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Ericsson Technology Review: Key technology choices for optimal massive IoT devices

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The massive IoT device domain faces two key challenges: cost-efficiently connecting a large number of devices in a wide area, and efficiently managing these devices over their complete life cycle. Further, since security and trust are key requirements in most massive IoT applications, it is important to ensure that the devices are secure, both in terms of communication and data integrity end-to-end (E2E), from device to data usage.

The latest Ericsson Technology Review article explores how to address these challenges in five key technology areas – connectivity, communication protocols, security, identity solutions and machine intelligence (MI). Carefully considered choices in these areas make it possible to achieve the desired key device characteristics and create IoT devices that support the multitude of existing and emerging massive IoT use cases.

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Ericsson Technology Review: Key technology choices for optimal massive IoT devices

  1. 1. Massive IoT devices Security Identity solutions Machine intelligence Communication protocols Connectivity ERICSSON TECHNOLOGY C H A R T I N G T H E F U T U R E O F I N N O V A T I O N | # 1 2 ∙ 2 0 1 8 MASSIVE IoTDEVICES
  2. 2. ✱ MASSIVE IoT DEVICES 2 ERICSSON TECHNOLOGY REVIEW ✱ JANUARI 9, 2019 The latest cellular communication technologies LTE-M and NB-IoT enable the introduction of a new generation of IoT devices that deliver on the promise of scalable, cost-effective massive IoT applications using LPWAN technology. However, a few key technology choices are necessary to create IoT devices that can support the multitude of existing and emerging massive IoT use cases. CLAES LUNDQVIST, ARI KERÄNEN, BEN SMEETS, JOHN FORNEHED, CARLOS R. B. AZEVEDO, PETER VON WRYCZA The Internet of Things (IoT) represents an ongoingparadigmshiftwithincommunications: everything that benefits from a connection can and will be connected. ■ MassiveIoTreferstoapplicationsthatareless latencysensitiveandhaverelativelylowthroughput requirements,butrequireahugevolumeoflow-cost, low-energyconsumptiondevicesonanetworkwith excellentcoverage.ThegrowingpopularityofIoT usecasesindomainsthatrelyonconnectivity spanninglargeareas,andareabletohandleahuge numberofconnections,isdrivingthedemandfor massiveIoTtechnologies. Throughthedevelopmentofnewtechnologiesin thefieldsofcommunication,computation,sensors, electronicsandbatteries,itisnowpossibleto developbattery-powereddeviceswithsensorsand actuatorsandcomputersthatareconnectedvia wide-areacommunicationnetworkstoacloud-based platformthathandlesdevicedataandmanagement. Thesedevicescanbetailoredtofitseveralspecific applicationareasanddeployedinmassivenumbers, makingthemfitforuseinmassiveIoTapplications. ExamplesofmassiveIoTapplicationareasinclude: wearables(e-health);assettracking(logistics);smart city/smarthome,environmentalmonitoringand smartmetering(smartbuilding);andsmart manufacturing(monitoring,tracking,digitaltwins). Thekeydevicecharacteristicsinclude: ❭❭ low device and deployment cost ❭❭ small form factor ❭❭ long battery life ❭❭ wireless connectivity for challenging locations ❭❭ strong application and communication security. TherearetwokeychallengesinthemassiveIoT devicedomain:(1)connectingalargevolume optimalmassive IoTdevices KEY TECHNOLOGY CHOICES FOR
  3. 3. MASSIVE IoT DEVICES ✱ JANUARI 9, 2019 ✱ ERICSSON TECHNOLOGY REVIEW 3 ofdevicesinawideareacost-efficiently,and(2) efficientlymanagingthesedevicesovertheir completelifecycle.Assecurityandtrustarekey requirementsinmostmassiveIoTapplications,the devicesmustbetrustedintermsofboth communicationanddataintegrityend-to-end(E2E), fromdevicetoapplicationdatausage.Many applicationsalsobenefitfromdevicesthatinclude localintelligencethatcanprocessdatabeforeitis furthercommunicated. Toaddressthesechallenges,itisnecessaryto makesmartchoicesinfivekeytechnologyareas– connectivity,communicationprotocols,security, identitysolutionsandmachineintelligence(MI)– asshowninFigure1.Carefullyconsideredchoicesin thesefiveareasmakeitpossibletoachievethe desiredkeydevicecharacteristicsandcreateIoT devicesthatsupportthemultitudeofexistingand emergingmassiveIoTusecases. Connectivity NewmassiveIoTcellulartechnologies,suchas NarrowbandIoT(NB-IoT)andLTEformachine- typecommunication(LTE-M),aretakingoffand drivinggrowthinseveralcellularIoTconnections, withacompoundannualgrowthrateof27percent expectedbetween2018and2024[1].LTE-Mand NB-IoTarecellularradioaccesstechnologiesthat providelow-powerwide-area(LPWA)IoT connectivityinlicensedspectrum,unlikeshort-range technologiesinunlicensedspectrumsuchas BluetoothandZigbee,andLPWAtechnologiessuch asSigfoxandLoRaWAN. The3GPPrelease13designtargetsformassive IoTwere:longdevicebatterylife,lowdevice complexitytoensurelowcost,supportformassive numbersofdevices,andcoverageenhancementsto beabletoreachdevicesinbasementsandother challenginglocations.Twonewcellulartechnologies Figure 1 Key technologies for massive IoT devices Massive IoT devices Security Identity solutions Machine intelligence Communication protocols Connectivity
  4. 4. ✱ MASSIVE IoT DEVICES 4 ERICSSON TECHNOLOGY REVIEW ✱ JANUARI 9, 2019 wereintroducedin3GPPrelease13:LTE-MTC (LTE-M),whichincludesanewuserequipment (UE)categorycalledCat-M1,andNB-IoT,which includesUEcategoryCat-NB1[2]. ACat-M1UEsupportsareducedbandwidthof 1.4MHzandadatathroughputofupto300kbpsin thedownlinkand375kbpsintheuplink.Italso supportsmobilityandVoLTEservices.Therefore, Cat-M1UEsaresuitableforapplicationssuchas wearablesandassettracking. NB-IoToperatesinhalf-duplexmodewithinthe 200kHzbandwidthandsupportsadatathroughput ofupto26kbpsinthedownlinkand63kbpsinthe uplink.SimilartoCat-M1,NB-IoToffersthecoverage enhancementfeature,withupto+20dBenhanced coverage,versus+15dBinCat-M.TheUEoutput powerclassesare20dBmand23dBm,asinCat-M. Toimprovetheuserexperienceandtocaterto moreusecases,severalenhancementsandnew functionalitiesareintroducedin3GPPLTE-Mand NB-IoTreleases14and15[3][4].Amongother things,release14featuresimprovementstoLTE-M –suchasmoreaccuratepositioningofUE,multicast transmissionandVoLTEinenhancedcoverage,as wellashigherdataratestoserveawiderrangeof applications,reducelatencyandextendbatterylife. Similarly,release14NB-IoTperformanceis improvedwithmoreaccuratepositioningofUE, multicasttransmission,capacityimprovement (thankstothesupportofpagingandrandom-access proceduresonnon-anchorcarriers),higherpeak dataratesandanewlowerpowerclass(14dBm)that enablesreducedpowerconsumptionandsmaller batteryformfactors. Inrelease15,LTE-Mfeaturesincludesupportfor higherUEvelocities,anewlowerUEpowerclass, reducedsystemacquisitiontime,reducedUEpower consumptionbyearlydatatransmission,awake-up signalforpagingmonitoring,relaxedmonitoringfor cellreselection,increasedspectralefficiencyand improvedaccesscontrol. Themainfeaturesintroducedinrelease15 NB-IoTaimtofurtherreducelatencyandUEpower consumption(earlydatatransmission,wake-up signalandquickRadioResourceControlrelease,for example).Otherfeaturesinclude:UEmeasurement improvements,supportofcellrangesofupto100km, TDDsupport,reducedsysteminformation acquisitionandcellsearchtime,andimprovedUE differentiationandaccesscontrol. Terms and abbreviations ASIC – Application-Specific Integrated Circuit | CoAP – Constrained Application Protocol | DMI – Distributed Machine Intelligence | E2E – End-to-end | EAP – Extensible Authentication Protocol | HTTP – Hypertext Transfer Protocol | IETF – Internet Engineering Task Force | IoT – Internet of Things | IPSO – Internet Protocol for Smart Objects | iUICC – Integrated Universal Integrated Circuit Card | LoRaWAN – Long Range Wide-Area Network | LPWA – Low-Power Wide-Area | LPWAN – Low-Power Wide-Area Network | LTE-M – LTE for Machines | LwM2M – Lightweight M2M | M2M – Machine-to-Machine | MI – Machine Intelligence | MNO – Mobile Network Operator | MQTT – Message Queuing Telemetry Transport | MTC – Machine Type Communication | NB-IoT – Narrowband Internet of Things | ODMI – On-Device Machine Intelligence | OSCORE – Object Security for Constrained RESTful Environments | PKI – Public Key Infrastructure | QUIC – Quick UDP Internet Connections | SenML – Sensor Measurement Lists | SGX – Software Guard Extensions | TCP – Transmission Control Protocol | TEE – Trusted Execution Environment | TLS – Transport Layer Security | TPU – Tensor Processing Unit | UDP – User Datagram Protocol | UE – User Equipment | WoT-TD – Web of Things Thing Descriptions
  5. 5. MASSIVE IoT DEVICES ✱ JANUARI 9, 2019 ✱ ERICSSON TECHNOLOGY REVIEW 5 Communicationprotocols Whilemanylegacymachine-to-machine(M2M) devicesusetailor-madeprotocolstacksforeach specificapplication,moreandmoredevicestoday (aswellasthevastmajorityofcurrentecosystems) useinternetprotocolsasthebasisoftheIoTprotocol stack.Thatis,theyusetheInternetProtocol(IP)on topofvariousdatalinkprotocols,followedbya selectionofstandardizedtransportandtransfer protocols,endingupattheapplicationlayerwith datamodelsandsemantics,asshowninFigure2. Thelatestcompressiontechniques,suchasStatic ContextHeaderCompression[5]cancompressthe IPv6andotherheadersintojustafewbytes,making itpossibleforeventhemostconstrainedlow-power wide-areanetwork(LPWAN)IoTcommunication systemstouseIPv6.OntopofIPv6,UserDatagram Protocol(UDP)orTransmissionControlProtocol (TCP)isusuallyusedatthetransportlayer.More recently,theQUICprotocol[6],combiningfeatures fromUDPandTCP,isattractinginterestforIoT scenariosaswell. IoTE2Ecommunicationisusuallysecuredwith TransportLayerSecurity(TLS).Recently,the InternetEngineeringTaskForce(IETF)finishedthe standardizationofTLSv1.3.Thislatestversion enablesfasterconnectionsetup,moreresiliencyto addresschangesandstrongersecurity.WhenE2E securitythroughmiddleboxes,suchasproxies,is needed,IoTcommunicationcanbesecuredwith ObjectSecurityforConstrainedRESTful Environments(OSCORE)[7]. Transferprotocolsareusedoverthe(secure) transportlayertotransferdataobjectsandprovide semanticsforoperations.Twotransferprotocolsthat reusethewebmodelarewidelyusedtoday: HypertextTransferProtocol(HTTP)[8]and ConstrainedApplicationProtocol(CoAP)[9]. ThenewversionofHTTP,HTTP/2[10],isalso increasinglybeingadopted.MessageQueuing Figure 2 Structure of an IoT device protocol stack LwM2M & IPSO + SenML / iot.schema.org / W3C Web of Things / (various) CoAP / HTTP / HTTP/2/ MQTT / (various) UDP / TCP / QUIC with transport security IP NB-IoT / CAT-M / (various) Data and semantics Transfer Transport Network Data link and physical
  6. 6. ✱ MASSIVE IoT DEVICES 6 ERICSSON TECHNOLOGY REVIEW ✱ JANUARI 9, 2019 TelemetryTransport(MQTT)isawidely-used publish-subscribeprotocolfortheIoT.Inindustrial environments,morespecializedprotocolsareoften used,andsomeenvironmentsalsoreuselegacy messagingprotocolsforIoT.Outofalltheoptions, webprotocols,andinparticularCoAPforthe embeddedweb,haveproventobethebestchoice, especiallyforinteroperabilityandscalability. Datamodelsprovidecommonsyntax,structure andsemanticsforthecommunicatingendpoints.A datamodelcanbesomethingverysimple– containingasingletemperaturevalue,forexample –butmostreal-lifesystemsrequiretheexchangeof moreinformation.Traditionally,inmanyM2M systemsthisinformationhasbeenencodedin application-specificways,butintheIoT,wheredata isoftenexchangedwithmultipletypesofloosely coordinatedsystems,commondatamodelsare neededtoensureendpointsunderstandthe meaningofthedata.Standardizeddatamodelssuch asSensorMeasurementLists(SenML)[11]canbe usedtoefficientlyinterchangebatchesaswellasthe timeseriesofsensorandactuatordata. AfullybuiltandoperationalIoTsystemalso requireslife-cyclemanagementcapabilitiessuchas automatedbootstrapping,configurationand firmwareupdates.TheOpenMobileAlliance SpecWorksLightweightMachine-to-Machine (LwM2M)deviceanddatamanagementprotocol [12]isbuiltonthestandardwebprotocolstack,using IP,UDP/TCP,CoAP,TLS/OSCOREandSenML. Furthermore,IPSOsmartobjectscanbeusedwith LwM2Mtoenablereusableapplicationsemantics. LwM2MandIPSOsmartobjectsprovideafullsuite tosupportlife-cyclemanagementandapplications withinteroperabilityfromconnectivityto applicationlayer. Finally,itispossibletobridgethegapbetween devicesfromdifferent–andoftenuncoordinated– ecosystemsbyusingcommonwaystoexpressdevice interactioncapabilitiessuchastheWorldWideWeb Consortium’sWebofThingsThingDescriptions (WoT-TD)[13],andcommonvocabulariesfor describingthings,suchasiot.schema.org. Security ThesecurityofIoTdevicesisbuiltonfunctionsfor securecommunication,applicationsecurityand devicesecurity.Together,thesefunctionsprotect devicemanagement,guaranteedataownershipand ensurethatdevicesremaintrustworthythroughout theirentireoperationallife.Securecommunication protocolslikeTLS,DTLSandOSCOREallowfor differentalgorithms.However,notallsupported algorithmsaresecure–thisisthecaseforTLSv1.2, forexample.Inaddition,IoTdevicesnormallyonly supportasubsetofalgorithms,whichmakesit importanttoselecttherightones.Newerprotocols likeTLSv1.3aremoresecureandinmanycasesalso moreefficient. IoTdevicesoftenonlysupportsymmetrickey cryptographicalgorithms,duetothefactthatpublic- keycryptographicfunctionsarecomplexand demandlargekeysizes,whichmaybeproblematic forveryconstraineddevices.Withproperdesign(as inIETFAuthenticationandAuthorizationfor ConstrainedEnvironments/OSCORE),however,it ispossibletotakeadvantageofpublic-key cryptographicfunctionsinsmallIoTdevices.The powerconsumptionofcomplexcomputationscan bereducedbyusingoptimizedhardware ITISPOSSIBLETOTAKE ADVANTAGEOFPUBLIC-KEY CRYPTOGRAPHICFUNCTIONS INSMALLIOTDEVICES
  7. 7. MASSIVE IoT DEVICES ✱ JANUARI 9, 2019 ✱ ERICSSON TECHNOLOGY REVIEW 7 accelerationofcryptographicfunctions.Itis thereforelikelythatfuturesmallIoTdeviceswill havecertaindedicatedcryptographichardware. Persistentcryptographickeymaterialmustbe storedsecurelyandkeptisolatedfromapplication softwareandphysicalinterfacesasmuchaspossible. IoTdevicesareincreasinglyfollowingthe smartphoneapproachofusingTrustedExecution Environments(TEEs)forthisisolation.Recently, ARM’sTrustZoneTEEtechnologywasbroughtto constraineddevices.Formorepowerfuldevices, therearealternativessuchasIntelSGX.Also, dedicatedsecuritycomponentslikeTrusted PlatformModulesorproprietaryASICs (application-specificintegratedcircuits)canbeused. Suchsolutionscanachieveahighlevelofsecurity, albeitathighercostandpowerconsumptionlevels. Inmanyusecases,integratedTEEswillbesufficient andmorecost-effective. Tomaintainsecurityduringtheiroperationallife, IoTdevicesshouldsupportsecuresoftware/ firmwareupgrade.Suchsecureupgradeisoften realizedbyhavingthesoftwaresignedpriorto releaseandhavingatrustedsubsysteminthedevice thatperformsaverificationofthesoftwarebeforeit isprogrammed/loadedintothedevice.Thistrusted subsystemisoftenreferredtoastherootoftrustofa device.Newstandardizationwork[14]wasrecently startedforsecuringupdatesforsoftware/firmware. Proceduresforsecuredevicelife-cyclemanagement arenoteasyandmayhavetobetailoredforaspecific usecase.Theawarenessoftheimportanceofdevice securityisgrowingintheindustry,butmoreefforts areneededtorealizewell-integratedtrustworthy systemsthatcovertheneedsoflife-cycle managementandapplicationssecurity. Supportingsecuresoftwareupdateiscrucial tothecreationoftrustworthyIoTdevices. Identitysolutions Trustworthinessalsodependsonsecuredigital identities.Adigitalidentitycanbeusedfor authentication,tomaintaindataownershiporfor softwareoriginverification.Forexample,adevice canproveitistrustworthy–thatis,ithasbeen producedbyalegitimatemanufacturer–throughan initialidentity. Anidentityconsistsofasecurelystoredsecretand anassignedlinkbetweenthissecretandanidentifier orname.Awell-knownwaytodothisistousea publickeyinfrastructure(PKI),wherethedevice holdsaprivatekeyandtheidentityisacertificate thatlinksthiskeytoanidentifierwrittenintothe certificate.ForIoTdevices,traditionalPKIshave theirproblems.Theircryptographicoperationscan becumbersomeforhighlyconstraineddevices,the certificatescanbelarge,andthecertificate revocationmanagementisusuallysotrickythatitis hardlyused.Furthermore,traditionalPKIshave privacyissues.Theseissuescanbeaddressed,as theyhavebeeninEnhancedPrivacyID,butat significantlyhighercomplexitycoststhanPKI. AsanalternativetoPKIs,itispossibletouse identitiesbasedonsymmetrickeycryptography. Thismethodisalreadyinuseforthe2G,3Gand4G mobilenetworksystemsthatuseSIMstoholdthe authenticationcredentials.SIMsusededicated hardwarechipsandarerelativelycomplex,mainly forlegacyreasons.Morecost-effectivesolutionsare ontheirway,suchastheintegratedUniversal SUPPORTINGSECURE SOFTWAREUPDATEISCRUCIAL TOTHECREATIONOFTRUST- WORTHYIoTDEVICES
  8. 8. ✱ MASSIVE IoT DEVICES 8 ERICSSON TECHNOLOGY REVIEW ✱ JANUARI 9, 2019 IntegratedCircuitCard(iUICC),inwhichtheSIM hardwareisintegratedintothedeviceprocessors. For5Gmobilenetworksystems,symmetrickey- basedidentitiesfornetworkaccesswillremainin use,butin5GitisalsopossibletousePKI-based identitiesviaExtensibleAuthenticationProtocol (EAP)-TLS.Figure3illustratesEAP-TLSID managementandusefornetworkaccess. Beyondmobilenetworks,othernetwork technologiesalsorequireidentities,andapplications mayneedidentitiestoo.Therefore,dependingonthe deviceusecase,asingledevicemayneedseveral identities.Thiscanbeproblematicforconstrained devices,anditmakesidentitymanagementdifficult. Asdifferentdevicehardwarewillcomewith differenttypesofinitialidentities,Ericssonbelieves thatafederationofidentities[15]isimportantinthe bootstrappingofidentitiesthatsupportthedevice usecase. Thecomplexityofidentitymanagementcanbe reducedifidentitiescanbereused.Inpractice,such reusemaybebuiltoncarefulderivationtechniques, inwhichanewidentityiscreatedandreceivestrust fromanexistingone.Thisis,forexample,thecasein GenericBootstrappingArchitecture,whereaSIM- basedkeycanbeusedtoderiveakeyforTLSor applicationsecurity. Amoreholisticanddistributedapproachto handlingthetrustindeviceidentitiescanbe achievedwithblockchainsordistributedledgers. Figure 3 EAP-TLS ID management and use for network access LWM2M LPA TEE iUICC EAP-TLS IoT device with Cat-M/NB-IoT Legend DM: device management iUICC: internal UICC LPA: local profile agent MNO network access ID provisioning and device management DM MNO network Identity
  9. 9. MASSIVE IoT DEVICES ✱ JANUARI 9, 2019 ✱ ERICSSON TECHNOLOGY REVIEW 9 Theseoptionsmakeitpossibletolinkdevicelife- cyclemanagementwiththatofthedeviceidentityin acommonframework. Machineintelligence MItechnologiesarekeytobuildingIoTsystemsthat canimprovetheirownperformanceofataskasmore databecomesavailableandmoreknowledgeis inferredandretained[16].InmassiveIoT,which handleslargevolumesofdataandmillionsof devices,MIisrequiredtointelligentlyautomatedata transmission,routinganddataprocessing. DistributedMI(DMI)concernsthedeployment, dynamiccompositionandlife-cyclemanagementof multi-nodeMIservices,whichcanbechainedfor provisioninganintelligentsystem.Orchestrating lightweightDMIcomponentstojointlyperformMI tasksthatenhancemassiveIoToperationsisa fundamentalresearchtopicatEricsson[17]. OneimportantpathinDMIismovingintelligence towardthedeviceend,whichwillminimizeE2E latency,enhancedataprivacyandlowerbandwidth requirementswhilereducingserver-sidecosts.Such on-deviceMI(ODMI)effortsgobeyondroutingIoT datatocloudbackendsandinsteadpromote horizontalconnectivityofdevicestoedge infrastructurethathostsDMIservices. Tofollowthispath,itisessentialthattheIoT devicesareabletoperformlow-powercomputation closetowherethedataisgeneratedandthe actuationisneeded.Thisrequiresknowledgeof MI-tailoredASICsandoftheirintegrationwithMI frameworks.Inthehardwarelayer,ODMIhasbeen embodiedintographicsprocessingunits,ASICs suchastensorprocessingunits(TPUs),and neuromorphicchips.ThemaininnovationofTPUs reliesonefficientcomplexinstructionset implementationsforthematrixmultiplierunit, whichiskeyforexecutingmodernMIworkflows. Neuromorphicchipsarelow-powerhardwarewhere asynchronousbrain-inspiredmanycoremeshesare interconnectedoversparseandrecurrentinter-core communicationtopologies,thuseasingthe translationofMIdataflowsintoinstructionflows. Onthesoftwareside,manyvendorsfavortheidea ofoffloadingMIcomputationtohardware accelerators.Inthislayer,theintegrationofsystems optimizationhasbecomewidespread,suchas compilersandschedulersthatcanpruneandbreak downMIworkflowsintodistributabletaskgraphs. ScalablemassiveIoTsystemsrequireinvestmentin MIservicesthatcanberepurposedtoadaptto operationalconditionsinevolvingnetworks,as sensorsandactuatorsareaddedandremoved. Flexibilityisthenacoredesignprincipleinmassive IoTsystems.EdgeandODMIaddsuchflexibility becausetheyoffermoreDMIdeploymentoptions andcontroloverchangingServiceLevel Agreements. LeadingtheMIandIoTconvergencewillrequire intertwiningtherightcompetenceinuniqueteam setups,bridgingsystemarchitects,embedded systemsdesignersanddistributedsystemengineers, aswellassubjectmatterexpertsonMI,security,IoT protocolsandsystemsoptimization.AtEricsson,we aretakingthismultidisciplinarychallengeseriously toensurethatweareequippedtoapplyDMI competentlytogeneratebusinessvalueinemerging IoTmarkets. ONEIMPORTANTPATHIN DMIISMOVINGINTELLIGENCE TOWARDTHEDEVICEEND
  10. 10. ✱ MASSIVE IoT DEVICES 10 ERICSSON TECHNOLOGY REVIEW ✱ JANUARI 9, 2019 Conclusion Rapidtechnologyadvancesinrecentyearshave beenofgreatbenefittotheongoingrealizationof massiveIoTdevices.Itis,however,vitalfordevice manufacturers,mobilenetworkoperatorsandother industryplayerstocarefullyconsidertheoptions andmaketherightchoiceswhenapplyingnew technologiesinthedevicedomain.FromEricsson’s perspective,therearefivekeytechnologyareasthat areofparticularsignificance:connectivity, communicationprotocols,security,identitysolutions andmachineintelligence(MI). Intermsofconnectivity,weareconvincedthat LTE-MandNB-IoTtechnologieswillfurther enhancefunctionalityanduse-caseapplicability, improvingthepossibilitytocreatedeviceswith lowerpowerconsumptionandasmallerformfactor, atalowercost.Itisalsoouropinionthatthebestway toensuretheinteroperabilityofIoTdevicesfrom communicationtoapplicationlayeristhroughthe useofprotocolstacksbasedonstandardized Further reading ❭❭ Ericsson web page, Internet of Things, available at: https://www.ericsson.com/en/internet-of-things ❭❭ Ericsson white paper, January 2016, Cellular networks for Massive IoT – enabling low power wide area applications, available at: https://www.ericsson.com/en/white-papers/cellular-networks-for-massive-iot-- enabling-low-power-wide-area-applications ❭❭ Ericsson white paper, June 2017, IoT security – protecting the networked society, available at: https:// www.ericsson.com/en/white-papers/iot-security-protecting-the-networked-society ❭❭ Ericsson white paper, March 2018, 5G security – enabling a trustworthy 5G system, available at: https:// www.ericsson.com/en/white-papers/5g-security---enabling-a-trustworthy-5g-system ❭❭ Ericsson Research blog, March 2017, Smart contracts for identities, available at: https://www.ericsson. com/en/blog/2017/10/smart-contracts-for-identities ❭❭ Ericsson Technology Review, November 2017, End-to-end security management for the IoT, available at: https://www.ericsson.com/en/ericsson-technology-review/archive/2017/end-to-end-security-management-for- the-iot internetprotocolsanddatamodelswithefficient capabilitiesfordatatransferanddevice management. Withregardtosecurity,webelievethatthe implementationofcryptographicfunctionsonthe deviceistheoptimalapproachtoachievingstrong devicesecurity.TEEswillsoonbeappliedtoIoT devicestosupportusecasesinwhichsecurestorage iscrucialandisolationbetweenfunctionalityis required.Itisalsoourviewthattheuseofsecure identitieswillsoonbecomekey,asameansto identifytheoriginofdataandtorealizesecure connectivity.Newcost-efficientsolutionsfor LPWANaccesswillemerge,leveragingthedevice’s built-insecuritycapabilities. Finally,advancesinMItechnologieshavemadeit possibletomoveintelligencetowardthedeviceend, whichweregardasagreatopportunitytominimize E2Elatency,enhancedataprivacyandlower bandwidthrequirements,whilereducing server-sidecosts.
  11. 11. MASSIVE IoT DEVICES ✱ JANUARI 9, 2019 ✱ ERICSSON TECHNOLOGY REVIEW 11 References 1. Ericsson Mobility Report, November 2018, available at: https://www.ericsson.com/en/mobility-report/ reports/november-2018 2. Academic Press, Cellular Internet of Things: Technologies, Standards and Performance, 1st edition, 2017, O. Liberg, M. Sundberg, E. Wang, J. Bergman, J. Sachs 3. IEEE Network, volume 31, issue 6, Overview of 3GPP Release 14 Enhanced NB-IoT, November/December 2017, A. Höglund et al. 4. IEEE Communications Standards Magazine, volume 2, issue 2, Overview of 3GPP Release 14 Further Enhanced MTC, June 2018, A. Höglund et al. 5. IETF, June 2018, LPWAN Static Context Header Compression (SCHC) and fragmentation for IPv6 and UDP, available at: https://tools.ietf.org/html/draft-ietf-lpwan-ipv6-static-context-hc-16 6. IETF, October 2018, QUIC: A UDP-Based Multiplexed and Secure Transport, available at: https://tools.ietf. org/html/draft-ietf-quic-transport-15 7. IETF, August 2018, Object Security for Constrained RESTful Environments (OSCORE), available at: https://tools.ietf.org/html/draft-ietf-core-object-security-15 8. IETF, June 2014, Hypertext Transfer Protocol (HTTP/1.1): Message Syntax and Routing, available at: https://tools.ietf.org/html/rfc7230 9. IETF, June 2014, The Constrained Application Protocol (CoAP), available at: https://tools.ietf.org/html/ rfc7252 10. IETF, May 2015, Hypertext Transfer Protocol Version 2 (HTTP/2), available at: https://tools.ietf.org/html/ rfc7540 11. IETF, August 2018, Sensor Measurement Lists (SenML), available at: https://tools.ietf.org/html/rfc8428 12. OMA SpecWorks, Lightweight M2M (LWM2M), available at: https://www.omaspecworks.org/what-is-oma- specworks/iot/lightweight-m2m-lwm2m/ 13. W3C, October 21, 2018, Web of Things (WoT) Thing Description, available at: https://www.w3.org/TR/wot- thing-description/ 14. IETF, Software Updates for Internet of Things (suit), available at: https://datatracker.ietf.org/wg/suit/about/ 15. Intel, October 15, 2018, Intel and Arm Share IoT Vision to Securely Connect Any Device to Any Cloud, Lorie Wigle, available at: https://newsroom.intel.com/editorials/intel-arm-share-iot-vision-securely-connect- any-device-any-cloud/ 16. Ericsson Technology Review, April 2017, Tackling IoT complexity with machine intelligence, available at: https://www.ericsson.com/en/ericsson-technology-review/archive/2017/tackling-iot-complexity-with-machine- intelligence 17. Ericsson white paper, May 2018, Artificial intelligence and machine learning in next-generation systems, available at: https://www.ericsson.com/en/white-papers/machine-intelligence
  12. 12. ✱ MASSIVE IoT DEVICES 12 ERICSSON TECHNOLOGY REVIEW ✱ JANUARI 9, 2019 theauthors Claes Lundqvist ◆ serves as director of Technology Foresight at Ericsson Group Function Technology. He joined Ericsson in 1996 and has held various positions in R&D and product management, working with technology platforms for mobile devices. His current work focuses on the technology management area, including technologies for mobile devices and the IoT. He holds an M.Sc. in electrical engineering from KTH Royal Institute of Technology in Stockholm, Sweden. Ari Keränen ◆ is an expert in IoT standards and protocols at Ericsson Research in Finland.. He joined the company in 2007 and has since worked with various internet technologies ranging from multimedia signaling and peer-to-peer systems to the IoT. He holds an M.Sc. in communications engineering from Aalto University in Helsinki, Finland. Ben Smeets ◆ is a senior expert in trusted computing at Ericsson Research. He holds a Ph.D. in information theory from Lund University, Sweden, where he also serves as a professor. He joined Ericsson Mobile Communications in 1998, and started out working on security solutions for mobile phone platforms. Smeets is currently working on trusted computing technologies in connection with containers and secure enclaves. John Fornehed ◆ joined Ericsson in 1991 and currently serves as an IoT expert and technical director. He spent many years in Japan, where he was responsible for strategic accounts with mobile operators, among other things. Fornehed’s current work includes serving as an evangelist on IoT device life-cycle management, including secure IDs, for both industry and academia. Carlos R. B. Azevedo ◆joinedEricssonResearch’s Brazilian team in 2015. He currently serves as an MI and IoT technologies researcher at Ericsson Research in Stockholm, where he designs the architecture of intelligent, anticipatory and situation- aware systems. He holds a Ph.D. in electrical engineering from the University of Campinas in Brazil. Peter von Wrycza ◆ joined Ericsson in 2011 and has held different positions in the areas of 3GPP standardization, 5G research and the IoT. He currently serves as head of IoT Technologies Research at Ericsson Research, where he drives the research, development and standardization activities for the IoT. Von Wrycza holds a Ph.D. in telecommunications from KTH Royal Institute of Technology in Stockholm.
  13. 13. ISSN 0014-0171 284 23-3324 | Uen © Ericsson AB 2019 Ericsson SE-164 83 Stockholm, Sweden Phone: +46 10 719 0000

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