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Ericsson Technology Review - Technology Trends 2019

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Six key trends manifesting the platform for innovation.

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Ericsson Technology Review - Technology Trends 2019

  1. 1. 1 OCTOBER 8, 2019 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ OCTOBER 8, 2019 2 ✱ CTO TECHNOLOGY TRENDS 2019 CTO TECHNOLOGY TRENDS 2019 ✱ six key trends manifesting the platform for innovation TECHNOLOGY TRENDS 2019 Affordable and efficient connectivity is a fundamental component of digitalization and has become as important as clean water and electricity in creating a sustainable society of the future. Recognition of this fact is of critical importance as we enter a new era that is defined by the combinatorial effects of a multitude of transformative technologies in areas such as mobility, the Internet of Things (IoT), distributed computing and artificial intelligence (AI). Theuniversalconnectivitynetworkthat weusetodayisbuiltonvoiceandmobile broadbandservicesthatcurrentlyserve 9billionconnecteddevicesglobally. Thistechnologyisrecognizedand acknowledgedforitsavailability,reliability, integrityandaffordability,anditistrusted tohandlesensitiveandimportant information.Today’snetworkprovides pervasiveglobalcoverageonascalewith whichnoothertechnologycancompete. Ithasquicklybecomeamultipurpose network,readyandabletoonboardall typesofusers,aswellassupportingalarge numberofnewusecasesandaplethoraof newtechnologiestomeetanyconsumer orenterpriseneed.Assuch,itisideally suitedtoserveasthefoundationforfuture innovationinanyapplication. APPROPRIATEANDUNIVERSAL CONNECTIVITY Themultipurposenetworkissignificantly morecost-efficientthanspecializedor dedicatednetworksolutions,makingit themostaffordablesolutiontoaddress society’sneedsacrossthespectrum fromhuman-to-humantohuman-to-thing andthing-to-thingcommunication. Itsupportseverythingfromtraditional voicecallstoimmersivehuman-to-human communicationexperiences.Intermsof human-to-thingcommunication, itenableseverythingfromdigital paymentstovoice-controlleddigital assistants,aswellasreal-timesensitive dronecontrolandhigh-qualitymedia streaming. WithregardtoIoTcommunication,the ubiquitousconnectivityprovidedbythe multipurposenetworkenablesthe creationofaphysicalworldthatisfully automatedandprogrammable.Examples ofthisincludemassivesensormonitoring, fullyautonomousphysicalprocessessuch asself-drivingcarsandmanufacturing robots,aswellasdigitally-embedded processessuchasautonomousdecision- makingintaxreturns. KEYTECHNOLOGYTRENDS Inmyview,theongoingevolutiontoward thefuturenetworkcontinuestorely heavilyonthefivekeytechnologytrends thatIoutlinedinlastyear’strendsarticle. Therefore,inthisyear’stechnologytrends article,Ihavechosentobuildonlastyear’s conclusionsandsharemyviewofthe futurenetworkplatforminrelationtothose fivetrends,withoneaddition:distributed computeandstorage. BY: ERIK EKUDDEN, CTO ✱ CTO TECHNOLOGY TRENDS 2019 CTO TECHNOLOGY TRENDS 2019 ✱ 1 2
  2. 2. 3 OCTOBER 8, 2019 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ OCTOBER 8, 2019 4 ✱ CTO TECHNOLOGY TRENDS 2019 CTO TECHNOLOGY TRENDS 2019 ✱ TREND#1: INTERNETOFSKILLS TheInternetofSkillshasthepotentialto bridgethegeographicaldistancebetween humansaswellasbetweenhumansand things.Ahighqualityofexperience(QoE) isessentialtocreateimmersive interactionsthatallowhumanstoattend meetingsremotelywiththesameabilityto participateasiftheywerephysically present.Humanshavetotrustthe networktoenablecriticalremote operationsandinteractionwiththings. Self-drivingvehicleswillrequirea remotepersontotakeoverthedriving orsupportinthedecision-makingifthe autonomoussystemfails.Hence,tele- operationofrobotsandvehiclesisneeded atsea,onlandandunderground,aswellas intheair.Remotehumanassistanceisalso requiredfortaskssuchasmaintenance, troubleshootingandrepairingacross industrial,enterprise,healthcareand consumerdomains.TheInternetofSkills alsoappliestotheabilitytoexperience physicalitemsremotelyinapplications suchasonlineshoppingandgaming. High-qualityandefficientcapturing, transmissionandrenderingofvisual,audio andhapticinformationisessentialtothe InternetofSkills.Thisinformationwillbe capturedbymultipledevicesanditmust befusedtogethertobereproducedremotely. Adistributedenvironmentforaccess, computeandstorageofthisinformation isthereforehighlyadvantageous. Hapticcommunicationsrequirelatencies below10msinthemostdemanding scenarios.Largevolumesof3Dvisualdata andhigh-frequencyhapticdataimpose highnetworkbandwidthandlatency demands,bothintheuplinkanddownlink. Anetworkplatformwithlow-latency characteristicsallowsforlargeamountsof datatobequicklytransmittedbetween devices.Thismeansthatmoretimecanbe spentonprocessingandperforming analyticsontheavailableinformationto enhancetheexperience. Securityandprivacyareveryimportant sincethedevicesmaycapturesensitive visual,audioandhapticinformation.This informationcanrelatetotheuserofthe deviceorotherusersthatsharethesame environment,includingdetailed characteristicsoftheuser’sphysical environmentsuchastheirhomeoroffice, aswellasinsightsintotheuser’sdaily activities. Thenetworkplatformwillalsobevery beneficialforenablingthepositioningof devices,bothoutdoorsandindoors.The networkradiopositioninginformationcan befusedwithinformationfromthedevice’s onboardsensorssuchasthecameraand inertialsensors. Demanding use cases exemplified by trends 1 and 2 Today’s networks are transforming into a platform where applications, processes and other technologies are developed, deployed and enhanced. For me, it is fundamental that the platform ensures affordable, reliable and trusted operation. Two use cases that I expect the network platform will need to support are trends 1 and 2: the Internet of Skills and cyber-physical systems (CPSs). PORTSOFTHEFUTURE Terminalportoperationswill increasinglyconsistofamixtureof physicalmachinery,roboticssystems, automatedvehicles,human-operated digitalplatformsandAI-based softwaresystems.Theseelements willtransformfutureportsintoCPSs, creatingadigitalecosystem comprisedofvariousintelligent agentshighlyspecializedinspecific aspectsofcargoloading/unloading andofthelogisticchains. AUTOMOTIVE Allnewfeaturesinmoderncars, suchasadvanceddriverassistance systemsandconnectedvehicle services,arebasedonelectronics andsoftwareratherthanon mechanicalengineeringinnovations. Safety-criticalfunctions,driver- assistancesoftwareandinfotainment applicationswillruninspecificand highlycompartmentalizedonboard modulesthatinteractwithaplethora ofsensorsandactuators.Inthis context,thefuturevehiclewill increasinglytaketheformofaCPS forwhichthepreventionofaccidents isthemaingoal. SMARTMANUFACTURING Thefactoryofthefuturewillbeaset ofinteractingCPSs,wherehighly skilledworkerswillhavedirectinsight intotheoperationsofcoordinated intelligentmachinesfromacentral controlentity.Everyfunctionalaspect ofaproductionchainwillbeaffected –fromdesign,tomanufacturing, throughtosupplychains,andlater extendingtocustomerserviceand support.Thesmartfactorywillbe hyper-connected,data-intensive andhighlysecure. EXAMPLES OF CYBER-PHYSICAL SYSTEMS TREND#2: CYBER-PHYSICALSYSTEMS CPSresultsfromtheintegrationof differentsystemstocontrolaphysical processandusesfeedbacktoadapttonew conditionsinrealtime.Thisisachievedby integratingphysicalprocesses,networking andcomputation.ACPSgeneratesa ndacquiresdata,sothattherelevant elementsinvolvedhaveaccesstothe appropriateinformationattherighttime. Therefore,theCPScanutonomously determineitscurrentoperatingstatus, andcorrectiveactionsarerealizedby theactuators.Informationcomesfrom sensorsandfromotherrelatedCPSs. Theroleofhumansistosupervisethe operationoftheautomatedand self-organizingprocesses. CommunicationisvitalinCPSstoallow differentandheterogeneousobjectsto exchangeinformationwitheachotherand withhumans,atanytimeandinany conditions.Deterministiccommunication (intermsoflatency,bandwidthandreliability) largelyimpactsthedynamicinteractions betweensubsystemsinCPSs.Minimizing thetimeittakestoperformcontroltasks iscriticaltoensuringthatasystem functionscorrectly. Thefuturenetworkplatformshould providethespecificconnectivity performancetoguaranteeCPS-critical requirements.Asanexample,latency criticalityisanissueforallcaseswhere acontrollerorcomplexAImusttake decisionsandactionsinrealtime. EachCPShasaspecificarchitecture thatrequiresanadaptivenetworkplatform. Hence,aspecificad-hocdesignofindoor and/oroutdoorcoverageisrequired. Inaddition,networkslicingwillenable satisfyingheterogeneousconnectivity requirementsonthesamenetwork, foranyindoororoutdoorscenarios.
  3. 3. OCTOBER 8, 2019 ✱ ERICSSON TECHNOLOGY REVIEW 6 CTO TECHNOLOGY TRENDS 2019 ✱ 5 ERICSSON TECHNOLOGY REVIEW ✱ OCTOBER 8, 2019 ✱ CTO TECHNOLOGY TRENDS 2019 MAINCHARACTERISTICS Theinterconnectbetweendifferentkinds ofnetworks,fromlocaltowide-area coverage,buildsaglobalnetworkthat providesaplatformforpervasiveglobal services.Theinherentmobilitywithinand betweenthenetworkscreates unprecedentedcoveragebothindoors andoutdoors.Utilizingallthesenetwork assetsenablesadistributedenvironment foraccess,computeandstorage.These assetsarevirtualized,distributedacross thenetwork,andaremadeavailablewhere theyareneededandaremostefficient. Applicationsandprocessesare dynamicallydeployedthroughout thenetwork.Networkslicingenables streamlinedconnectionsfordifferent applications,enhancingtheefficiency ofthetotalusageofthenetwork. Autonomousdeployment,operation andorchestrationisanessentialcapability ofthenetworkplatformtoenable cost-efficiency.Justasimportantare thereliabilityandresiliencetofulfill expectationsfromindustryandsociety. Built-in,automatedsecurityfunctions protectthenetworkandtheintegrity ofitsusersfromexternalthreats. THENETWORKPLATFORMOFFERING Thenetworkplatformoffersawiderange ofcapabilitiestoallitsusers. Itprovidesaseamlessuniversal connectivityfabricwithalmostunlimited, scalableandaffordabledistributed computeandstorage.Sensorsand actuatorscanbeattachedanywhere throughoutthenetwork.Latencycanbe optimizedbyinteractingwiththecontrol ofaccess,computeandstorage. Embeddedintotheplatformisa distributedintelligencethatsupports userswithinsightsandreasoning. Theaddressabilityandreachability capabilitiesmakeitpossibletoconnect anyoneoranythingregardlessoflocation andtime.Togetherwiththeinherent securityandavailability,thenetwork platformcanalsomeetcommunication needsrelatingtosecureidentificationof usersandnetworks.Italsoprovidesthe scalabilitytoautomaticallyadapttothe exactneedsofindividualusersand applications.Asanexample,adaptive powerconsumptionisenabledbyaflexible airinterface.Anotherexampleisautomated life-cyclemanagementofdevices,users andapplications.Thisguaranteesthemost cost-efficientsolutionforusers,inboththe longandshortterm. Thenetworkplatformofferingis consumedthroughanautomateddigital marketplace.Networkservicesanddata areavailablethroughconsistentandopen businessinterfacesfortheapplications (APIs).Data,suchaslocation,connectivity conditionsanduserbehavior,canbemade availablefromthenetworkplatform. Withallthesecapabilities,thenetwork platformoffersthemostaccessibleand valuablefoundationforfutureinnovation. My vision of the future network platform As I see it, the future network platform is characterized by its capability to instantaneously meet any application needs. It can handle huge amounts of data, scarce amounts of data, and everything in between. It will meet requirements for both open data and sensitive data, as well as all manner of needs related to uplink and downlink transmission. From real-time critical to non-critical, predefined to flexible air interface, preset to adaptive routing – the future network platform has it covered. Anyone and anything that can benefit from a connection should be able to access and use the network. 5
  4. 4. OCTOBER 8, 2019 ✱ ERICSSON TECHNOLOGY REVIEW 8 CTO TECHNOLOGY TRENDS 2019 ✱ 7 ERICSSON TECHNOLOGY REVIEW ✱ OCTOBER 8, 2019 ✱ CTO TECHNOLOGY TRENDS 2019 TREND#3: DISTRIBUTEDCOMPUTE ANDSTORAGE Futureapplicationswillrequirenewpro- cessingcapabilitiesfromthenetworkin ordertoreducetheamountofdatathat needstobecommunicated,providelow latency,andincreaserobustnessandsecurity. Today’sprocessorsandacceleratorswill eventuallyexperiencetheendofMoore’s Law,andnewheterogeneouscomputing solutionswillemerge.Commodity hardwarehasbeenjoinedbyahighly heterogeneoussetofspecializedchipsets –oftenreferredtoasaccelerators–thatare optimizedforacertainclassofapplications. Forexample,data-intensiveapplications suchasmachinelearning(ML)/AIor augmentedreality/virtualrealitycantake advantageofthemassiveparallelization offeredbyGraphicalProcessingUnits orTensorProcessingUnits.Latency- sensitiveapplicationscan utilize computationpatternreuseofferedby eithercustom-designedintegratedcircuits orfield-programmableintegratedcircuits. Thenextstepofheterogeneous computingwillinvolvenewcomputing paradigmssuchasneuromorphic processorsthatyieldlowpower consumption,fastinferenceandevent- driveninformationprocessing.Another emergingtechnologyisphotonic computing.Photonsareusedinsteadof electrons,thusavoidingthelatency oftheelectron-switchingtimes. Quantumprocessor-basedacceleration ofcompute-intensiveandlatency-sensitive algorithmswilleventuallybecomeareality. Byexploitingthequantummechanics principlessuchassuperpositionand entanglement,quantumprocessors promiseexponentialgrowthofcomputing powerforacertainclassofproblems. Theemergenceofuniversalmemories willofferthecapacityandpersistency featuresofstorage,combinedwithby te-addressabilityandincreasedaccess speedofmemory.Programswritten forpersistentmemoriescanremove thedistinctionbetweenruntimedata structuresandofflinedatastorage structures,resultinginfasterstart-up timesandrecoveryincaseoffailover. Advancementsinnon-volatilememory technologieswillbecrucialtomeet strictlatencyrequirements. Theincreasingdisparityofcentral processingunitspeedsversusmemory accessspeedswillleadtomemory-centric computearchitectures.Computeunits willbeembeddedinsidethememoryorthe storagefabrics.Thiswillnotonlyincrease performance,butalsoleadtosignificant energy-efficiencygainsbyreducingthe datamovementoftraditionalcompute- centricarchitectures. Efficientlydevelopingapplications foradistributedcomputeenvironment willrequirenewprogrammingmodels. Programswillbenefitfromseparating theintentoftheapplicationfromthehow Four technologies evolving the network platform: Trends 3-6 In my view, four technology areas are crucial to the evolution of the future network platform, represented by trends 3 to 6: distributed compute and storage, ubiquitous radio access, security assurance and zero-touch networks. 8
  5. 5. 9 OCTOBER 8, 2019 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ OCTOBER 8, 2019 10 ✱ CTO TECHNOLOGY TRENDS 2019 CTO TECHNOLOGY TRENDS 2019 ✱ technologiesandvirtualization,whichare introducingrequirementsforcontinuous complianceverificationinadynamic environment.Atthesametime,security assuranceneedstoberootedinthe evidencecollectedinthenetworkslices supportingdifferentindustries.AIandML technologieswillbringautomationof assuranceandcomplianceverificationto thenetworkplatform. Intheworldofcloudcomputing,enclave andconfidentialcomputinghardware solutionsthatprovidearootoftrustare currentlybeingpackagedinpre-commercial cloudsolutions.Thesetechnologieshave thepotentialtobecomeprevalentwhen addressingsecurityconcernsfor processinginthecloud.Conceptually similartrustedcomputingtechnologies arealsomovingintoIoTdevices. Thetrendtowardencryption everywherecontinueswithreports ofupto90percentusageofHTTPS. Asubstantiallydifferentprotocolstackon theinternetisexpectedinafewyears,with QUICandDoHasthedominantprotocols, protectedbynewlystandardizedpost- quantumalgorithms.Sincecurrent securityprotocolsarenotsuitedfor constrainedIoTnodesanddevices,the industryisworkingtostandardizenew lightweightapplicationlayerprotocols. Atthesametime,remotelymanaged eUICC(embeddedUniversalIntegrated CircuitCard)basedSIMidentitiesinIoT devicesareincreasinglybeingdeployed fornetworkaccess.ModernSIMsbased ontheeUICC,andlatertheevenmore cost-effectiveiUICC(integratedUniversal IntegratedCircuitCard),willformthetrust anchorsforsecureidentitiesandnetwork accessinfivetosevenyears. Mission-criticalusecasesandregulatory demands,aswellascloudandedge computing,arethedrivingforcesbehind thetrustandassurancetechnologiesthat arebeingdevelopedandbecoming integralpartsofthenetworkplatform. TREND#6: ZERO-TOUCHNETWORKS Azero-touchnetworkiscapableofself- managementandiscontrolledbybusiness intents.Data-drivencontrollogicmakesit possibletodesignthesystemwithoutthe needforhumanconfiguration,aswellas toprovideahigherdegreeofinformation granularity.ApplyingAItechnologieswill enablezero-touchautomationofnetwork life-cyclemanagement,includingoptimizing systemperformance,predictingupcoming faultsandenablingpreventiveactions. Theperformanceofadata-driven zero-touchfunctioncanincreaseby utilizingthewidernetworkdatafrommany localclients,butthisneedstobebalanced againstthecostandtimeassociatedwith transferringlargevolumesofdata. OneapproachistodesigndistributedML solutions,suchasfederatedlearning,which makesitpossibletogenerateanetwork- wideglobalMLmodel.Trainingisdoneon localclients,andtheneedtotransferdatais limitedtomodelupdates,insteadofrawdata. Withreinforcementlearning,itis possibletodesignasolutionthatresponds tounforeseenenvironments,whichcanbe usedtoautomateoroptimizeaspecific process.Areinforcementlearningagent learnshowtoactoptimallygiventhe systemstateinformationandreward function,focusingonfindingabalance betweenexplorationofunchartedterritory andexploitationofcurrentknowledge. Therequirementsonreliabilityandsafety will,however,setlimitsontheapplicability. Robotsareusedtointerfacewiththe networkinfrastructure,collaboratewith humansandutilizeAItoperformphysical inspections,determinefaultcauses, predictfuturefaultsandplanmaintenance work.Computer-visiontechniquesenable, forexample,automatedcelltower inspection,whilemachinereasoningis usedtoplanandexecutedroneflight. Techniquestogeneralizeandtransfer lessonslearnedcanbeusedtoincrease performancefromonetowerinspectionto another.TheseAI-basedrobotsystems willcollaboratewithhumans,thereby increasingtheirsafetyandefficiency. Anintent-basedapproachsimilartothe onereferencedintrend3(distributed computeandstorage)allowshumanusers tointeractwiththeAIsystemthatispartof zero-touchapplications.Domainmodeling, knowledgerepresentationandreasoning (togetherwithML)areusedtocreatea cognitivelayerforhumanstointeractwith thesystemusinghigh-levelintents. Thesystemiscapableofevaluatingand executingstrategiesinlinewithanintent, basedonlower-levelkeyperformance indicator(KPI)predictions.Bycomplementing MLwithmachinereasoning,thesystem canbedesignedtoexpresswhycertain decisionsweretakenandisawayto implementexplainableAI. TrustworthyMLmodelsthatfulfillzero- touchaspectsneedtobebuiltinlinewith theneedforprivacyandlegislativerules forhowdatacanbeexposedormoved. Newspecializedhardwareforaccelerating MLtrainingandinferencewillimprove performanceandreduceenergy consumptioninawell-designedzero-touch networkplatform.RecentprogressinAI hasshownnewpromisingpossibilitiesto designforzerotouch.Manychallengesneed tobeovercome,however,andthevalue andefficiencyoftraditionallydesigned controllogicshouldnotbeunderestimated. andwhereofthephysicalnetwork. Today,intent-basednetworkinguses ServiceLevelAgreementsandpolicies todefinetheintentofnetworkoperations. Thenetworkconfigures,monitorsand troubleshootsissuesinthenetworkto fulfilltheseintents.Inthefuture,therewill bemorecloudservicesmanagedbyintent- basedoperationstoevolvetowardmore advancedautomation. Thenetworkplatformwillbenefitfrom theseamlessintegrationofspecialized computeandstoragehardwaretoboost performanceforawiderrangeof emerging,complexapplications. Theadvancedcomputeandstorage capabilitieswillbemovedtotheedgeof thenetwork,closertowherethedatais generated.Further,thenetworkwillbe abletosupportdeveloperswithefficient andtransparentprogrammingmodels. Edge-nativeapplicationswillbedesigned fromthegrounduptofullycapitalizeon computeandstorageresourcesanywhere. TREND#4: UBIQUITOUSRADIOACCESS Improvedindoorcoverage,maximal energyefficiency,fiber-likeperformance andsupportforbothsmallcellsandawide rangeofnewusecasesarekeyfeaturesof the5Gnetworksthatarecurrentlybeing rolledout.Thesenetworkswillbethe baselineforfutureradionetworksand thenetworkplatformitself. Futurewirelessaccessnetworkswill consistofawiderangeofdifferenttypesof nodesjointlyprovidingwirelessaccess coverage.Deviceswillinmanycaseshave simultaneousconnectivitytomultiple networknodes,includingdifferentaccess technologies,forenhancedperformance andreliability.Wirelesstechnologywill alsobeusedfortheconnectivitybetween thenetworknodes,asacomplementto fiber-basedconnectivity. Networkcoveragewillbefurther extendedbymakinguseofintermediate devicestoforwarddatatodevicesoutside thecoverageofthebasicnetwork.Device cooperationcanbeusedtocreatevirtual largeantennaarraybycombiningthe antennasofmultipledevices,which requirestightsynchronization.Asthe networkisbecomingincreasinglydense withagreateramountofsmalllow-power networknodes,andwithdevices contributingtotheoverallconnectivity,the borderbetweendevicesandnetwork nodesmaybemorediffuse. Keytothemanagementofthiskindof massiveheterogenousnetwork,withamuch moremesh-likeconnectivity,willbethe developmentandutilizationofadvanced AIfunctionality.Thiswillenablethenetwork toevolveandadaptovertimetonewrequire- mentsandchangesintheenvironment. Operationabove100GHzwillenable terabit-per-seconddatarates,although onlyfortrulyshort-rangeconnectivity. Therearecurrentlyimplementation challengesforthisfrequencyrange,such ashowtogeneratesubstantialpowerand theheatdissipation,consideringthe inherentlysmalldimensionsofthe components,includingantennas.The extensiontohigher-frequencyoperation anduseofbeam-formedtransmissionswill enableenhancementsinspectrumsharing. InthehigherlayersofRANsandcore networks,theevolutiontowardcloud- nativeimplementationandautomation continues.Networkinterfacesaremoving awayfromtraditionalpoint-to-point interfacestowardmoreservices-based applicationinterfacesdecoupledfrom underlyingtransportconnections. Cloud-nativeimplementationofstateless networkfunctionsuseexternalcontext storageforredundancyandcontext managementfordifferentevents, suchascontextrelocationwhenmobile. Beyondtheprimarytaskofproviding wirelessconnectivity,theradio-access infrastructurewillalsobecapableof deliveringotherservices.Thisisalready happeningtoday,inpart,withtheintroduction oflocation-basedservicesasacomplement toGPS.Thecombinationofhigh-frequency bandnetworksanddensedeploymentswill makeitpossibletodramaticallyenhance theaccuracydowntosub-meterlevel. Otherserviceexamplesincludetime synchronization,time-sensitivenetworking, thecollectionofcomplementary informationaboutlocalweather conditionsandthecreationofradar-like scansoftheenvironment. TREND#5: SECURITYASSURANCE Theneedforprotectionandassurance (orevencompliance)isgrowingrapidly asbusinessandsocietyincreasinglyrely onuniversalconnectivityandcompute. Today,thereisintenseactivitytoexplore thepotentialofAIandMLtoprotectsystems andnetworks.Thereislarge-scale adoptionofthesetechnologiesinareas suchasnetworkthreatdetectionand threatintelligenceextraction,whileother areassuchascontinuousauthentication appearlessmature.WhileAItechnologies canprovideawiderangeofbenefits,itis importanttonotethattheycanalsobe usedbyadversariestofindavenuesof attackthatspecificallytargetMLsystems. Intheseautonomousnetworks,security assuranceproceduresplaytheimportant roleofverifyingsecuritypropertiesofthe networkplatform.Onechallengeliesinthe networkarchitectures,basedoncloud
  6. 6. 11 OCTOBER 8, 2019 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ OCTOBER 8, 2019 12 ✱ CTO TECHNOLOGY TRENDS 2019 CTO TECHNOLOGY TRENDS 2019 ✱ Muchmorecost-efficientthanspecialized ordedicatednetworksolutions,thenetwork platformisclearlythemostaffordable solutiontoaddresssociety’sneedsacross thespectrumfromhuman-to-humanto human-to-thingandthing-to-thing communication.Oneofitsmajor advantagesisthatitisavailablethrough anopenmarketplacethatisaccessibleto anyone,anywhere,atanytime. Themultipurposenetworkisrapidly emergingasasecure,robustandreliable platformwhereapplications,processes andothertechnologiescanbedeveloped, deployedandmanaged.TheInternetof Skillsandcyber-physicalsystems– trends1and2–areimportantexamples ofusecasesthatitneedstosupport. Akeycharacteristicofthefuture networkplatformwillbeitsabilityto instantaneouslymeetanyapplication need,anytime.Fourtechnologyareas– trends3-6–areplayingcriticalrolesinits ongoingevolution:distributedcompute andstorage,ubiquitousradioaccess, securityassuranceandzero-touch networks. Self-drivingvehicles,intelligent manufacturingrobotsandreal-timedrone controlarejustafewexamplesofthe myriadofwaysinwhichthemultipurpose networkisenablingtheautomationofthe physicalworldand,ultimately,thecreation ofasustainablesocietyofthefuture. CONCLUSION ◆ As Group CTO, Erik Ekudden is responsible for setting the direction of technology leadership for the Ericsson Group. His experience of working with technology leadership globally influences thestrategicdecisionsandinvestmentsin,forexample,mobility,distributedcloud,artificialintelligence andtheInternetofThings.Thisbuildsonhisdecades-longcareerintechnologystrategiesandindustry activities.EkuddenjoinedEricssonin1993andhasheldvariousmanagementpositionsinthecompany, including Head of Technology Strategy, Chief Technology Officer Americas in Santa Clara (USA), and Head of Standardization and Industry. He is also a member of the Royal Swedish Academy of Engineering Sciences and the publisher of Ericsson Technology Review. ERIK EKUDDEN SENIOR VICE PRESIDENT, CHIEF TECHNOLOGY OFFICER AND HEAD OF GROUP FUNCTION TECHNOLOGY No other technology in the world today can provide pervasive global coverage on a scale comparable to that of the network platform, and it is my firm belief that it is ideally suited to serve as the innovation platform for both current and future applications. The technology evolution characterized by this year’s trends points toward the future definition of 6G.

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