Internet of Things
Description
This book addresses researchers and graduate students at the forefront of study/research on the Internet of Things (IoT) by presenting state-of-the-art research together with the current and future challenges in building new smart applications (e.g., Smart Cities, Smart Buildings, and Industrial IoT) in an efficient, scalable, and sustainable way. It covers the main pillars of the IoT world (Connectivity, Interoperability, Discoverability, and Security/Privacy), providing a comprehensive look at the current technologies, procedures, and architectures.
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Persons
SIMONE CIRANI, PHD, is a Co-Founder and Head of IoT at Caligoo Inc., Chicago, IL, USA.
GIANLUIGI FERRARI, PHD, is a Faculty Member at the Department of Engineering and Architecture, at the University of Parma, Italy. He is also Co-founder and President of things2i s.r.l., Parma, Italy.
MARCO PICONE, PHD, is a Co-Founder and Head of Mobile Computing at Caligoo Inc., Chicago, IL, USA.
LUCA VELTRI, PHD, is a Faculty Member at the Department of Engineering and Architecture, at the University of Parma, Italy.
Content
Preface xv
1 Preliminaries, Motivation, and Related Work 1
1.1 What is the Internet of Things? 1
1.2 Wireless Ad-hoc and Sensor Networks:The Ancestors without IP 2
1.3 IoT-enabled Applications 3
1.3.1 Home and Building Automation 3
1.3.2 Smart Cities 4
1.3.3 Smart Grids 4
1.3.4 Industrial IoT 5
1.3.5 Smart Farming 7
2 Standards 9
2.1 "Traditional" Internet Review 9
2.1.1 Physical/Link Layer 10
2.1.1.1 IEEE 802.3 (Ethernet) 11
2.1.1.2 IEEE 802.11 12
2.1.2 Network Layer 14
2.1.2.1 IPv6 and IPv4 14
2.1.3 Transport Layer 17
2.1.3.1 TCP and UDP 19
2.1.4 Application Layer 21
2.1.4.1 HTTP 21
2.1.4.2 AMQP 22
2.1.4.3 SIP 23
2.2 The Internet ofThings 25
2.2.1 Designing the Architecture of an IP-based Internet of Things 26
2.2.2 Physical/Link Layer 28
2.2.2.1 IEEE 802.15.4 and ZigBee 28
2.2.2.2 Low-powerWi-Fi 30
2.2.2.3 Bluetooth and BLE 31
2.2.2.4 Powerline Communications 32
2.2.3 Network Layer 33
2.2.3.1 The 6LoWPAN Adaptation Layer 34
2.2.4 Transport Layer 34
2.2.5 Application Layer 34
2.2.5.1 CoAP 35
2.2.5.2 CoSIP Protocol Specification 60
2.3 The Industrial IoT 76
3 Interoperability 79
3.1 Applications in the IoT 79
3.2 The Verticals: Cloud-based Solutions 80
3.3 REST Architectures:TheWeb of Things 81
3.3.1 REST: TheWeb as a Platform 82
3.3.1.1 Resource-oriented Architectures 83
3.3.1.2 REST Architectures 84
3.3.1.3 Representation of Resources 84
3.3.1.4 Resource Identifiers 85
3.3.1.5 Statelessness 86
3.3.1.6 Applications as Finite-state Machines 86
3.3.1.7 Hypermedia as the Engine of Application State 86
3.3.2 Richardson MaturityModel 88
3.3.2.1 Level 0: the Swamp of POX 88
3.3.2.2 Level 1: Resources 90
3.3.2.3 Level 2: HTTP Verbs 90
3.3.2.4 Level 3: Hypermedia 95
3.3.2.5 The Meaning of the Levels 97
3.4 TheWeb of Things 97
3.5 Messaging Queues and Publish/Subscribe Communications 98
3.5.1 Advantages of the Pub/Sub Model 99
3.5.2 Disadvantages of the Pub/Sub Model 100
3.5.3 Message Queue Telemetry Transport 100
3.5.3.1 MQTT versus AMQP 101
3.6 Session Initiation for the IoT 102
3.6.1 Motivations 102
3.6.2 Lightweight Sessions in the IoT 104
3.6.2.1 A Protocol for Constrained Session Initiation 106
3.6.2.2 Session Initiation 106
3.6.2.3 Session Tear-down 108
3.6.2.4 Session Modification 108
3.7 Performance Evaluation 109
3.7.1 Implementation 109
3.7.2 Experimental Results 111
3.7.3 Conclusions 114
3.8 Optimized Communications: the Dual-network Management Protocol 115
3.8.1 DNMP Motivations 115
3.8.2 RelatedWork 117
3.8.3 The DNMP Protocol 118
3.8.4 Implementation with IEEE 802.15.4 and IEEE 802.11s 123
3.8.4.1 LPLT Networking 123
3.8.4.2 HPHT Networking 123
3.8.4.3 Node Integration 124
3.8.5 Performance Evaluation 125
3.8.5.1 Experimental Setup 125
3.8.5.2 Operational Limitations of IEEE 802.15.4 126
3.8.6 IEEE 802.15.4-controlled Selective Activation of the IEEE 802.11s Network 129
3.8.7 Conclusions 130
3.9 Discoverability in Constrained Environments 131
3.9.1 CoRE Link Format 131
3.9.1.1 CoRE Link Format: Discovery 132
3.9.1.2 Link Format 133
3.9.1.3 The Interface Description Attribute 135
3.9.2 CoRE Interfaces 135
3.9.2.1 Sensor 136
3.9.2.2 Parameter 137
3.9.2.3 Read-only Parameter 137
3.9.2.4 Actuator 137
3.10 Data Formats: Media Types for Sensor Markup Language 138
3.10.1 JSON Representations 141
3.10.1.1 Single Datapoint 141
3.10.1.2 Multiple Datapoints 142
3.10.1.3 Multiple Measurements 142
4 Discoverability 145
4.1 Service and Resource Discovery 145
4.2 Local and Large-scale Service Discovery 146
4.2.1 ZeroConf 151
4.2.2 UPnP 152
4.2.3 URI Beacons and the PhysicalWeb 152
4.3 Scalable and Self-configuring Architecture for Service Discovery in the IoT 154
4.3.1 IoT Gateway 156
4.3.1.1 Proxy Functionality 156
4.3.1.2 Service and Resource Discovery 158
4.3.2 A P2P-based Large-scale Service Discovery Architecture 159
4.3.2.1 Distributed Location Service 160
4.3.2.2 Distributed Geographic Table 161
4.3.2.3 An Architecture for Large-scale Service Discovery based on Peer-to-peer Technologies 162
4.3.3 Zeroconf-based Local Service Discovery for Constrained Environments 167
4.3.3.1 Architecture 167
4.3.3.2 Service Discovery Protocol 168
4.3.4 Implementation Results 170
4.3.4.1 Local Service Discovery 171
4.3.4.2 Large-scale Service Discovery 175
4.4 Lightweight Service Discovery in Low-power IoT Networks 178
4.4.1 Efficient Forwarding Protocol for Service Discovery 180
4.4.1.1 Multicast through Local Filtered Flooding 181
4.4.2 Efficient Multiple Unicast Forwarding 183
4.5 Implementation Results 185
5 Security and Privacy in the IoT 191
5.1 Security Issues in the IoT 192
5.2 Security Mechanisms Overview 196
5.2.1 Traditional vs Lightweight security 196
5.2.1.1 Network Layer 197
5.2.1.2 Transport Layer 199
5.2.1.3 Application Layer 201
5.2.2 Lightweight Cryptography 202
5.2.2.1 Symmetric-key LWC Algorithms 203
5.2.2.2 Public-key (Asymmetric) LWC Algorithms 206
5.2.2.3 Lightweight Cryptographic Hash Functions 210
5.2.2.4 Homomorphic Encryption Schemes 213
5.2.3 Key Agreement, Distribution, and Security Bootstrapping 214
5.2.3.1 Key Agreement Protocols 215
5.2.3.2 Shared Group-key Distribution 215
5.2.3.3 Security Bootstrapping 216
5.2.4 Processing Data in the Encrypted Domain: Secure Data Aggregation 217
5.2.5 Authorization Mechanisms for Secure IoT Services 219
5.3 Privacy Issues in the IoT 222
5.3.1 The Role of Authorization 222
5.3.2 IoT-OAS: Delegation-based Authorization for the Internet of Things 227
5.3.2.1 Architecture 227
5.3.2.2 Granting Access Tokens 229
5.3.2.3 Authorizing Requests 231
5.3.2.4 SP-to-IoT-OAS Communication: Protocol Details 231
5.3.2.5 Configuration 232
5.3.3 IoT-OAS Application Scenarios 232
5.3.3.1 Network Broker Communication 233
5.3.3.2 Gateway-based Communication 235
5.3.3.3 End-to-End CoAP Communication 235
5.3.3.4 Hybrid Gateway-based Communication 235
6 Cloud and Fog Computing for the IoT 237
6.1 Cloud Computing 237
6.2 Big Data Processing Pattern 238
6.3 Big Stream 239
6.3.1 Big-stream-oriented Architecture 243
6.3.2 Graph-based Processing 247
6.3.3 Implementation 251
6.3.3.1 Acquisition Module 251
6.3.3.2 Normalization Module 253
6.3.3.3 Graph Framework 254
6.3.3.4 Application Register Module 255
6.3.4 Performance Evaluation 257
6.3.5 Solutions and Security Considerations 262
6.4 Big Stream and Security 263
6.4.1 Graph-based Cloud System Security 266
6.4.2 Normalization after a Secure Stream Acquisition with OFS Module 268
6.4.3 Enhancing the Application Register with the IGS Module 269
6.4.4 Securing Streams inside Graph Nodes 273
6.4.5 Evaluation of a Secure Big Stream Architecture 277
6.5 Fog Computing and the IoT 281
6.6 The Role of the IoTHub 283
6.6.1 Virtualization and Replication 285
6.6.1.1 The IoT Hub 285
6.6.1.2 Operational Scenarios 287
6.6.1.3 Synchronization Protocol 290
7 The IoT in Practice 303
7.1 Hardware for the IoT 303
7.1.1 Classes of Constrained Devices 305
7.1.2 Hardware Platforms 307
7.1.2.1 TelosB 307
7.1.2.2 Zolertia Z1 307
7.1.2.3 OpenMote 310
7.1.2.4 Arduino 313
7.1.2.5 Intel Galileo 315
7.1.2.6 Raspberry Pi 318
7.2 Software for the IoT 321
7.2.1 OpenWSN 321
7.2.2 TinyOS 322
7.2.3 FreeRTOS 323
7.2.4 TI-RTOS 323
7.2.5 RIOT 324
7.2.6 Contiki OS 325
7.2.6.1 Networking 325
7.2.6.2 Low-power Operation 326
7.2.6.3 Simulation 326
7.2.6.4 Programming Model 327
7.2.6.5 Features 328
7.3 Vision and Architecture of a Testbed for theWeb of Things 328
7.3.1 An All-IP-based Infrastructure for Smart Objects 330
7.3.2 Enabling Interactions with Smart Objects through the IoT Hub 332
7.3.2.1 Integration Challenges 334
7.3.3 Testbed Access and Security 335
7.3.3.1 The Role of Authorization 335
7.3.4 Exploiting the Testbed:WoT Applications for Mobile and Wearable Devices 336
7.3.5 Open Challenges and Future Vision 338
7.4 Wearable Computing for the IoT: Interaction Patterns with Smart Objects in RESTful Environments 340
7.4.1 Shaping the Internet ofThings in a Mobile-Centric World 340
7.4.2 Interaction Patterns with Smart Objects throughWearable Devices 342
7.4.2.1 Smart Object Communication Principles 342
7.4.2.2 Interaction Patterns 343
7.4.3 Implementation in a Real-world IoT Testbed 345
7.4.3.1 Future Vision: towards the Tactile Internet 348
7.5 Effective Authorization for theWeb ofThings 349
7.5.1 Authorization Framework Architecture 353
7.5.1.1 System Operations 353
7.5.2 Implementation and Validation 357
Reference 359
Index 381
1
Preliminaries, Motivation, and Related Work
1.1 What is the Internet of Things?
The Internet of Things (IoT) encapsulates a vision of a world in which billions of objects with embedded intelligence, communication means, and sensing and actuation capabilities will connect over IP (Internet Protocol) networks. Our current Internet has undergone a fundamental transition, from hardware-driven (computers, fibers, and Ethernet cables) to market-driven (Facebook, Amazon) opportunities. This has come about due to the interconnection of seamingly disjoint intranets with strong horizontal software capabilities. The IoT calls for open environments and an integrated architecture of interoperable platforms. Smart objects and cyber-physical systems - or just "things" - are the new IoT entities: the objects of everyday life, augmented with micro-controllers, optical and/or radio transceivers, sensors, actuators, and protocol stacks suitable for communication in constrained environments where target hardware has limited resources, allowing them to gather data from the environment and act upon it, and giving them an interface to the physical world. These objects can be worn by users or deployed in the environment. They are usually highly constrained, with limited memory and available energy stores, and they are subject to stringent low-cost requirements. Data storage, processing, and analytics are fundamental requirements, necessary to enrich the raw IoT data and transform them into useful information. According to the "Edge Computing" paradigm, introducing computing resources at the edge of access networks may bring several benefits that are key for IoT scenarios: low latency, real-time capabilities and context-awareness. Edge nodes (servers or micro data-centers on the edge) may act as an interface to data streams coming from connected devices, objects, and applications. The stored Big Data can then be processed with new mechanisms, such as machine and deep learning, transforming raw data generated by connected objects into useful information. The useful information will then be disseminated to relevant devices and interested users or stored for further processing and access.
1.2 Wireless Ad-hoc and Sensor Networks: The Ancestors without IP
Wireless sensor networks (WSNs) were an emerging application field of microelectronics and communications in the first decade of the twenty-first century. In particular, WSNs promised wide support of interactions between people and their surroundings. The potential of a WSN can be seen in the three words behind the acronym:
- "Wireless" puts the focus on the freedom that the elimination of wires gives, in terms of mobility support and ease of system deployment;
- "Sensor" reflects the capability of sensing technology to provide the means to perceive and interact - in a wide sense - with the world;
- "Networks" gives emphasis to the possibility of building systems whose functional capabilities are given by a plurality of communicating devices, possibly distributed over large areas.
Pushed on by early military research, WSNs were different from traditional networks in terms of the communication paradigm: the address-centric approach used in end-to-end transmissions between specific devices, with explicit indication of both source and destination addresses in each packet, was to be replaced with an alternative (and somewhat new) data-centric approach. This "address blindness" led to the selection of a suitable data diffusion strategy - in other words, communication protocol - for data-centric networks. The typical network deployment would consist of the sources placed around the areas to be monitored and the sinks located in easily accessible places. The sinks provided adequate storage capacity to hold the data from the sources. Sources might send information to sinks in accordance with different scheduling policies: periodic (i.e., time-driven), event specific (i.e., event-driven), a reply in response to requests coming from sinks (i.e., query-driven), or some combination thereof.
Because research focused on the area, WSNs have typically been associated with ad-hoc networks, to the point that the two terms have almost become - although erroneously so - synonymous. In particular, ad-hoc networks are defined as general, infrastructure-less, cooperation-based, opportunistic networks, typically customized for specific scenarios and applications. These kinds of networks have to face frequent and random variations of many factors (radio channel, topology, data traffic, and so on), implying a need for dynamic management of a large number of parameters in the most efficient, effective, and reactive way. To this end, a number of key research problems have been studied, and solutions proposed, in the literature:
- self-configuration and self-organization in infrastructure-less systems;
- support for cooperative operations in systems with heterogenous members;
- multi-hop peer-to-peer communication among network nodes, with effective routing protocols;
- network self-healing behavior providing a sufficient degree of robustness and reliability;
- seamless mobility management and support of dynamic network topologies.
1.3 IoT-enabled Applications
The IoT touches every facet of our lives. IoT-enabled applications are found in a large number of scenarios, including: home and building automation, smart cities, smart grids, Industry 4.0, and smart agriculture. In each of these areas, the use of a common (IP-oriented) communication protocol stack allows the building of innovative applications. In this section, we provide a concise overview of potential applications in each of these areas.
1.3.1 Home and Building Automation
As the smart home market has seen growing investment and has continued to mature, ever more home automation applications have appeared, each designed for a specific audience. The result has been the creation of several disconnected vertical market segments. Typical examples of increasingly mainstream applications are related to home security and energy efficiency and energy saving. Pushed by the innovations in light and room control, the IoT will foster the development of endless applications for home automation. For example, a typical example of an area of home automation that is destined to grow in the context of the IoT is in healthcare, namely IoT-enabled solutions for the physically less mobile (among others, the elderly, particulary relevant against a background of aging populations), and for the disabled or chronically ill (for instance, remote health monitoring and air-quality monitoring). In general, building automation solutions are starting to converge and are also moving, from the current applications in luxury, security and comfort, to a wider range of applications and connected solutions; this will create market opportunities. While today's smart home solutions are fragmented, the IoT is expected to lead to a new level of interoperability between commercial home and building automation solutions.
1.3.2 Smart Cities
Cities are complex ecosystems, where quality of life is an important concern. In such urban environments, people, companies and public authorities experience specific needs and demands in domains such as healthcare, media, energy and the environment, safety, and public services. A city is perceived more and more as being like a single "organism", which needs to be efficiently monitored to provide citizens with accurate information. IoT technologies are fundamental to collecting data on the city status and disseminating them to citizens. In this context, cities and urban areas represent a critical mass when it comes to shaping the demand for advanced IoT-based services.
1.3.3 Smart Grids
A smart grid is an electrical grid that includes a variety of operational systems, including smart meters, smart appliances, renewable energy resources, and energy-efficient resources. Power line communications (PLC) relate to the use of existing electrical cables to transport data and have been investigated for a long time. Power utilities have been using this technology for many years to send or receive (limited amounts of) data on the existing power grid. Although PLC is mostly limited by the type of propagation medium, it can use existing wiring in the distribution network. According to EU's standards and laws, electrical utility companies can use PLC for low bit-rate data transfers (with data rates lower than 50 Kbps) in the 3-148 kHz frequency band. This technology opens up new opportunities and new forms of interactions among people and things in many application areas, such as smart metering services and energy consumption reporting. This makes PLC an enabler for sensing, control, and automation in large systems spread over relatively wide areas, such as in the smart city and smart grid scenarios. On top of PLC, one can also adopt enabling technologies that can improve smart automation processes, such as the IoT. For instance, the adoption of the PLC technology in industrial scenarios (e.g., remote control in automation and manufacturing companies), paves the way to the "Industrial IoT". Several applications have...
