Internet of Things. Principles and Paradigms

Description

Cover Title Page Copyright Page Contents List of Contributors About the Editors Preface Organization of the book Acknowledgments Part I - IoT Ecosystem concepts and architectures Chapter 1 - Internet of Things: an overview 1.1 - Introduction 1.2 - Internet of Things definition evolution 1.2.1 - IoT emergence 1.2.2 - Internet of Everything 1.2.3 - Industrial IoT 1.2.4 - Smartness in IoT 1.2.5 - Market share 1.2.6 - Human in the loop 1.2.7 - Improving the quality of life 1.3 - IoT architectures 1.3.1 - SOA-based architecture 1.3.2 - API-oriented architecture 1.4 - Resource management 1.4.1 - Resource partitioning 1.4.2 - Computation offloading 1.4.3 - Identification and resource/service discovery 1.5 - IoT data management and analytics 1.5.1 - IoT and the Cloud 1.5.2 - Real-time analytics in IoT and Fog Computing 1.6 - Communication protocols 1.6.1 - Network layer 1.6.2 - Transport and application layer 1.7 - Internet of Things applications 1.7.1 - Monitoring and actuating 1.7.2 - Business process and data analysis 1.7.3 - Information gathering and collaborative consumption 1.8 - Security 1.9 - Identity management and authentication 1.10 - Privacy 1.11 - Standardization and regulatory limitations 1.12 - Conclusions References Chapter 2 - Open source semantic web infrastructure for managing IoT resources in the Cloud 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 References Chapter 3 - Device/Cloud collaboration framework for intelligence applications 3.1 - Introduction 3.2 - Background and related work 3.3 - Device/Cloud collaboration framework 3.3.1 - Powerful smart mobile devices 3.3.2 - Runtime Adaptation Engine 3.3.3 - Privacy-protection solution 3.4 - Applications of Device/Cloud collaboration 3.4.1 - Context-aware Proactive Suggestion 3.4.2 - Semantic QA cache 3.4.3 - Image and speech recognition 3.5 - Future work 3.6 - Conclusions Acknowledgments References Chapter 4 - Fog Computing: principles, architectures, and applications 4.1 - Introduction 4.2 - MotivatiNG scenario 4.3 - Definitions and characteristics 4.4 - Reference architecture 4.5 - Applications 4.5.1 - Healthcare 4.5.2 - Augmented reality 4.5.3 - Caching and preprocessing 4.6 - Research directions and enablers 4.6.1 - Programming models 4.6.2 - Security and reliability 4.6.3 - Resource management 4.6.4 - Energy minimization 4.7 - Commercial products 4.7.1 - Cisco IOx 4.7.2 - Data in motion 4.7.3 - LocalGrid 4.7.4 - ParStream 4.7.5 - Prismtech Vortex 4.8 - Case study 4.8.1 - Experiment setup 4.8.1.1 - Network Topology and Data Sources 4.8.2 - Performance evaluation 4.8.2.1 - Average Tuple Delay 4.8.2.2 - Core Network Usage 4.9 - Conclusions References Part II - IoT Enablersand solutions Chapter 5 - Programming frameworks for Internet of Things 5.1 - Introduction 5.2 - Background 5.2.1 - Overview 5.2.2 - Embedded device programming languages 5.2.2.1 - nesC 5.2.2.2 - Keil C 5.2.2.3 - Dynamic C 5.2.2.4 - B# 5.2.3 - Message passing in devices 5.2.3.1 - RPC 5.2.3.2 - REST 5.2.3.3 - CoAP 5.2.4 - Coordination languages 5.2.4.1 - Linda and eLinda 5.2.4.2 - Orc 5.2.4.3 - Jolie 5.2.5 - Polyglot programming 5.3 - Survey of IoT programming frameworks 5.3.1 - Overview 5.3.2 - IoT programming approaches 5.3.3 - Existing IoT frameworks 5.3.3.1 - Mobile Fog 5.3.3.2 - ELIoT (Erlang Language for IoT) 5.3.3.3 - Compose API 5.3.3.4 - Distributed Dataflow Support for IoT 5.3.3.5 - PyoT 5.3.3.6 - Dripcast 5.3.3.7 - Calvin 5.3.3.8 - Simurgh 5.3.3.9 - High-Level Application Development for the Internet of Things 5.3.3.10 - PatRICIA 5.3.4 - Summary 5.4 - Future research directions 5.5 - Conclusions References Chapter 6 - Virtualization on embedded boards as enabling technology for the Cloud of Things 6.1 - Introduction 6.2 - Background 6.2.1 - ARM virtualization extensions 6.2.2 - XEN ARM virtualization 6.2.3 - KVM ARM virtualization 6.2.4 - Container-based virtualization 6.3 - Virtualization and real-time 6.4 - Experimental results 6.4.1 - Reference architecture 6.4.2 - Benchmarking tools 6.4.3 - Discussion 6.4.3.1 - CPU Performance Analysis 6.4.3.2 - Memory Performance Analysis 6.4.3.3 - Memory Footprint Analysis 6.4.3.4 - I/O Performance Analysis 6.4.3.5 - Network Performance Analysis 6.5 - Future research directions 6.6 - Conclusions References Chapter 7 - Micro Virtual Machines (MicroVMs) for Cloud-assisted Cyber-Physical Systems (CPS) 7.1 - Introduction 7.2 - Related work 7.2.1 - Virtual machines and Micro Virtual Machines 7.2.2 - Other architectures 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 7.5.1 - Virtual machines and Sensor Observation Service 7.5.2 - Implementation 7.6 - IoT architecture for selected use cases 7.6.1 - eHealth 7.6.2 - Precision Agriculture 7.6.3 - Domotic 7.7 - Future research directions 7.8 - Conclusions References Part III - IoT Data andknowledgemanagement Chapter 8 - Stream processing in IoT: foundations, state-of-the-art, and future directions 8.1 - Introduction 8.2 - The foundations of stream processing in IoT 8.2.1 - Stream 8.2.2 - Stream processing 8.2.3 - The Characteristics of stream data in IoT 8.2.3.1 - Timeliness and Instantaneity 8.2.3.2 - Randomness and Imperfection 8.2.3.3 - Endlessness and Continuousness 8.2.3.4 - Volatility and Unrepeatability 8.2.4 - The general architecture of a stream-processing system in IoT 8.3 - Continuous Logic Processing System 8.4 - Challenges and future directions 8.4.1 - Scalability 8.4.2 - Robustness 8.4.3 - SLA-compliance 8.4.4 - Load balancing 8.5 - Conclusions References Chapter 9 - A framework for distributed data analysis for IoT 9.1 - Introduction 9.2 - Preliminaries 9.3 - Anomaly detection 9.4 - Problem statement and definitions 9.4.1 - Hyperellipsoidal anomaly detection 9.5 - Distributed anomaly detection 9.5.1 - Clustering ellipsoids 9.5.2 - Experimental results 9.6 - Efficient incremental local modeling 9.6.1 - Incremental updates 9.6.2 - Implementation of incremental updates 9.6.3 - Experimental results 9.7 - Summary References Part IV - IoT Reliability,security, andprivacy Chapter 10 - Security and privacy in the Internet of Things 10.1 - Concepts 10.1.1 - IoT reference model 10.1.2 - IoT security threats 10.1.3 - IoT security requirements 10.1.3.1 - Scale 10.1.3.2 - IP Protocol-Based IoT 10.1.3.3 - Heterogeneous IoT 10.1.3.4 - Lightweight Security 10.2 - IoT security overview 10.2.1 - IoT protocols 10.2.2 - Network and transport layer challenges 10.2.3 - IoT gateways and security 10.2.4 - IoT routing attacks 10.2.5 - Bootstrapping and authentication 10.2.6 - Authorization mechanisms 10.2.6.1 - Resource Owner 10.2.6.2 - Resource Server (Service Provider, SP) 10.2.6.3 - Client (Service Consumer, SC) 10.2.6.4 - Authorization Server 10.2.7 - IoT OAS 10.3 - Security frameworks for IoT 10.3.1 - Light weight cryptography 10.3.1.1 - Symmetric-Key LWC Algorithms 10.3.2 - Asymmetric LWC algorithms 10.3.3 - Key agreement, distribution, and bootstrapping 10.3.3.1 - Security Bootstrapping 10.4 - Privacy in IoT networks 10.4.1 - Secure data aggregation 10.4.2 - Enigma 10.4.3 - Zero knowledge protocols 10.4.4 - Privacy in beacons 10.5 - Summary and conclusions References Chapter 11 - Internet of Things—robustness and reliability 11.1 - Introduction 11.2 - IoT characteristics and reliability issues 11.2.1 - IoT architecture in brief 11.2.1.1 - Different Categories of Applications 11.2.1.1.1 - Zero tolerance 11.2.1.1.2 - Restartable 11.2.1.1.3 - Error Tolerant 11.2.2 - Failure scenarios 11.2.2.1 - Infrastructure Fault 11.2.2.2 - Interaction Fault 11.2.2.3 - Fault in Service Platform 11.2.3 - Reliability challenges 11.2.3.1 - Making Service Available to User 11.2.3.2 - Serviceability of IoT System 11.2.3.3 - Reliability at Network Level 11.2.3.4 - Device Level Reliability 11.2.4 - Privacy and reliability 11.2.5 - Interoperability of devices 11.2.6 - Reliability issues due to energy constraint 11.3 - Addressing reliability 11.3.1 - Nullifying impact of fault 11.3.1.1 - Redundancy in Service Platform Design 11.3.1.2 - Redundancy in M2M Topology 11.3.1.3 - Graceful Degradation 11.3.1.3.1 - Software Design 11.3.1.3.2 - Performability Model 11.3.2 - Error detection 11.3.2.1 - Watchdog 11.3.2.2 - Heartbeat 11.3.2.3 - Exception Handling 11.3.2.4 - Recovery Through Restart 11.3.3 - Fault prevention 11.3.3.1 - Failure Prediction 11.3.3.2 - Improving Communication Reliability 11.3.3.2.1 - Service Degradation Support 11.3.3.3 - Failure Prevention by Service Platform 11.3.3.4 - Improving Energy Efficiency 11.3.3.4.1 - Device Power Management 11.3.3.4.2 - Communication Power Management 11.3.3.4.3 - Service Platform 11.3.3.4.3.1 - Data Quality vs Energy Usage References Chapter 12 - Governing Internet of Things: issues, approaches, and new paradigms 12.1 - Introduction 12.2 - Background and related work 12.2.1 - Overview 12.2.2 - Background 12.2.2.1 - Governance 12.2.2.2 - Internet Governance 12.2.2.3 - Enterprise Network Management 12.2.2.4 - Management Versus Governance 12.2.2.5 - Surveillance and Internet of Things 12.2.3 - Related work 12.3 - IoT governance 12.3.1 - Overview 12.3.2 - An integrated governance idea 12.3.3 - Governance models 12.3.4 - Important governance issues 12.3.5 - Existing approaches 12.3.6 - New paradigms 12.4 - Future research directions 12.5 - Conclusions References Chapter 13 - TinyTO: two-way authentication for constrained devices in the Internet of Things 13.1 - Introduction 13.2 - Security aspects and solutions 13.3 - Design decisions 13.4 - TinyTO protocol 13.4.1 - Possible handshake protocol candidates 13.4.2 - BCK with preshared keys for TinyTO 13.4.3 - Handshake implementation 13.5 - Evaluation 13.5.1 - Memory consumption 13.5.2 - Runtime performance 13.5.3 - Energy consumption 13.6 - Summary Acknowledgments References Chapter 14 - Obfuscation and diversification for securing the internet of things (IoT) 14.1 - Introduction 14.2 - Distinguishing characteristics of IoT 14.2.1 - Operating systems and software in IoT 14.2.2 - IoT network stack and access protocols 14.2.3 - Security and privacy in IoT 14.3 - Obfuscation and diversification techniques 14.4 - Enhancing the security in IoT using obfuscation and diversification techniques 14.4.1 - Motivations and limitations of the proposed ideas 14.5 - Different use-case scenarios on software diversification and obfuscation 14.6 - Conclusions and future work References Part V - IoT Applications Chapter 15 - Applied Internet of Things 15.1 - Introduction 15.2 - Scenario 15.3 - Architecture overview 15.3.1 - Sensor to gateway communication 15.3.1.1 - Wired Gateway Interfaces 15.3.1.2 - Wireless Gateway Interfaces 15.4 - Sensors 15.5 - The gateway 15.5.1 - Gateway hardware 15.5.2 - Gateway software 15.5.3 - Summary 15.6 - Data transmission 15.6.1 - Advanced Message Queuing Protocol 15.6.2 - Backend processing 15.6.2.1 - Overview 15.6.2.2 - Data Processing Framework 15.6.3 - To Cloud or not to Cloud 15.7 - Conclusions Acknowledgments References Chapter 16 - Internet of Vehicles and applications 16.1 - Basics of IoV 16.1.1 - Background and concept 16.1.2 - Network architecture 16.1.2.1 - Vehicles in IoV 16.1.2.2 - Connections in IoV 16.1.2.3 - Servers/Clouds in IoV 16.2 - Characteristics and challenges 16.2.1 - Characteristics of IoV 16.2.2 - Challenges in IoV 16.3 - Enabling technologies 16.3.1 - MAC protocols and standards 16.3.1.1 - IEEE 802.11 16.3.1.2 - IEEE 802.11p/WAVE 16.3.2 - Routing protocols 16.3.2.1 - AODV 16.3.2.2 - OLSR 16.3.2.3 - Multihop-MAC Protocol (IEEE 802.11s) 16.3.3 - Broadcasting and information dissemination 16.3.3.1 - V2V Based 16.3.3.2 - V2R Based 16.3.3.3 - DTN Based 16.4 - Applications 16.4.1 - Driving safety related 16.4.2 - Transportation efficiency related 16.4.2.1 - Intersection Control 16.4.2.2 - Route Navigation 16.4.2.3 - Parking Navigation 16.4.2.4 - Cooperative Driving 16.4.3 - Infotainment services 16.5 - Summary and future directions References Chapter 17 - Cloud-Based Smart-Facilities Management 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 17.5.1 - Sensor allocation 17.5.2 Request scheduling 17.6 - Resource management techniques for supporting data analytics 17.6.1 - Streaming 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 17.9.1 - Future research directions Acknowledgments References Index Back cover