- a
- access control threats 442–443
- active optical networks (AONs) 353
- actuation capacity 199
- actuators 171–172, 194
- adaptive traffic signal control (ATSC) approach 325
- advanced beam‐forming technology 520
- advanced code technology 519
- advanced driver‐assistance systems (ADAS)
- Advanced Message Queuing Protocol (AMQP) 160, 162
- Advanced Metering Infrastructure (AMI) 349
- agent‐based model 187
- aggregated‐proof‐based hierarchical authentication (APHA) 115
- air gapping 169
- AlexNet 329
- Amazon Echo 67
- AmazonWeb Services (AWS) 139
- analog‐to‐digital converter (ADC) 72
- analytics and decision‐making
- architectural model 157–158
- comparisons of surveyed solutions 197–198
- taxonomy 183–184
- data analytics 184–186
- decision‐making 186–189
- Apache NiFi open source framework 336
- application context 24–25
- application programming interface (API) 226
- application protocols 160
- Array of Things (AoT) 225
- artificial intelligence (AI)–augmented geographic routing approach 478
- artificial intelligence (AI) chipsets 68
- artificial neural network (ANN) 324, 325
- Aston, Kevin 311
- asymmetric DSL 353
- attractive repulsive greedy forwarding (ARGF) algorithm 488
- attractive repulsive pressure greedy forwarding (ARPGF) algorithm 488, 490
- attribute‐based access control (ABAC) 114
- augmented reality (AR) 10
- authentication 109–113
- authentication threats 442
- authorization 113–117, 125–129
- automatic repeat request (ARQ) 162
- autonomous driving class 436
- autonomous navigation class 436
- autonomous vehicles (AVs) 459
- autonomous vehicular networks (AVNs) 460
- cloud‐based architecture for communication 461
- fog‐based architecture for communication 462, 463
- hypothesis formulation 463–464
- simulation design
- hypothesis testing 467–469
- results 464–467
-
- b
- backhaul data transfer 5G, 512
- Basic Linear Algebra Subroutines (BLAS) 225
- beam division multiple access (BDMA) 516, 517
- Big Data 312
- analytics 185
- IoT
- ambiguity 317
- description 315
- features 316
- inconsistency 317
- interoperability characteristics 317
- quality characteristics 317
- redundancy 317
- stream applications 318–319
- temporariness 316
- uncertainty 317
- value 316
- variability 316
- variety 316
- velocity 316
- veracity 316
- volume 316
- binary offloading 231
- bioinformatics 529
- cloud computing applications 533–537
- fog computing for
- complex biological organisms, understanding of 540
- quality of service 539
- real-time microorganism detection system 541–543
- Infrastructure as a Service
- Bionimbus 535
- Cloud BioLinux 536–537
- CloVR 535–536
- OpenStack 535
- Platform as a Service 535
- Software as a Service
- CloudAligner 534
- CloudBurst 534
- Cloud4SNP 534
- Crossbow 534
- FX tool 534
- Myrna 534
- PeakRanger 534
- STORMSeq tool 533–534
- Variant Annotation Tool 534
- BioLinux platform 536–537
- Bluetooth 354
- Bluetooth Low Energy (BLE) 160
- BOLO Vehicle Tracking Algorithm 178
- broadband passive optical network (BPON) 353
- broker node 297
- Business Area Networks (BANs) 350
- c
- cache allocation approaches 91–93
- CacheWeight 93
- caching
- cache allocation approaches 91–93
- data allocation approaches 93–100
- and fog computing 81–82
- capability‐based access control (CapBAC) 115
- CaptureVideo (CV) 336
- CCN see content‐centric networking (CCN)
- cellular communications 354
- classification 320
- client mobility 82
- close‐to‐the‐edge method 188
- CloudAligner 534
- CloudBurst 534
- cloud computing 355, 459–460
- definition 513
- delivery models 532–533
- description 531
- environment 140
- vs. fog computing 538
- issues 530–531
- merits 530
- service models 532
- variations 431
- cloud‐fog‐IoT architecture 143
- cloudification
- architectural model 157
- storage 196–197
- taxonomy
- storage 182–183
- virtualization 179–182
- cloud layer 293–294
- cloudlets 10, 44, 446
- CloudMan 535
- Cloud of Sensors (CoS) 320
- Cloud4SNP 534
- Cloud Virtual Resource (CloVR) 535–536
- ClusterFS file system 535
- clustering 320
- cognitive radio (CR)
- combined‐type communication (CTC) 515, 516
- communication
- architectural model 154–155
- cellular 354
- comparisons of surveyed solutions 189–191
- efficient fog‐cloud 199–200
- failures 442
- low‐latency 190–191
- near‐field 110
- optical 353
- privacy 118
- taxonomy 159–165
- low‐latency 163–164
- mobility 164–165
- reliability 162–163
- standardization 160–161
- vehicle‐to‐device
- vehicle‐to‐infrastructure
- vehicle‐to‐vehicle
- communication technologies
- 4G 5G standards, 16–17
- IEEE 802.11 15–16
- LPWAN, other medium‐and long‐range technologies 18
- WPAN, short‐range technologies 17–18
- communication‐to‐computation ratio (CCR) 375, 382
- complex event processing (CEP) 321
- computational intelligence (CI)
- deep learning 326–328
- description 319
- goal of 322
- machine learning 322–326
- computational self‐awareness 255
- computer vision applications
- 3D scene reconstruction from LIDAR scans 480–482
- object tracking 482–483
- patient tracking with face recognition case study 478–480
- computing continuum
- goal‐oriented approach
- building blocks and enabling technologies 224–228
- goal‐oriented annotations for intensional specification 221–222
- mapping and run‐time system 222–224
- motivating continuum example 219–221
- research philosophy 217–219
- schematic 216–217
- computing/node failures 442
- conditional privacy‐preserving authentication with access linkability (CPAL) model 119
- confidentiality, integrity, and availability (CIA) triad model 59
- Constrained Application Protocol (CoAP) 160, 162, 163, 165, 538–539
- constrained battery life of edge devices 71–72
- constraints 441–442
- content‐centric networking (CCN)
- caching
- allocation approaches 91–93
- data allocation approaches 93–100
- and fog computing 81–82
- mobility management 82
- classification of 83
- direct exchange for location update 84
- interest forwarding 85
- mobility with indirection point 84–85
- proxy‐based mobility management 85
- query to the rendezvous for location update 84
- server‐side mobility 84
- tunnel‐based redirection 86–87
- user mobility 83–84
- research directions 81
- router components 80
- security in 88–90
- DOS attack risk 90
- risks due to caching 90
- security model 91
- content delivery network (CDN) 183
- content mobility 82
- context‐awareness 23–25
- application context 24–25
- end‐to‐end context 24
- mobility context 23–24
- server context 23
- Control and Provisioning of Wireless Access Point (CAPWAP) protocol 418
- convolutional neural network (CNN) 327, 328, 330
- cooperative CRNs 512–513
- cooperative distributed systems (CDS) model 119
- cooperative driving class 435
- cooperative perception class 435
- cooperative safety class 435
- cost‐effective caching (CEC) algorithm 97
- Crossbow 534
- cross‐layer cooperative caching strategy 96
- cross‐link detection protocol (CLDP) 485
- d
- data aggregation 174, 177–179, 195
- data allocation approaches 93–100
- data analytics 168
- data collectors (DCs) 335
- data discovery 171
- data discrepancy in real‐world settings 70–71
- Data Distribution Service (DDS) 160, 163
- data encryption 166
- data filtering 174, 176–177, 195
- data flow execution for big data 226–228
- data fusion 177
- data homogenization 174
- data mining 171
- data normalization 173–175, 195
- data prioritization techniques 176
- data privacy 448–449
- data quality 150–151
- architectural model 156–157
- comparisons of surveyed solutions 194–195
- taxonomy
- classification 173
- data aggregation 177–179
- data filtering 176–177
- data normalization 174–175
- data replication, FNs 272–273
- data serialization 174
- data stream mining
- classification 320
- clustering 320
- description 320
- outlier and anomaly detection 321
- regression 320–321
- data stream processing
- data stream mining 320–321
- information fusion
- high‐level fusion 320
- low‐level fusion 319
- medium‐level fusion 319
- multilevel fusion 320
- decision tree algorithm 324
- dedicated short‐range communications (DSRC) 18
- DeepEar 329
- Deep Keyword Spotting (KWS) 329
- deep learning (DL) 68, 326–328
- deep neural networks (DNNs) 326–327
- constrained battery life of edge devices 71–72
- data discrepancy in real‐world settings 70–71
- heterogeneity in computing units 73
- heterogeneity in sensor data 72–73
- memory and computational expensiveness of 68–70
- multitenancy of deep learning tasks 73–75
- offloading to nearby edges 75–76
- on‐device training 76
- Delaunay triangulation (DT) graphs 485
- delay‐critical fog‐based vehicular applications
- autonomous driving class 436
- autonomous navigation class 436
- communication task 436
- cooperative driving class 435
- cooperative perception class 435
- cooperative safety class 435
- directed acyclic flow graph of task 436
- execution task 436
- obstacle detection 434, 435
- timeliness guarantees
- benchmarking 437–440
- computational resource and data management 444–448
- coping with perturbation 443–449
- description 436
- firm real‐time application 437
- hard real‐time application 437
- network resource management 443
- resource monitoring 440
- RT communication 440–441
- scheduling tasks 440
- soft real‐time application 437
- timeliness perturbations
- access control threats 442–443
- authentication threats 442
- communication failures 442
- computing/node failures 442
- constraints 441–442
- heterogeneity 442
- intrusion threats 443
- message loss 442
- mobility 441–442
- network disconnection/link disruption 442
- privacy threats 443
- delay minimization without replication
- complexity reduction 277–278
- min‐cost flow formulation 276–277
- problem formulation 275–276
- delay minimization with replication
- greedy solution in multiple requests 280–282
- hardness proof 279
- rounding approach in multiple requests 282–284
- single request in line topology 279–280
- delay‐tolerant fog computing 432–433
- delay‐tolerant networking (DTN)
- denial‐of‐service (DoS) attacks 168
- depthwise separable convolutions 333
- DetectFaces (DF) 336
- device layer 294
- device privacy 118
- device‐to‐fog (D2F) 22
- digital subscriber line (DSL) 353
- disaster‐incident situational awareness, geospatial video analytics for see geospatial video analytics
- discretionary access control (DAC) 114
- distance‐based forwarding (DBF) protocol 10
- distributed capabilities‐based access control model (DCapBAC) 115
- distributed data learning process, advantages 334
- distribution management system (DMS)
- description 356
- feeder‐based communication scheme 358–366
- functions used in 357
- distribution system operator (DSO) 358
- distribution system state estimation (DSSE) 357
- Docker 180
- DOS attack risk 90
- downward information updating 278
- duplicate detection techniques 176
- duplicate name prefix detection (DND) 86
- dynamic adaptive streaming (DAS) technology 100
- dynamic ad hoc wireless network (DAWN) 507
- dynamic fog service for next generation mobile applications 10
-
- e
- earliest deadline first (EDF) method 379
- EDA see estimation of distribution algorithm (EDA)
- edge‐as‐a‐service (EaaS) 146
- edge‐cloud 44
- edge computing , , 44–45, 313
- architecture 46–47
- network management 61
- resource management 57–58
- security and privacy 58–61
- use cases 50–51
- smart home 52–54
- wearable ECG sensor 51–52
- edge device running edge operating system (edgeOS) 53
- edge devices 67
- constrained battery life of 71–72
- edge ecosystem 59
- Edge Mesh 341
- EdgeSGD 335
- efficient distributed data processing 200
- efficient fog‐cloud communications 199–200
- EFTF (earliest finish time first) rule 376
- EH mobile users (MUs) 232
- electrical power grid 347
- electrocardiogram (ECG) 245–246
- electromyography (EMG) 246
- Electronic Data Processing (EDP) 108
- elliptic curve cryptography (ECC) 112
- encoding and decoding method 376
- end‐device heterogeneity 21–22
- endpoint identifiers (EIDs) 164
- end‐to‐end context 24
- end‐to‐end network heterogeneity 22–23
- end‐to‐end security 30
- energy consumption vs. latency 238–239
- energy cost 27
- energy harvesting (EH)‐enabled Internet of Things
- computation offloading 231
- future research challenges 240–241
- system model 232–233
- computation model 233–235
- energy harvesting model 235–238
- tradeoffs in EH fog systems
- energy consumption vs. latency 238–239
- execution delay vs. task dropping cost 239–240
- energy harvesting model
- stochastic process 235–236
- wireless power transfer 236–238
- energy management system (EMS) 356
- energy optimization algorithms 255–258
- Eoulsan framework 535
- error detection mechanisms 176
- estimation of distribution algorithm (EDA)
- basic procedure of 372
- complex scheduling problems 373
- earliest deadline first method 379
- encoding and decoding method 376
- heuristic vs. uEDA method 381–382
- local search method 378
- modified heuristic method 378, 379
- probability model and initialization 377
- p‐values 381
- relative percentage deviation (RPD) value 381
- shortest processing time first method 379
- shortest t‐level task first method 379
- simulation environmental parameters 379, 380
- testing environment setting 379
- uEDA scheme 377–378
- updating and sampling method 377–378
- Ethernet passive optical network (EPON) 353
- European Telecommunication Standards Institute (ETSI) 147
- event‐(ESS) and time‐stepped simulation (TSS) 295
- evolutionary/genetic algorithms 187
- evolved packet core (EPC) caching techniques 524
- execution delay vs. task dropping cost 239–240
- execution time, of hardware platforms 329, 330
-
- f
- fault tolerance 448
- in SDN‐based wireless mesh networks 424
- federated intelligent transportation 10
- feeder‐based communication scheme, for DMS
- advantage 359
- Big Data calculations 359
- measurements 358, 359
- preconditions for deployment 358
- real‐time simulation Using MATLAB and ThingSpeak 359–366
- schematic illustration 358
- 5G 505
- cellular architecture 508–510
- cloud‐based architecture 513–514
- cognitive radio 512–513
- device‐centric architecture review 506
- device‐to‐device communication 510
- energy efficiency 510–511
- evolutionary view 507
- fog computing, need for 508
- in health care 521
- heterogeneous network design and support 507
- IEEE802.11 507
- issues/challenges 507, 522–524
- logistic and tracking 521
- machine‐to‐machine communication 507
- massive multiple‐input multiple‐output 507
- M2M 519–520
- personal usage 521
- protocol stack 509, 510
- research projects on 523
- revolutionary view 507
- seamless user experience 507
- in smart grid technology 521
- technology and methodology 514
- beam division multiple access 516, 517
- flexible duplex 518
- HetNet 515–516, 520
- mixed bandwidth data path 516, 518
- multibeam‐based communication system 520
- multiple‐input multiple‐output 518–519
- software defined networking 520–521
- wireless virtualization 516
- test‐driven design transmission 518
- two‐tier architecture 512
- virtualized home 522
- 5G standards 16–17
- fixed‐band non‐sharing (FB‐NS) algorithm 422, 423
- flat names 88
- floating‐point operations (FLOPs) 69
- flow‐based programming (FSB) 336
- FNs see Fog Networks (FNs)
- fog abstraction layer 49
- fog‐assisted runtime energy management, wearable sensors 253–254
- computational self‐awareness 255
- energy optimization algorithms 255–258
- MDP strategy 259–263
- myopic strategy 258
- fog computing 47–49, 312–313 see also edge computing
- architecture 49–50
- architecture for bioinformatics sequencing data 538, 539
- authentication 109–113, 124–125
- authorization 113–117, 125–129
- benefit of 460
- for bioinformatics applications
- complex biological organisms, understanding of 540
- quality of service 539
- real‐time microorganism detection system 541–543
- caching 81–82
- vs. cloud computing 538
- fog‐enabled infrastructures 105–106
- generic fog enabled IoT environment 105–106
- for geospatial video analytics 474–475
- Internet of Things security phenomenon 105, 107
- network management 61
- privacy 117–119
- purpose of 537
- resource management 57–58
- security and privacy 58–61
- smart cities 105–106
- trust in IoT 107–109
- use cases
- smart pipeline monitoring system 55–57
- smart traffic light system 54–55
- fog execution model 234–235
- fog layer 294
- fog moving close to sensors/actuators 188
- FogNetSim++
- architecture 296–298
- cloud layer 293–294
- device layer 294
- fog layer 294
- FogNetSim++ installation 300
- modeling and simulation 294–295
- OMNeT++ installation 298–299
- sample fog simulation 300–305
- Fog Networks (FNs)
- challenges 274–275
- data replication 272–273
- delay minimization without replication
- complexity reduction 277–278
- min‐cost flow formulation 276–277
- problem formulation 275–276
- delay minimization with replication
- greedy solution in multiple requests 280–282
- hardness proof 279
- rounding approach in multiple requests 282–284
- single request in line topology 279–280
- illustration of 269–270
- long‐term and short‐term placement 272
- multiple data placement with budget problem 270, 274
- network model 273
- performance evaluation
- algorithm comparison 286–287
- experimental setting 285–286
- results with and without data replication 288–289
- trace analysis 287–288
- trace information 285
- fog node selection 444, 446
- fog service orchestration layer 49–50
- fog simulators 295
- fog‐to‐cloud (F2C) 23
- fog‐to‐fog (F2F) 22–23
- follow‐me cloud (FMC) 145
- follow‐me fog (FMF) framework 443
- forest fire detection
- forward collision warning (FCW)
- 4G 505
- 4G standards 16–17
- function‐centric fog/cloud computing (FCC) paradigm
- challenges 476–477
- illustrative example of 475
- FX tool 534
-
- g
- Galaxy cloud 535
- generalized dominating set‐based caching (GDSC) 92
- generic fog enabled IoT environment 105–106
- geo‐distributed IoT devices 43
- geographic routing approach
- AI‐augmented implementation 487–490
- artificial intelligence relevance 486–487
- challenges 484–486
- geo‐social networks (GSNs) 82
- geospatial video analytics
- computer vision applications
- 3D scene reconstruction from LIDAR scans 480–482
- object tracking 482–483
- patient tracking with face recognition case study 478–480
- data collection using edge routing 484–490
- fog computing for 474–475
- geo‐distributed latency‐sensitive SFC challenges 491–492
- imagery data processing 473–474
- metapath‐based composite variable approach 492–495
- metapath‐based SFC orchestration implementation 495–496
- wide‐area motion imagery (see wide‐area motion imagery (WAMI))
- gigabit passive optical network (GPON) 353
- global positioning system (GPS) sensor 72
- goal‐oriented approach, computing continuum
- annotations for intensional specification 221–222
- building blocks and enabling technologies 224–228
- mapping and run‐time system 222–224
- motivating continuum example 219–221
- Google Latitude 82
- GoogleNest 67
- Google Protocol Buffers 174
- gravity pressure greedy forwarding (GPGF) protocol 485
- greedy distributed spanning tree routing (GDSTR) protocol 485
- greedy perimeter stateless routing (GPSR) 485
- greedy solution in multiple requests 280–282
- grey relational analysis (GRA) 96
-
- h
- health care, 5G in 521
- heterogeneity 442
- in computing units 73
- in sensor data 72–73
- heterogeneous network (HetNet) 515–516, 520
- heterogeneous physical resources 49
- heterogeneous signcryption (HSC) scheme 116
- hidden Markov model 187
- hierarchical data aggregation 178
- hierarchical data analytics 185
- hierarchical/humanfriendly names 88
- high‐performance computing (HPC) 215
- Hodrick‐Prescott filter 177
- Home Area Networks (HANs) 350
- host card emulation (HCE) 110
- human‐facing applications 371
- human‐type communication (HTC) 515
- hybrid cloud 533
- hypervisor 496
- hypervisor virtualization method 181
- hypothesis transfer learning (HTL) 334
-
- i
- ideal nearest replica routing (iNRR) 95
- identity authentication and capability‐based access control (IACAC) 115
- identity‐based cryptography (IBC) 112
- IEEE 802.11 15–16
- IEEE 802.15.4 160
- iFogSim 460, 462, 464, 470
- inductive transfer learning approach 388
- Industrial Area Networks (IANs) 350
- information centric network (ICN) 183
- infrastructural fog (iFog)‐assisted mobile application
- infrastructural mobile fog computing
- forest fire detection
- land vehicular fog –10
- marine data acquisition –8
- marine fog 11
- mobile ambient assisted living
- road crash avoidance
- unmanned aerial vehicular fog 12–13
- user equipment‐based fog 13–15
- Infrastructure as a Service (IaaS) , 532
- bioinformatics tools
- Bionimbus 535
- Cloud BioLinux 536–537
- CloVR 535–536
- OpenStack 535
- infrastructure protocols 160
- Intel Edison 329
- intelligent, multiversion libraries 225–226
- intelligent systems, IoT
- accuracy vs. energy consumption 340
- lack of complete training data set 340
- security and privacy 341
- interest forwarding 85
- interference management 5G, 512
- Internet of Drones (IoD)
- Internet of Medical Things (IoMT)
- Internet of Things (IoT) , 311, 371
- architectural model
- analytics and decision‐making 157–158
- cloudification 157
- communication 154–155
- data quality 156–157
- security and privacy 156
- case studies 152–154
- challenges 198, 312
- comparisons of surveyed solutions
- actuators 194
- analytics and decision‐making layer 197–198
- cloudification 195–197
- communication 189–191
- data quality 194–195
- security and privacy 191–193
- sensors 193–194
- data challenges in three dimensions (see Big Data; data stream processing)
- data quality 150–151
- data types 315
- definitions 142–144
- intelligent systems
- accuracy vs. energy consumption 340
- lack of complete training data set 340
- security and privacy 341
- interoperability 149
- location‐awareness 152
- mobility 152
- motivations 144–148
- real‐time responsiveness 149–150
- recommended research directions 198–200
- scalability 148–149
- security and privacy 151–152
- security phenomenon 105, 107
- sensors 330
- taxonomy 158–159
- analytics and decision‐making layer 183–189
- cloudification 179–183
- communication 159–165
- data quality 173–179
- Internet of Things 170–172
- security and privacy layer 165–170
- three‐tier architecture 313
- two‐tier cloud assisted 313
- Internet of Vehicles (IoVs)
- Internet service provider (ISP) 83
- interoperability 149
- interworking of different fog localities 200
- intrusion detection 168
- intrusion threats 443
- IoT‐based remote health monitoring application 251
- IoT‐based smart traffic infrastructure
- IoT intelligent systems
- accuracy vs. energy consumption 340
- lack of complete training data set 340
- security and privacy 341
- Iowa Quantified (IQ) project 225
- iteration updating (IU) algorithm 287
- iterative feature transformation (IFT) 389
-
- k
- key‐policy attribute‐based encryption (KP‐ABE) scheme 119
- K‐means 324
- K‐nearest neighbors (KNN) 324
-
- l
- land vehicular fog computing (LV‐Fog) , –10, 31–32
- latency constraints 48
- leave a copy down (LCD) policy 95
- leave a copy everywhere (LCE) policy 95
- LIDAR scans 3D scene reconstruction, 480–482
- likelihood of features tracking (LoFT) framework 482, 483
- linear EH model 237–238
- linear predictive coding (LPC) algorithm 178
- LinuX Containers (LXC) 180
- load balancing of request and traffic 28–29
- load flow (LF) 357
- local execution model 234
- location‐awareness method 152, 188
- location privacy 449
- location‐temporal access control (LTAC) 115
- location update, direct exchange for 84
- Locator/ID Separation Protocol (LISP) 160
- LoRaWAN 355
- low‐latency 163–164
- low power wide area networks (LPWANs) 18, 355
- low‐rate wireless personnel area networks (LR‐WPAN) 416
- Lyapunov optimization framework 240
-
- m
- machine learning (ML) 312, 314
- artificial neural network 324, 325
- defined 322
- on fog devices, challenges for running 328–334
- incremental learning algorithms 325
- K‐nearest neighbors 324
- Naïve Bayes algorithm 324
- reinforcement learning 323, 325
- supervised learning 322, 325
- unsupervised learning 323
- machine‐to‐machine applications 371
- machine‐type communication (MTC) 515–516
- mandatory access control (MAC) 162
- man‐in‐the‐middle (MiM) attacks 170
- marine data acquisition –8
- marine fog 11
- Markov decision process (MDP) theory 250
- massive MIMO 519
- media access control (MAC) 10
- message loss 442
- Message Queuing Telemetry Transport (MQTT) 160, 297, 538
- metabolic equivalent of task (MET) 385
- description 386
- estimation error parameter 401
- exergaming experiment
- data collection 394–395
- reconfigurable design 403, 404
- gold standard computation 386–387
- R2 correlation coefficient of regression model 401
- reconfigurable estimation system 392–394
- reliable calculation
- energy consumption 397
- location‐independent MET estimation models 390, 391
- sensor localization 390–392, 398–401
- sensor‐based estimation 387–388
- transfer learning approach 388–389, 404, 405
- treadmill experiment
- data collection 395–396
- reconfigurable design 402–403
- unreliability mitigation 388
- value estimation 392, 398–399
- metabolic equivalent of task estimation systems (MES) 386
- metalinks 492, 493
- metapath‐based composite variable approach 492–495
- metapath‐based SFC orchestration implementation 495–496
- control applications 495–496
- SDN and hypervisor 496
- simple coordination layer 495, 496
- metapath composite variable approach 478
- metapaths 493
- metropolitan vehicle‐based cloudlet 10
- min‐cost (MC) algorithm 287
- min‐cost flow formulation 276–277
- min‐volume (MV) algorithm 286
- mixture of Gaussians (MOG)approach 482
- mobile ad hoc network
- mobile ad hoc wireless networks (MANETs) 476, 484
- mobile ambient assisted living (AAL)
- mobile base station (MBS) 511–514
- mobile cloud computing (MCC) , 44
- mobile edge computing (MEC) 44
- mobile fog computing (MFC)
- challenges 32
- in land vehicular fog computing 31–32
- in unmanned aerial vehicular fog computing 32–33
- in user equipment‐based fog computing 33
- communication technologies
- 4G 5G standards, 16–17
- IEEE 802.11 15–16
- LPWAN, other medium‐and long‐range technologies 18
- WPAN, short‐range technologies 17–18
- decision 450
- general challenges
- autonomous runtime adjustment and rapid redeployment 34
- scalable resource management of fog providers 35
- scheduling of fog applications 34–35
- testbed tool 33–34
- infrastructural
- forest fire detection
- land vehicular fog –10
- marine data acquisition –8
- marine fog 11
- mobile ambient assisted living
- road crash avoidance
- unmanned aerial vehicular fog 12–13
- user equipment‐based fog 13–15
- network management 450
- nonfunctional requirements 18–20
- context‐awareness 23–25
- end‐device heterogeneity 21–22
- end‐to‐end network heterogeneity 22–23
- provider 27–29
- security 29–31
- severe heterogeneity 21
- tenants 25–27
- and related models –6
- resource consumption 450
- resource management 449
- resource monitoring 450
- resource provisioning 450
- virtualization 450
- mobile fog node (mFog)‐assisted application
- mobile Internet of Things (MIoT) , 152
- MobileNet 333
- mobile vehicular cloudlets (MVCs) 10
- mobility 152, 191, 441–442
- context 23–24
- with indirection point 84–85
- management in CNN 82
- classification of 83
- direct exchange for location update 84
- interest forwarding 85
- mobility with indirection point 84–85
- proxy‐based mobility management 85
- query to the rendezvous for location update 84
- server‐side mobility 84
- tunnel‐based redirection 86–87
- user mobility 83–84
- model compression technique 69
- motivating continuum example 219–221
- MQ Telemetry Transport (MQTT) 162
- multi‐access (mobile) edge computing (MEC)
- multibeam‐based communication system 520
- multilayer feed‐forward neural network 324, 325
- multilevel organization 199
- multiple data placement with budget problem (MDBP) 270, 274
- multiple‐input multiple‐output (MIMO) 518–519
- multitenancy fog service provider discovery 28
- multitenancy of deep learning tasks 73–75
- multivariate Gaussian model 187
- Myriad VPU 333
- Myrna 534
-
- n
- Naïve Bayes (NB) algorithm 324
- name‐based trust and security approach 90
- name resolution 88
- NB‐IoT 355
- near‐field communication (NFC) 110
- Neighborhood Area Networks (NANs) 350
- NetInf naming scheme 89
- network bandwidth constraints 48
- network disconnection/link disruption 442
- network edge geographic routing challenges 484–486
- network function virtualization (NFV) 61
- network mobility 82
- network security 449
- network topology processing (NTP) 357
- Neural Compute Stick (NCS) 333
- neural networks methods 187, 188
- next‐generation sequencing 529, 530
- node‐based mutual authentication scheme 112
- node specialization 199
- noncooperative CRNs 513
- non‐fixed band non‐sharing (NFB‐NS) algorithm 422–423
- non‐fixed‐band sharing (NFB‐S) algorithm 423
- nonlinear EH model 238
- nonorthogonal multiple access (NOMA) 232
- Nvidia Tegra K1 329
- o
- OAuth protocol 116
- object tracking, in WAMI
- 3C pipeline needs 482–483
- large function processing 483
- small function processing 483
- observability analysis (OA) 357
- Olympus 320
- omics sequences 529
- OMNeT++ installation 298–299
- on‐device training 76
- online analytical processing (OLAP) 417
- online transaction processing (OTLP) 417
- Open Edge Computing Consortium 146
- OpenFlow switch 414–415
- OpenFog Computing Consortium 147
- OpenMV kit 331–332
- OpenStack++ 181
- Open Standard for Public Transportation (OSPT) 110
- OpenVINO toolkit 333
- operation management 28–29
- optical communications 353
- outlier and anomaly detection 321
- Oxford Nanopore MinIoN device 541, 542
-
- p
- Panacea's Cloud patient triage status tracking 478–480
- parameter pruning approach 69
- partial offloading 231
- passive optical networks (PONs) 353
- pattern detection 168
- PeakRanger 534
- pharmacogenomics 530
- photoplethysmogram (PPG) 245
- photoplethysmography (PPG) 247
- physical actuators 172
- physical security 30
- physical sensors 171
- physical unclonable functions (PUF) 109
- Pigi 174
- Platform as a Service (PaaS) , 532
- bioinformatics platforms 535
- population‐based incremental learning (PBIL) 377
- portable edge computers 44
- power grids 347
- power line communications (PLC) 350, 353
- predictor‐class probability 324
- privacy 60
- communication 118
- data 448–449
- device 118
- fog computing 117–119
- location 449
- processing 118–119
- and security, IoT intelligent systems 341
- storage 118
- threats 443, 448
- usage 449
- privacy‐aware DCapBAC mechanism 116
- privacy preserved data mining (PPDM) 119
- private cloud 533
- ProbCache 93
- processing privacy 118–119
- provider 27–29
- proxy‐based mobility management 85
- public cloud 532
- public‐key infrastructure (PKI) 109, 169
- publish/subscribe technique 162
- q
- Qualcomm Snapdragon 800 329
- quality of experience (QoE)
- measurement 375
- video‐streaming services 100
- quality of service (QoS) 18, 21, 27, 162, 187, 373
- query language for RDF (SPARQL) 222
-
- r
- radio access network (RAN) 147
- radio‐frequency identification (RFID) 113, 317
- radio frequency identification (RFID) tags 521
- random (RD) algorithm 286
- random oracle model 112
- Raspberry Pi 332
- Raspberry Pi 3 333, 334
- real‐time microorganism detection system
- bacteria identification 541
- base calling 541, 543
- metagenomics approach 543
- Oxford Nanopore MinIoN device 541, 542
- real‐time responsiveness 149–150
- RecogniseFaces (RF) 336
- recurrent neural networks (RNNs) 73
- reference semantic models (RSMs) 175
- regression 320–321
- reinforcement learning 323, 325
- reliability 190
- resilient distributed datasets (RDDs) 227
- resource allocation 446
- resource constrained devices 48
- resource consumption 446
- resource description framework (RDF) 120, 222
- resource discovery techniques 165
- restricted Boltzmann machine (RBM) 72
- road crash avoidance
- roadside‐unit controller (RSUC) 181
- Rock64 333, 334
- rod side Cloudlet (RSC) 446
- role‐based access control (RBAC) 115
- rounding (RO) algorithm 287
- rounding approach in multiple requests 282–284
- routing locators (RLOCs) 164
- routing mechanisms 164
- Rule Markup Language (RuleML) 120
- runtime fog server discovery 28
-
- s
- safety data aggregation 178
- sample fog simulation 300–305
- sandboxes 168
- satellite communications 354
- scalability 148–149
- scale per sensor 144
- science/public policy problem 219
- secure socket layer (SSL)/transport layer security (TLS) 168
- security 29–31
- in content‐centric networking 88–90
- DOS attack risk 90
- risks due to caching 90
- security model 91
- monitoring and management 30–31
- token 169
- security and privacy layer 151–152, 191–193
- architectural model 156
- taxonomy
- self‐assembly caching (SAC) scheme 96
- semantic technologies 317
- SemanticWebRules Language (SWRL) 120
- Sensor and Actuator Networks (SANETs) 350
- sensors 171, 193–194
- server allocation, server scheduling, and server migration 29
- server base station (SBS) 511–513
- server context 23
- server discoverability and connectivity 28
- server‐side mobility 84
- service function chaining (SFC) 477
- optimality 491
- practical and near‐optimal SFC composition approach 491–492
- reliability 491
- service level agreements (SLAs) 450, 531
- access control 451
- authentication 451
- intrusion detection 451
- privacy preserving 451
- severe heterogeneity 21
- SG see smart grid (SG)
- shortest processing time first (SPF) method 379
- shortest t‐level task first (STF) method 379
- SigFox 355
- single nucleotide polymorphism (SNP) 530, 534
- single request in line topology 279–280
- Single Shot MultiBox Detector (SSD) 333
- small data analytics 185
- smart building 153–154
- smart connected vehicle (SCV) 153
- smart grid (SG) 347
- cognitive radio 354
- communication infrastructure 349–350
- effectiveness 355
- fog‐based architecture 355–356
- frameworks 153
- 5G in 521
- goal of 349
- IoT 355
- smart metering applications 355
- Smart Utilities Networks 354
- systems 175
- vs. traditional grid 348
- TV White Spaces 355
- wired communication technologies 350–353
- wireless communication technologies 353–354
- smart home 52–54
- smart IoT systems
- device classification 330, 331
- issue in developing 341
- smart pipeline monitoring system 55–57
- SmartSensor infrastructure 315
- smart traffic light (STL) system 54–55, 153
- Smart Utilities Networks (SUNs) 354
- Software as a Service (SaaS) , 532
- bioinformatics tools
- CloudAligner 534
- CloudBurst 534
- Cloud4SNP 534
- Crossbow 534
- FX tool 534
- Myrna 534
- PeakRanger 534
- STORMSeq tool 533–534
- Variant Annotation Tool 534
- software‐defined networking (SDN) 11, 61, 181, 496
- access points, management of 418
- advantages 419
- aim of 411
- architecture of 411, 412
- assistive agent 418
- challenges 419
- clean state model 419
- event processing 417
- evolutionary model 419
- in fog computing 419–421
- 5G 520–521
- in mobile wireless networks 413
- OpenFlow‐based communication protocol 413
- Open Network Foundation categorization 411–412
- research works 416–419
- in wireless mesh networks
- architecture of 421, 422
- benefits of 423–424
- challenges 421
- fault tolerance 424
- fixed‐band non‐sharing algorithm 422, 423
- non‐fixed band non‐sharing algorithm 422–423
- non‐fixed‐band sharing algorithm 423
- in wireless sensor networks
- architecture 425–426
- challenges 424–425
- home networks 426
- Sensor OpenFlow 426
- software defined wireless networks (SDWN) 426–427
- specification languages 174
- spectrum hole 513
- standardization 190
- state‐of‐the‐art DNN models 69
- storage privacy 118
- STORMSeq tool 533–534
- supervised learning 322, 325
- supervisory control and data acquisition (SCADA) system 347, 354, 357
- support vector machine (SVM) algorithm 324, 389
- symmetric DSL 353
-
- t
- tardiness 373
- task migration/offloading 446
- threat index 112
- 3D scene reconstruction from LIDAR scans 480–482
- three‐tier IoT system architecture 374
- time division multiple access (TDMA) 232
- time‐series data 318
- TimesIn 93
- topology of Fog devices 337
- tradeoffs in EH fog systems
- energy consumption vs. latency 238–239
- execution delay vs. task dropping cost 239–240
- transductive transfer learning approach 388
- trust
- in IoT 107–109
- management and multitenancy security 31
- through web semantics 120, 122–123
- trusted third party (TTP) 116
- tunnel‐based redirection (TBR) 86–87
- Twister2 environment 226–227
- Twister:Net 226
- two‐factor authentication 110
- two‐party‐based EAKA protocol 112
- two‐phase event‐monitoring and data‐gathering (TPEG) 447
- two‐tier cloud assisted IoT 313
-
- u
- Universal Plug and Play (UPnP) 160
- unmanned aerial vehicular fog computing (UAV‐Fog) , 12–13, 32–33
- unsupervised learning 323
- unsupervised transfer learning approach 388
- upward information collection 278
- usage privacy 449
- user‐access control 168
- user authentication 108, 169
- user‐behavior‐driven CCN caching 96
- user equipment‐based fog computing (UE‐fog) , 33
- content delivery 14–15
- crowd sensing 15
- healthcare 13–14
- user mobility 83–84
- user node 297–298
- utility centers 350
-
- v
- Variant Annotation Tool (VAT) 534
- vehicle‐to‐device (V2D) communication
- vehicle‐to‐Infrastructure (V2I) communication
- vehicle‐to‐vehicle (V2V) communication
- vehicular ad‐hoc network (VANET) computing , 433
- vehicular fog computing (VFC) , 433
- vehicular opportunistic computation offloading 10
- video processing, multilevel data fusion for 338, 339
- virtual actuators 172
- virtualized home 522
- virtual private networks (VPNs) 459
- virtual reality 10
- virtual sensors 171
- Volt‐Var Optimization (VVO) 357
-
- w
- wearable sensors
- design challenges 250–251
- ECG sensor 51–52
- filter‐based techniques 248
- fog‐assisted runtime energy management 253–254
- computational self‐awareness 255
- energy optimization algorithms 255–258
- MDP strategy 259–263
- myopic strategy 258
- healthcare IoT paradigm 245
- Internet of Things 245
- IoT system architecture 251–253
- Markov decision process theory 250
- multiple access control 249
- peak detection algorithm 248
- photoplethysmography 247
- power spectral density 248
- remote health monitoring 247
- sleep scheduling 249
- SpO2 calculation 248–249
- web ontology language (OWL) 120, 222
- web semantics and trust management 120–123
- Wide Area Measurement Systems (WAMS) 349
- wide‐area motion imagery (WAMI) 474
- object tracking
- 3C pipeline needs 482–483
- large function processing 483
- small function processing 483
- wide area networks (WANs) 350
- Wi‐Fi 354
- WiMAX 354
- wind farm 153
- wired communication technologies, for SG
- digital subscriber line 353
- optical communications 353
- power line communications 350, 353
- wireless access in vehicular environments (WAVEs) 16
- wireless body area network (WBAN) 249
- wireless communication technologies, for SG
- Bluetooth 354
- cellular communications 354
- satellite communications 354
- Wi‐Fi 354
- WiMAX 354
- ZigBee 353–354
- wireless mesh networks (WMN), SDN in
- architecture of 421, 422
- benefits of 423–424
- challenges 421
- fault tolerance 424
- fixed‐band non‐sharing algorithm 422, 423
- non‐fixed band non‐sharing algorithm 422–423
- non‐fixed‐band sharing algorithm 423
- wireless personal area network (WPAN) 17–18, 160
- wireless power transfer (WPT) 232
- wireless sensor networks (WSNs) 116, 315
- SDN in
- architecture 425–426
- challenges 424–425
- home networks 426
- Sensor OpenFlow 426
- wireless technologies
- wireless virtualization 516
- Worldwide Interoperability for Microwave Access (WiMAX) 354
- World Wide Web Consortium's (W3C's) specification 222
-
- y
- Yelp 82
-
- z
- Zero‐Knowledge Authentication Protocol 113
- ZigBee 160, 161, 353–354
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