Front Cover 1
Machine-to-machine (M2M) Communications: Achitecture, PerformanceandApplications 4
Copyright 5
Contents 6
List of contributors 12
Woodhead Publishing Series in Electronic and Optical Materials 14
Chapter 1: Introduction to machine-to-machine (M2M) communications 18
1.1. Introducing machine-to-machine 18
1.1.1. Machine-to-machine and the big data opportunity 18
1.1.2. Machine-to-machine technology landscape 21
1.1.3. Cellular M2M requirements 22
1.2. The machine-to-machine market opportunity 22
1.2.1. Return-of-investment (ROI) argumentation 22
1.2.2. Market overview 24
1.2.3. Market challenges and opportunities 27
1.3. Examples of commercial and experimental M2M network rollouts 28
1.3.1. Commercial rollouts 28
1.3.2. Pilots and field trials 30
1.4. Machine-to-machine standards and initiatives 31
1.4.1. Standards development organizations 31
1.4.2. Industrial associations and special interest groups (SIGs) 34
1.4.3. Global industrial M2M initiatives 35
1.4.4. International innovation projects on M2M 35
1.5. Book rationale and overview 37
Part One: Architectures and standards 42
Chapter 2: Overview of ETSI machine-to-machine and oneM2M architectures 44
2.1. Introduction 44
2.2. Need and rationale for M2M standards 44
2.3. Standardized M2M architecture 48
2.4. Using M2M standards for ``vertical´´ domains, the example of the smart home 53
2.5. Conclusions and future trends for M2M standardization 60
References 62
Chapter 3: Overview of 3GPP machine-type communication standardization 64
3.1. Introduction 64
3.2. Pros and cons of M2M over cellular 65
3.2.1. Advantages of using cellular M2M 65
3.2.2. Challenges to facilitate cellular M2M 66
3.2.3. Suitability of current cellular solutions 67
3.3. MTC standardization in 3GPP 68
3.3.1. Technical requirements 68
3.3.1.1. The need for MTC user identification 68
3.3.1.2. The need for coverage improvement 69
3.3.1.3. Service exposure and enablement support 70
3.3.2. 3GPP MTC-related releases 70
3.3.3. MTC feature enhancements 72
3.3.3.1. Overload and congestion control at core network and RAN 72
3.3.3.2. Low-cost and enhanced coverage MTC UE for LTE 73
3.3.3.3. Other enhancements 73
3.4. Concluding remarks 74
References 76
Chapter 4: Lower-power wireless mesh networks for machine-to-machine communications using the IEEE802.15.4 standard 80
4.1. Introduction 80
4.2. The origins 80
4.2.1. Early low-power technologies 80
4.2.2. First demonstrations 81
4.2.3. IEEE802.15.4, the foundation 82
4.3. Challenges of low-power mesh networking 83
4.3.1. The unreliable nature of wireless 83
4.3.2. Low-power operation 85
4.3.3. Protocol considerations 85
4.4. The past 86
4.4.1. Proprietary solutions 86
4.4.2. ZigBee 86
4.4.3. Time synchronized mesh protocol 86
4.5. The present 87
4.5.1. Reliability, reliability, reliability 87
4.5.2. Industrial-grade standards 88
4.5.3. Internet integration 90
4.6. The future 91
4.6.1. Today's challenges 91
4.6.2. IETF 6TiSCH: combining IPv6 connectivity with industrial performance 91
4.6.3. Toward hybrid systems 92
4.7. Conclusion 92
Acknowledgments 93
References 93
Chapter 5: M2M interworking technologies and underlying market considerations 96
5.1. Interworking technologies for M2M communication networks: introduction 96
5.2. A panorama of heterogeneous technologies 96
5.2.1. Three-level architecture with non-IP devices 97
5.2.2. Two-level architecture with IP-enabled devices 98
5.2.3. Two-level architecture with non-IP devices 99
5.3. From capillary to IP networks 99
5.3.1. The gap between IP and capillary networks 99
5.3.2. The big IP funnel 100
5.4. Going up to the M2M cloud 101
5.4.1. Enabling M2M data exchange with web services 101
5.4.2. RESTful web services 101
5.4.3. MQTT 102
5.4.4. CoAP 103
5.4.5. XMPP 103
5.5. M2M market as internetworking enabler 104
5.5.1. Market actors 104
5.5.2. Preliminary CAPEX and OPEX considerations 105
5.5.3. The role of traditional operators 105
5.5.4. New M2M operators 105
5.5.5. M2M hardware vendors 106
5.5.6. M2M cloud/middleware and software application providers 107
5.6. Future trends 108
References 109
Chapter 6: Weightless machine-to-machine (M2M) wireless technology using TV white space: developing a standard 110
6.1. Why a new standard is needed 110
6.2. The need for spectrum 111
6.3. TV white space as a solution 112
6.4. Designing a new technology to fit M2M and white space 114
6.5. Weightless: the standard designed for M2M in shared spectrum 117
6.5.1. Applications 118
6.5.2. Security 119
6.5.3. MAC 119
6.5.4. PHY 120
6.6. Establishing a standards body 121
6.7. Conclusions 124
References 124
Chapter 7: Supporting machine-to-machine communications in long-term evolution networks 126
7.1. Introduction to M2M in LTE 126
7.2. Main technical challenges and existing solutions 127
7.2.1. Handling a very large number of devices 127
7.2.2. Low-energy-consumption solutions for MTC 129
7.2.3. Supporting low-cost MTC UEs 129
7.2.4. Providing extended coverage for MTC devices 131
7.3. Integrating MTC traffic into a human-centric system: a techno-economic perspective 132
7.3.1. The impact of a larger number of devices 133
7.3.2. The integration of LTE and capillary networks as a scalable solution 133
7.3.2.1. Overview of capillary networks 134
7.3.2.2. Techno-economic view on capillary networks 136
7.3.3. Technology migration and deployment strategies 136
7.4. Business implications for MTC in LTE 138
7.4.1. Is there a need for a change in operators' mindset? 139
7.4.2. The relationship between business challenges and engineers 139
7.4.3. Business models for M2M 141
7.5. Conclusions 143
Acknowledgments 144
References 144
Part Two: Access, scheduling, mobility and security protocols 148
Chapter 8: Traffic models for machine-to-machine (M2M) communications 150
8.1. Introduction 150
8.2. Generic methodology for traffic modeling 152
8.2.1. Trace recording 153
8.2.2. Traffic modeling 154
8.3. M2M traffic modeling 155
8.3.1. Use case: fleet management 156
8.3.2. Source traffic modeling 157
8.3.2.1. M2M traffic states 157
8.3.2.2. Source modeling via semi-Markov models 158
8.3.3. Aggregated traffic modeling 159
8.3.4. Source modeling for coordinated traffic via Markov-modulated Poisson processes 161
8.3.4.1. MMPPs: the basics 162
8.3.4.2. Coupling multiple MMPP processes 162
8.4. Model fitting from recorded traffic 164
8.4.1. B1: modeling individual devices as Markov chains 164
8.4.2. B2: modeling aggregated traffic 166
8.4.3. B3: modeling single Markov states 168
8.5. Conclusions 169
References 170
Chapter 9: Random access procedures and radio access network (RAN) overload control in standard and advanced long-term ev... 172
9.1. Introduction 172
9.2. E-UTRAN access reservation protocol 175
9.2.1. Random access preamble 175
9.2.2. Random access response 177
9.2.3. RRC connection request 178
9.2.4. Contention resolution 179
9.3. Extended access barring protocol 179
9.4. Alternative E-UTRAN load control principles 180
9.5. Overview of core network challenges and solutions for load control 181
9.6. Ongoing 3GPP work on load control 183
9.7. Resilience to overload through protocol re-engineering 184
9.8. Conclusion 187
Acknowledgments 187
References 187
Chapter 10: Packet scheduling strategies for machine-to-machine (M2M) communications over long-term evolution (LTE) cellu... 190
10.1. State of the art in M2M multiple access in legacy cellular systems 190
10.2. Signaling and scheduling limitations for M2M over LTE 191
10.2.1. Signaling in LTE scheduling 192
10.2.2. The LTE scheduling framework 193
10.3. Existing approaches for M2M scheduling over LTE 195
10.3.1. Group-based scheduling 195
10.3.2. Time granularity of scheduling 195
10.4. Novel approaches for M2M scheduling over LTE 196
10.4.1. QoS classes and LTE scheduling 196
10.4.2. Low-complexity scheduling and M2M bandwidth estimation 198
10.5. Technology innovations and challenges for M2M scheduling over wireless networks beyond 2020 200
10.5.1. Hybrid contention/reservation multiple access protocol for future M2M over cellular systems 201
10.6. Conclusions 202
References 202
Chapter 11: Mobility management for machine-to-machine (M2M) communications 204
11.1. Introduction 204
11.2. Use cases for M2M mobility 206
11.2.1. eHealth 207
11.2.2. Transportation 208
11.2.3. Smart buildings 208
11.3. Challenges of M2M mobility 209
11.4. Infrastructure considerations for mobility in M2M 210
11.4.1. Overview of M2M network reference architecture by standard organizations 210
11.4.1.1. IEEE 802 LAN/MAN standards 211
11.4.1.2. 3GPP MTC reference architecture 211
11.4.1.3. ETSI M2M reference architecture 211
11.4.1.4. oneM2M 212
11.4.2. Managing mobility with 3GPP EPC 213
11.4.3. Software-defined networks 215
11.4.4. Management and control of M2M devices 216
11.5. State-of-the-art solutions 217
11.5.1. Mobility support for IPv6 217
11.5.2. Cognitive M2M communication 218
11.5.3. Delay-tolerant networking 219
11.6. Summary and conclusions 219
Acknowledgments 220
References 220
Chapter 12: Advanced security taxonomy for machine-to-machine (M2M) communications in 5G capillary networks 224
12.1. Introduction 224
12.2. System architecture 226
12.2.1. Centralized architecture 227
12.2.2. Hierarchical architecture 227
12.2.3. Flat architecture 227
12.2.4. Security analysis 228
12.3. System assets 228
12.3.1. Binary data 229
12.3.2. Logical infrastructure 229
12.3.3. Device components 229
12.3.4. Security analysis 229
12.4. Security threats 229
12.4.1. Leak of service 230
12.4.2. Falsification of service 230
12.4.3. Denial of service 231
12.4.4. Time of service 231
12.4.5. Security analysis 231
12.5. Types of attacks 232
12.5.1. Ability 232
12.5.2. Activity 232
12.5.3. Class 232
12.5.4. Security analysis 233
12.6. Layers under attack 233
12.6.1. L0 hardware 233
12.6.2. L1 PHY layer 234
12.6.3. L2 MAC layer 235
12.6.4. L3 NTW layer 235
12.6.5. Security analysis 236
12.7. Security services 236
12.7.1. Confidentiality 236
12.7.2. Integrity 236
12.7.3. Availability 237
12.7.4. Freshness 237
12.8. Security protocols and algorithms 237
12.8.1. Security services 237
12.8.2. Security analysis 238
12.9. Concluding remarks 241
References 242
Chapter 13: Establishing security in machine-to-machine (M2M) communication devices and services 244
13.1. Introduction 244
13.2. Requirements and constraints for establishing security in M2M communications 245
13.2.1. Unattended devices 245
13.2.2. Impact of multitude 245
13.2.3. Communication overhead 245
13.2.4. Computation overhead 246
13.2.5. Spatial considerations 246
13.2.6. Many-to-many communications 247
13.2.7. Ecosystem liability considerations 247
13.2.8. Privacy aspects 247
13.3. Trust models in M2M ecosystems 248
13.3.1. Ad hoc application level security 248
13.3.2. M2M service provider-managed model 248
13.3.3. Trust manager security model 250
13.4. Protecting credentials through their lifetime in M2M systems 251
13.4.1. Security fundamentals 251
13.4.2. Protecting secrets in exposed equipment 251
13.4.3. Efficient security approach 252
13.4.4. Emerging alternative: physically unclonable functions 253
13.5. Security bootstrap in the M2M system 254
13.5.1. Preprovisioning of credentials and physical binding 254
13.5.2. Need for late-stage personalization, dynamic provisioning, and security administration 255
13.5.3. Remote bootstrapping of prepersonalized secure elements: late-stage personalization 255
13.5.4. Dynamic bootstrapping 256
13.5.5. Bootstrapping by derivation from pre-existing credentials 257
13.5.6. Out-of-band-assisted bootstrapping 257
13.5.7. Key pair generation in communicating objects 257
13.6. Bridging M2M security to the last mile: from WAN to LAN 259
13.6.1. Gateway security models 261
13.6.1.1. Security model with a gateway ending the IP communication path 261
13.6.1.2. Security model with a gateway using NAT 262
13.6.1.3. Security model with a border router device 262
13.6.2. Specific case: multihop capillary networks 262
13.6.3. Bridging different security layers 263
13.7. Conclusion 263
13.7.1. Further sources of information/advice 263
13.7.2. Future trends 264
Part Three: Network optimization for M2M communications 266
Chapter 14: Group-based optimization of large groups of devices in machine-to-machine (M2M) communications networks 268
14.1. Introduction 268
14.2. Mobile network optimizations for groups of M2M devices 269
14.3. Managing large groups of M2M subscriptions 271
14.4. Group-based messaging 274
14.5. Policy control for groups of M2M devices 278
14.6. Groups and group identifiers 282
14.7. Conclusions 283
References 283
Chapter 15: Optimizing power saving in cellular networks for machine-to-machine (M2M) communications 286
15.1. Introduction 286
15.2. Extended idle mode for M2M devices 287
15.2.1. Requirements 287
15.2.2. Optimizations in the non-access stratum 288
15.2.2.1. Extended periodic updating timers 288
15.2.2.2. Power-saving state 289
15.2.3. Optimizations in the access stratum 291
15.2.3.1. Extended DRX in idle mode 291
15.2.3.2. Power-saving state 292
15.2.4. Performances 295
15.3. Paging idle-mode M2M device in a power-efficient manner 296
15.3.1. Challenges 296
15.3.1.1. Requirements for paging M2M devices in a group manner 296
15.3.1.2. Limitation of current H2H paging mechanism 297
15.3.2. Group-based paging for MTC 298
15.3.2.1. Location-based paging in the NAS level 298
15.3.2.2. Three-layer paging in the AS level 300
15.3.3. Performance 301
15.4. Power saving for uplink data transmission 303
15.4.1. Requirements for signaling optimization 303
15.4.1.1. Analysis on M2M applications 303
15.4.1.2. Available application-based method 303
15.4.2. On-demand uplink transmission 304
15.4.3. Performances 305
15.5. Conclusions 306
References 306
Chapter 16: Increasing power efficiency in long-term evolution (LTE) networks for machine-to-machine (M2M) communications 308
16.1. Introduction 308
16.2. M2M scenarios 309
16.3. 3GPP status and work 311
16.3.1. LTE power consumption-related work in 3GPP 311
16.4. Introduction to basic LTE procedures 312
16.4.1. Initial access procedures 312
16.4.2. Idle and connected mode 313
16.4.3. UE mobility 314
16.4.3.1. Mobility in idle mode 314
16.4.3.2. Mobility in connected mode 314
16.4.4. Discontinuous reception (DRX) 314
16.5. UE power consumption in LTE 315
16.5.1. Example power consumption model 316
16.5.1.1. Hardware model 316
16.5.1.2. State model 317
16.5.2. Way forward toward reduced power consumption 320
16.5.3. Reducing tail energy consumption 320
16.5.4. Extending the DRX cycle lengths 321
16.5.4.1. Results: aggressive optimization assumptions 321
16.5.4.2. Results: more realistic assumptions 322
16.5.5. Power-saving mode 325
16.5.6. Attach/detach 327
16.5.7. Other methods improving power efficiency 328
16.6. Discussion and conclusion 328
16.6.1. Discussion 328
16.6.2. Conclusion 329
References 330
Chapter 17: Energy and delay performance of machine-type communications (MTC) in long-term evolution-advanced (LTE-A) 332
17.1. Introduction 332
17.1.1. Motivation and scope 332
17.1.2. Research background 332
17.2. Technology background 333
17.2.1. Review of LTE-A signaling 333
17.2.2. 3GPP evaluation methodology and system assumptions 335
17.3. Analytic performance assessment 337
17.3.1. Delay analysis 337
17.3.1.1. Expected delay of Msg3 and Msg4 338
17.3.1.2. Expected delay of Msg1 and Msg2 without collisions 338
17.3.1.3. Expected delay of Msg1 and Msg2 with collisions 339
17.3.2. Discussion 340
17.3.3. Energy consumption analysis 340
17.4. Performance assessment via simulation 342
17.4.1. Calibration of the simulator 343
17.5. Numerical results 345
17.6. Conclusion and further research directions 345
Appendix 348
A.1. Calculation of the average number of Msg3 and Msg4 transmissions 349
A.2. Calculation of the average number of Msg1/Msg2 transmissions (system without collisions) 349
A.3. Calculation of the average time that the preamble is waiting for retransmission 350
A.4. Calculation of the average number of Msg1/Msg2 transmissions (system with collisions) 350
Part Four: Business models and applications 354
Chapter 18: Business models for machine-to-machine (M2M) communications 356
18.1. Introduction 356
18.2. An overview of M2M from a commercial perspective 356
18.3. A brief history of M2M 357
18.3.1. The roots of M2M 357
18.3.2. The present 359
18.3.3. The future 360
18.4. The potential for M2M 361
18.5. The benefits of M2M 365
18.6. Business models for M2M 367
18.7. The return on investment 369
Chapter 19: Machine-to-machine (M2M) communications for smart cities 372
19.1. Introduction 372
19.2. Smart city technologies 373
19.2.1. M2M technology in the field 374
19.2.2. Big data back-end platform 375
19.2.3. Client interfaces 376
19.3. M2M smart city platform 377
19.3.1. Platform architecture 377
19.3.2. Open data APIs and app stores 377
19.3.3. Interaction with stakeholders 379
19.4. Financing M2M deployments in smart cities 380
19.4.1. Smart city rollout phases 380
19.4.2. Barriers of entry 381
19.4.3. Bootstrapping the smart city market 382
19.4.4. Smart city value chain 383
19.5. The ten smart city challenges 384
19.5.1. Political cycles and decision taking 385
19.5.2. Procurement and finances 386
19.5.3. Established and complex stakeholder system 386
19.5.4. Urban fab labs, data, and citizens 387
19.6. Conclusions 388
Chapter 20: Machine-to-machine (M2M) communications for e-health applications 392
20.1. Introduction 392
20.2. M2M network architecture 394
20.3. Enabling wireless technologies: standards and proprietary solutions 395
20.3.1. M2M area network 396
20.3.1.1. Open standards 396
20.3.1.2. Proprietary solutions 399
20.3.2. M2M access communication network 399
20.4. End-to-end solutions for M2M communication: connectivity and security 400
20.4.1. Technology integration for M2M communications 401
20.4.2. Test bed implementation of M2M solutions 402
20.4.3. Security and privacy issues 404
20.4.3.1. Challenges 404
20.4.3.2. Approaches 406
20.5. Existing projects 407
20.6. Concluding remarks 411
Acknowledgments 411
References 411
Index 416