Intelligent IoT for the Digital World. Yang Sun Yang
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Acknowledgments
We would like to thank all the people who have made contributions to this book. In particular, we want to acknowledge the enormous amount of help we received from Yang Liu, Zening Liu, Lei Zhu, Zhouyang Lin, and Guoliang Gao at School of Information Science and Technology, ShanghaiTech University, China; Zhi Zhou, Liekang Zeng, and Siqi Luo at Sun Yat‐sen University, China; Anqi Huang and Rong Xia at Huazhong University of Science and Technology, China; Linshan Jiang, Guosheng Lin, Jun Zhao, Mengyao Zheng, Dixing Xu, Chaojie Gu, and Zhenyu Yan at Nanyang Technological University, Singapore; Xin Lou and Yang Li at Advanced Digital Sciences Center, Singapore; David Yau at Singapore University of Technology and Design; Peng Cheng at Zhejiang University, China; and Jun Huang at Massachusetts Institute of Technology, USA.
In addition, we want to express our gratitude to our colleagues for their kind support and encouragement. Last but not least, this book has been partially supported by the National Key Research and Development Program of China under grant 2020YFB2104300, the Program for Guangdong Introducing Innovative and Entrepreneurial Teams under grant 2017ZT07X355, the Singapore Ministry of Education AcRF Tier 1 grant 2019‐T1‐001‐044, and the National Natural Science Foundation of China (NSFC) under grant 62071193.
Acronyms
2CComputing and Communication3CComputing, Communication and Caching3GPPthe Third Generation Partnership Project5GFifth GenerationADCanalog‐to‐digital converterAFEanalog front‐endAIArtificial IntelligenceAMAmplitude ModulationASTAArrivals See Time AveragesBHCABusy Hour Call AttemptsBNBusy NodeBPFband‐pass filterBRBandwidth ReservationBSBase StationCAGRCompounded Annual Growth RateCATSCost Aware Task SchedulingCCPACalifornia Consumer Privacy ActCDCCloud data centerCDFCumulative Distribution FunctionCNoTcommon notion of timeCSPClock Synchronization ProtocolC‐V2Xcellular vehicle‐to‐everythingDNNdeep neural networkDRLdeep reinforcement learningDSRCDedicated Short Range CommunicationsEDCEdge Data CentereMBBenhanced mobile broadbandFFTfast Fourier transformFMFrequency ModulationFNFog NodeFTSPFlooding Time Synchronization ProtocolGAPgeneralized assignment problemGDPRGeneral Data Protection RegulationGPSGlobal Positioning SystemGRPGaussian random projectionH2Mhuman‐to‐machineHDPHealth Device ProfileHetVNETHeterogeneous Vehicle NETworkHNHelper NodeICNInformation‐Centric NetworkingIIRinfinite impulse responseIMT‐2020International Mobile Telecommunications‐2020IMUInertial Measurement UnitIoITInternet of Intelligent ThingsIoTInternet of ThingsLPCClinear prediction coefficientsLPWALow power wide areaLTE‐VLong Term Evolution for VehicleM2MMachine‐to‐machineMANETMobile ad hoc networkMCCMobile Cloud ComputingMECMobile/Multi‐access Edge ComputingmMTCmassive machine type communicationsMPCMulti‐party ComputationMRFmean removal filterMTCMachine‐type CommunicationsMTMHMultiple Tasks and Multiple HelpersNB‐IoTNarrowband IoTNGMNNext‐Generation Mobile NetworkNOMANon‐Orthogonal Multiple AccessPDFprobability density functionPLLPhase‐locked LoopPOMTPaired Offloading of Multiple TasksPOSTParallel Offloading of Splittable TasksPRACHPhysical Random Access ChannelPTPPrecision Time ProtocolQoSQuality of ServiceR&DResearch and DevelopmentRACHRandom Access ChannelRANRadio Access NetworkRBSReference‐Broadcast SynchronizationRMSEroot mean square errorRTTRound‐trip‐timeSD‐WANsoftware‐defined wide area networkSLAMSimultaneous Localization and MappingSoAService‐oriented ArchitectureTDMATime Division Multiple AccessTEETrusted Execution EnvironmentTNTask NodeTPSNTiming‐sync Protocol for Sensor NetworksUEUser EquipmentURLLCUltra Reliable Low Latency CommunicationsUWBUltra WideBandVANETVehicular Ad‐hoc NETworkVR/ARvirtual/augment realityZBzettabytesZCDzero crossing detection
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