4. Resource management
- 1.5. IoT data management and analytics
- 1.6. Communication protocols
- 1.7. Internet of Things applications
- 1.8. Security
- 1.9. Identity management and authentication
- 1.10. Privacy
- 1.11. Standardization and regulatory limitations
- 1.12. Conclusions
- Chapter 2: Open source semantic web infrastructure for managing IoT resources in the Cloud
- Abstract
- 2.1. Introduction
- 2.2. Background/related work
- 2.3. OpenIoT architecture for IoT/cloud convergence
- 2.4. Scheduling process and IoT services lifecycle
- 2.5. Scheduling and resource management
- 2.6. Validating applications and use cases
- 2.7. Future research directions
- 2.8. Conclusions
- Acknowledgments
- Chapter 3: Device/Cloud collaboration framework for intelligence applications
- Abstract
- 3.1. Introduction
- 3.2. Background and related work
- 3.3. Device/cloud collaboration framework
- 3.4. Applications of device/cloud collaboration
- 3.5. Future work
- 3.6. Conclusions
- Acknowledgments
- Chapter 4: Fog Computing: principles, architectures, and applications
- Abstract
- 4.1. Introduction
- 4.2. Motivating scenario
- 4.3. Definitions and characteristics
- 4.4. Reference architecture
- 4.5. Applications
- 4.6. Research directions and enablers
- 4.7. Commercial products
- 4.8. Case study
- 4.9. Conclusions
- Chapter 1: Internet of Things: an overview
- Part II: IoT enablers and solutions
- Chapter 5: Programming frameworks for Internet of Things
- Abstract
- 5.1. Introduction
- 5.2. Background
- 5.3. Survey of IoT programming frameworks
- 5.4. Future research directions
- 5.5. Conclusions
- Chapter 6: Virtualization on embedded boards as enabling technology for the Cloud of Things
- Abstract
- 6.1. Introduction
- 6.2. Background
- 6.3. Virtualization and real-time
- 6.4. Experimental results
- 6.5. Future research directions
- 6.6. Conclusions
- Chapter 7: Micro Virtual Machines (MicroVMs) for Cloud-assisted Cyber-Physical Systems (CPS)
- Abstract
- 7.1. Introduction
- 7.2. Related work
- 7.3. Architecture for deploying CPS in the Cloud and the expansion of the IoT
- 7.4. Extending the possibilities of the IoT by Cloud Computing
- 7.5. Micro Virtual Machines with the Sensor Observation Service, the path between smart objects and CPS
- 7.6. IoT architecture for selected use cases
- 7.7. Future research directions
- 7.8. Conclusions
- Chapter 5: Programming frameworks for Internet of Things
- Part III: IoT data and knowledge management
- Chapter 8: Stream processing in IoT: foundations, state-of-the-art, and future directions
- Abstract
- 8.1. Introduction
- 8.2. The foundations of stream processing in IoT
- 8.3. Continuous Logic Processing System
- 8.4. Challenges and future directions
- 8.5. Conclusions
- Chapter 9: A framework for distributed data analysis for IoT
- Abstract
- 9.1. Introduction
- 9.2. Preliminaries
- 9.3. Anomaly detection
- 9.4. Problem statement and definitions
- 9.5. Distributed anomaly detection
- 9.6. Efficient incremental local modeling
- 9.7. Summary
- Chapter 8: Stream processing in IoT: foundations, state-of-the-art, and future directions
- Part IV: IoT reliability, security, and privacy
- Chapter 10: Security and privacy in the Internet of Things
- Abstract
- 10.1. Concepts
- 10.2. IoT security overview
- 10.3. Security frameworks for IoT
- 10.4. Privacy in IoT networks
- 10.5. Summary and conclusions
- Chapter 11: Internet of Things—robustness and reliability
- Abstract
- 11.1. Introduction
- 11.2. IoT characteristics and reliability issues
- 11.3. Addressing reliability
- Chapter 12: Governing Internet of Things: issues, approaches, and new paradigms
- Abstract
- 12.1. Introduction
- 12.2. Background and related work
- 12.3. IoT governance
- 12.4. Future research directions
- 12.5. Conclusions
- Chapter 13: TinyTO: two-way authentication for constrained devices in the Internet of Things
- Abstract
- 13.1. Introduction
- 13.2. Security aspects and solutions
- 13.3. Design decisions
- 13.4. TinyTO protocol
- 13.5. Evaluation
- 13.6. Summary
- Acknowledgments
- Chapter 14: Obfuscation and diversification for securing the internet of things (IoT)
- Abstract
- 14.1. Introduction
- 14.2. Distinguishing characteristics of IoT
- 14.3. Obfuscation and diversification techniques
- 14.4. Enhancing the security in IoT using obfuscation and diversification techniques
- 14.5. Different use-case scenarios on software diversification and obfuscation
- 14.6. Conclusions and future work
- Chapter 10: Security and privacy in the Internet of Things
- Part V: IoT applications
- Chapter 15: Applied Internet of Things
- Abstract
- 15.1. Introduction
- 15.2. Scenario
- 15.3. Architecture overview
- 15.4. Sensors
- 15.5. The gateway
- 15.6. Data transmission
- 15.7. Conclusions
- Acknowledgments
- Chapter 16: Internet of Vehicles and applications
- Abstract
- 16.1. Basics of IoV
- 16.2. Characteristics and challenges
- 16.3. Enabling technologies
- 16.4. Applications
- 16.5. Summary and future directions
- Chapter 17: Cloud-Based Smart-Facilities Management
- Abstract
- 17.1. Introduction
- 17.2. Background and related work
- 17.3. A cloud-based architecture for smart-facility management
- 17.4. Middleware services
- 17.5. Resource management techniques for wireless sensor networks
- 17.6. Resource management techniques for supporting data analytics
- 17.7. Case study: management of sensor-based bridges
- 17.8. Case study: research collaboration platform for management of smart machinery
- 17.9. Conclusions
- Acknowledgments
- Chapter 15: Applied Internet of Things
- Index
- Holler, From Machine-to-Machine to the IoTs: Introduction to a New Age of Intelligence, Academic Press, Apr 2014, 336 pages, 9780124076846, $99.95
- Marinescu, Cloud Computing: Theory and Practice, Morgan Kaufmann, May 2013, 416 pages, 9780124046276, $69.95
- Hwang, Distributed and Cloud Computing: From Parallel Processing to the Internet of Things, Morgan Kaufmann, Oct 2011, 672 pages, 9780123858801, $89.95
- Vasseur, Interconnecting Smart Objects with IP, Morgan Kaufmann, Jun 2010, 432 pages, 9780123751652, $77.95
- Li, Xu, and Tryfonas, Security for the Internet of Things, Feb 2017, 224 pages, $49.95
Graduate level Computer Science students studying IoT, sensors network, distributed systems, networks security, cloud computing, and Big Data. IoT practitioners, including network architects, data scientists, computer engineers, and IoT and cloud developers.