Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.

Ericsson Technology Trends 2017 / Technology trends driving innovation

912 Aufrufe

Veröffentlicht am

Our industry has an increasingly important role to play in creating the foundation for new business in a broad range of industry sectors in countries all around the world. As Ericsson’s new Chief Technology Officer, it’s my job to keep track of technological advancements on the horizon and leverage them to create new value streams for society, consumers and industries. The challenge is timing, and to see new things in the context of the present without losing sight of history.

I have selected the five trends presented here based on my understanding of the ongoing transformation of the industry, including rapid digitalization, mobilization and continuous technology evolution, and how they affect the future development of network platforms – one of the essential components of the emergent digital economy. At Ericsson, our role is to keep these top trends in sight to guide our innovation, test our limits and ultimately create a thriving market for the next generation of technology.

Veröffentlicht in: Technologie
  • Als Erste(r) kommentieren

  • Gehören Sie zu den Ersten, denen das gefällt!

Ericsson Technology Trends 2017 / Technology trends driving innovation

  1. 1. 2 #02, 2017 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ #02, 2017 3 STANDARDIZING NARROWBAND ✱TECHNOLOGY T R E N D S ✱✱ TECHNOLOGY T R E N D S technology trends driving innovation Our industry has an increasingly important role to play in creating the foundation for new business in a broad range of industry sectors in countries all around the world. As Ericsson’s new Chief Technology Officer, it’s my job to keep track of technological advancements on the horizon and leverage them to create new value streams for society, consumers and industries. The challenge is timing, and to see new things in the context of the present without losing sight of history. I have selected the five trends presented here based on my understanding of the ongoing transformation of the industry, including rapid digitalization, mobilization and continuous technology evolution, and how they affect the future development of network platforms – one of the essential components of the emergent digital economy. At Ericsson, our role is to keep these top trends in sight to guide our innovation, test our limits and ultimately create a thriving market for the next generation of technology. → #1 AN ADAPTABLE TECHNOLOGY BASE Blending technologies in new ways to unleash next generation computational networks #2 THE DAWN OF TRUE MACHINE INTELLIGENCE (MI) Moving from cognitive MI toward augmented human intelligence #3 END-TO-END SECURITY AND IDENTITY FOR THE INTERNET OF THINGS (IOT) A holistic approach to trust in all dimensions #4 AN EXTENDED DISTRIBUTED IOT PLATFORM Acceleration toward a distributed and connected IoT platform #5 OVERLAYING REALITY WITH KNOWLEDGE Immersive communication that ties user experience to the physical world 21 by erik ekudden, cto – five to watch
  2. 2. 3 ✱ TECHNOLOGY T R E N D S TECHNOLOGY T R E N D S ✱ 4#02, 2017 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ #02, 2017 T O R E L E A S E the full potential of the digital economy, the underlying technology components will rely on a symbiotic evolution in the software and hardware dimension. It is in the lowest layers of the technology stack – at the intersection between software and hardware – where more powerful and flexible solutions will become available, enabled by virtualization technologies and horizontal architectures. ARCHITECTURALADJUSTMENTS AHEAD Geometricalscalinghaslongbeenthe mainpathforthetransistortechnology evolutionbutextensiveresearchis currentlyunderwaytofindalternative methodstoincreasetransistor performance.Significanteffortsare beingputintobuildingmoreadvanced architecturalstructures,suchasvarious typesofnon-monolithicintegration technologies,toincreaseintegration andtherebymaintaintheperformance evolutiontrack. Inthecomputingdomain,the dominatingCPU architecture trendismassivemulticoretomeet parallelprocessingdemands.With moreprocessorsonachip,memory architecturesanddatatransferwill becomekeytechnologiesinhardware. Non-volatilememoryandintegrated siliconphotonicswillreachmaturity andchangetheentirememory/storage hierarchy.Thenewtechnologiesare expectedtohavesignificantlyhigher performanceaswellaslowerlatencyand energyconsumption. Tofurtherenhancecomputational powerandperformanceindatacenters, specializedresourcessuchassmart networkinterfacecontrollers,general purposegraphicsprocessorsandfield programmablegatearrayswillbemade availableforvirtualapplicationsthrough abstractions.Asimilarco-processing architecturalapproachcanbeexpected forquantumcomputing. Therapidadvancesofbasecomponents willmeanthatthefirstexascalesystemswith computingpoweratdoublethecapacityof today’stop500computerscombinedcanbe expectedwithinfiveyears. Incombinationwithspecifictypes ofalgorithmsandapplications,these technologyshiftscouldprovetobe disruptive. SPURRINGINNOVATIONTHROUGH ALGORITHMEVOLUTION Massivedatacollectionfrom,forexample, IoTsensorswilldrivetheneedfornew predictivesoftwarealgorithmsthat alsotakeadvantageoftheincreasingly parallelcomputationalpower.Algorithm developmentwillplayanevenmore significantroleinsoftwaredesign.One exampleisdeeplearning,abranchof machinelearningthatusesalayered algorithmstructuretolearnhierarchical concepts. Theamountofcodeneededtoreach ahigherlevelofcomplexityisverysmall, areductionbyafactorof10ormore, comparedwithtraditionalsoftware systemapproaches.Thistypeofsystem learnsfromexamples:itutilizesageneric algorithmthatusestheexamplestoset parametersinthealgorithmtofitthe particulartaskathand. Reinforcementlearningisatechnology todevelopself-learningsoftwareagents, whichcanlearnandoptimizeonan observedstateoftheenvironmentanda rewardsystem.Thisenablesdevelopment ofself-learningsystemsthatrequire neitherhumaninterventionnorhand- engineered,threshold-basedpolicies. ENABLINGTHEFUTURE COMMUNICATIONSYSTEM Fromaconnectivityperspective,one interestingareaisbeamforminginfuture 5Gnetworks,wheresymbiosisofsoftware andhardwareplaysanimportantrole. Atmm-wavefrequencies,hundredsof antennasandtransceiverchainswork togetherwithadvancedcontrolalgorithms togenerate,formandsteerradiowaves inrealtimetoaccomplishmultiuser MIMO(multiple-input,multiple-output). Eachdeviceisaccessedbyasingleuser dedicatedbeamtooptimizenetworkand usercapacity,efficiencyandquality. AtEricsson,wearecurrentlyinvesting inavarietyofcollaborativeeffortswith academiaandthetechnologyindustry tofosteranopenenvironmentinwhich toshareideasandvisionsthatwillenable themostsuccessfulfuturenetworkfrom bothasocietalandindividualhuman perspective. an adaptable technology base #1
  3. 3. 65 #02, 2017 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ #02, 2017 TECHNOLOGY T R E N D S ✱✱ TECHNOLOGY T R E N D S the dawn of true machine intelligence ARTIFICIAL INTELLIGENCE (AI) first emerged in the early 1950s when symbolic logic and rule-based systems were used to generate logical conclusions. Another important step included artificial neural networks, capable of performing pattern recognition by learning from data through iterative optimization. The advancements in these computational-intense algorithms have progressed in performance and cost through the evolution of computing power, data availability and connectivity. Machineintelligence(MI)combines machinelearningandAImethodsto createdata-drivenintelligent,non-fragile systemsforautomation,augmentation andamplifications.MIisabouttheabilityto augmenthumanintelligence.Humanswill beempoweredbyanecosystemofsharing dataandinsights,withsupportfromdigital assistantsguidingandaugmentinghuman awareness.MIwillcreateanewtype ofautonomouscoachingenvironment wherehumansandmachinescantrain andmentoreachother.Thissituationis comparabletoateacherinaclassroom guiding,mentoring,discussingwithand learningfromthestudents. MIwillhelpusunderstandand accomplishthingsweneverwouldhave discoveredbyourselves.Itestablishesa wholenewfoundationandpotentialfor innovation,withtheabilitytobemuch moreinfluentialthanindustrialization. Human-machinecommunicationwill furtherevolvetowardamultifaceted communicationplatformthatincludes capabilitiessuchassituationandsocial awareness.Adeeperdialoguebetween humansandmachineswillemerge,moving beyondcognitiveintelligencetoward augmentedhumanintelligence. SIMPLICITYTHROUGHANALYTICS ANDAUTOMATION AmongthemanytoolsintheMItoolbox isanalytics–coveringeverythingfrom straightforwardanalyticsovermultiple nodesandpetabytesofdata,tocomplex multidimensionalanalyticsonparallel processorsystems.Today,analyticsis oftenahuman-involvedprocessthat requirestheconsiderationofseveral aspects,includinghowtohandledata volumes,dataspeedandthemultitudeof datatypes. Anexampleofcomplexeventprocess handlingwithamassiveamountofreal- timedataiselectronictrading.Thistype oftooliscapableofhandling,analyzing anddrawingconclusionsbasedupon millionsofmessagespersecond.Froma networkperspective,wewillseethese typesofusecasesfurthersubstantiated bytheevolutionoftheIoT.Connectedcars andothertypesofconnecteddeviceswill comeonline,providingmoreusecases thatrequirereal-timemessagingfroma varietyofdecentralizeddatasources. Jettisonandmetadataareessentialto handlethehugevarietyindatastructuring. Automatingthesetasksisofgreat importancetoanyenterprisewithdigital aspirationsbecausehuman-intense interventionsarenotscalable. Automationisbestdescribedasa closed-loopsystem.Theautomation closedlooprefinessystemintervention dependingonrecordedimpact,with minimallatency.Theinterventionis updatedbasedonfeedbackonthesystem performance.Theclosedloopintroduces thenecessarychangeswithouthuman intervention,basedonperformancegoals definedbyhumans. Weareenteringtheeraofearly enablementofsentientMIthatcanbeused tocreatedigitalattention,agilememory andgoalmanagement. NETWORKEVOLUTIONBRINGS MUCHMORETHANRAWDATA Overthenextdecade,industryandsociety willestablishafoundationofinsight-driven systemsleveragingMItechnologies.New serviceengagementswillemerge,driven bypredictivemodellingandautomated operations.Furthermore,avarietyof deploymentmodelsservingdifferent usecaseswillemerge,suchaspure cloud-nativeapplications,on-premises datacenteroperations,anddistributed deploymentsacrossmultiplesites.All ofthiswillbebeneficialtomanydigital businessesandindustries. Analytics,MIandautomation capabilitieswillbeanintegralpartof futurenetworks,substantiatinginnovation fromnetworkoperationtonewbusiness opportunitieswithintheIoT,forinstance. #2
  4. 4. 87 #02, 2017 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ #02, 2017 ✱ TECHNOLOGY T R E N D S TECHNOLOGY T R E N D S ✱ Thiscomprehensiveapproachincludes end-to-endmanagementofsecurityand privacythatprovidespredictivesecurity insightsand,inmanycases,automated adjustmentsbasedonpolicies.Security andprivacyarenotthingsthatcanbe addedon;theymustbefullyintegrated intodomainsandcomponents,processes, storageandcommunication. ASYSTEMBUILTANDENABLEDBY TRUSTCOMPONENTS Thecomprehensiveapproachtosecurity andprivacywillbebasedonanindustry- wideagreementonhowtosecuretrustin development,deploymentandoperations. Itwillincludesecurityandprivacyenabling developmenttools,alongwithtoolsfor automatedandsecuredeployment.Itwill alsoincludeoperationsthatprovidedirect feedbacktodevelopment,continuous compliancemonitoring,andinmanycases, automated,policy-basedsecurityand privacyorchestrationthatconsidersthe constantlychangingthreat,vulnerability andtrustlandscapes. Inthecomingyears,identity managementtechnologieswill continuetobeinthespotlight–along withtechnologiesthatenabletrustin business-criticaldataandprivacy-related personaldata.Blockchainisanemerging technologythathaspotentialinthis regard. Securityanalyticsandmachine learningtechnologieswillprovidesecurity insightsaboutthreats,vulnerabilitiesand securitystatus.Systemintegritywillbe basedonroot-of-trusttechnologiesthat enabletrustworthyhardwareandsoftware components. Thetrust-enablingsecurityandprivacy technologiesimplementedindevices shouldbecost-effectiveandhighly scalable.Mission-criticalindustriesin particularwillrequirehightrustinsecurity andprivacy,aswellastheabilitytomeet tighttimeconstraints. ACOLLABORATIVEINDUSTRY EFFORT Asapartofthecomprehensivesecurity andprivacyapproach,collaborationin threat,vulnerabilityandtrustexchange willincrease.Differentindustryplayerscan contributetothecollaborationwithintheir areaofexpertise. Greatertransparencywillboosttrust, whichwillinturnboostIoTadoptionand acceleratedigitizationinmission-critical industries.Thecomprehensiveapproach tosecurityandprivacytogetherwith industry-widecollaboration,jointtrusted developmentandstandardizationwillbe essentialtrustenablers.Sincenetwork serviceprovidersarerankedamongthe mosttrustedindustryplayers(accordingto sourcessuchasthe2015AccentureDigital ConsumerSurvey),Ericssoniscommitted tohelpingthemplaythiskey,trust-building roleacrossmultipleindustries.   end-to-end security and identity for the iot #3 WHILE THE IoT is undoubtedly full of promise, there are still concerns about the proper handling of security and privacy, especially within mission- critical industries. Cybersecurity threats are emerging rapidly at the same time as the volume of the connected devices and software is increasing. It is more essential than ever to take a comprehensive approach to security and privacy that ranges from devices and gateways with connectivity to the cloud, IoT platforms and applications; chips to services; and development to operations. The need for industry-wide and cross-industry collaboration must also be taken into account.
  5. 5. TECHNOLOGY T R E N D S ✱✱ TECHNOLOGY T R E N D S 10#02, 2017 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ #02, 20179 Afullpaletteofnewflexibilityisbrought intothemarketaspay-as-you-go/use/ growenablesSMEstoofferfarbetter servicesthantheydotoday.These servicesincludeproactiveandpredictive maintenance,wheretheserviceimproves overtimeasaresultoftheabilitytolearn fromdata. Ericsson’sIoT-relatedengagements rangeendtoend.Forexample,weare examininghowaccesstechnologies canbeoptimizedforvarioustypesofIoT usecasessuchasNB-IoT(NarrowBand IoT)toreducepowerconsumptionand cost.Ericssonisalsoinvestingheavilyin theevolutionofLTEandtheenablement of5Gnetworkstoextendtherange ofaddressableIoTusecasesand applications.Additionally,weareworking tocreatecross-industryengagements suchas5GAAtoconnecttheautomotive andtelecomindustries(includingdevices) todevelopend-to-endsolutionsforfuture mobilityandtransportservices.Itisvital forahealthy,evolvingmarkettohave industry-widestandardsthatreduce fragmentation,whichwouldotherwise hamperIoTmarketadoption. an extended distributed iot platform T H E T E C H N O L O G Y shifts that the IoT brings will transform the technology industry in unprecedented ways. Networks will facilitate transactions, operations, logistics and the like, and simultaneously collect and analyze data, enabled by a cloud- based network infrastructure that connects machines, vehicles and devices. The race is on to develop and expand the capabilities of an industry- wide IoT platform. New business opportunities will be born through cross industry-society engagements. Anindustry-wideIoTplatformwillbemade upofdecentralizeddevicesrangingfrom simplepassivestoautonomousdevices thatareconnectedandcommunicating throughadistributedcloudwitha horizontalapplicationandmanagement platform.Itisadistributedsystem,where insightsareaggregatedfromtheedge towardthecenterandregulatedbypolicy andsecuritysettingsthatarespecificfor eachapplicationandusecase.Thisisa multi-cloudbasedinfrastructure,where acombinationofpublicandon-premise solutionsconnectandserveanytypeof IoT-relatedservicefromnear-productto software-as-a-service. TheIndustrialIoT(IIoT),abranchofthe IoTthatisoptimizedforindustry-specific usecaseswithenterpriseconnectivity, isalsoemerging.Productionflexibilityis enabledbysystemfunctionalitiesthat havebothspecificnomadicandmobility capabilities.Everythingcentersaround differentaspectsoflogistics–notonly fromaphysicalperspectivebutalso aroundinformationflowanddatastreams. Bysettingpolicyroles,networkslices arecreated,definingwhatisallowedfor eachspecificusecase.Securehandlingof informationisessential,sothatdatacan neitherleakinoroutofthesystem. SEMANTICINTEROPERABILITYTO SECUREFUNCTIONALITYGROWTH Devicescomewithdifferentmonitoring, managementandsecurityfunctions. Robotsinwarehouses,forinstance, requirepositiontrackingandcoordination anddeliveryfunctions.Simplehome automationsolutionsusecloud-based applicationsthatarecentrallyconnected tootherinformationflows,suchas weatherforecasts,trafficcamerasand soon.Aconnectedvehiclecloudincludes functionssuchasinfotainment,over theairupgrades,telematics,remote control,vehiclesafetyandsecurity,fleet managementandemergencyservices. Pre-provisioneddevicesareoneof thebuildingblocksthatenableanIoT platformthatcangrowinfunctionalityas newdevicetypesconnecttothenetwork. Thefirsttimethesedevices“wakeup”and connect,theyinformthesystemwhothey are,whattheycanbeusedforandwhat theyarecapableof.Thesystemisfurther enhancedbyzerotouchprovisioning, includingfullyautomateddevicecycle management. Devicesbecomeanintegralpartof thefuturenetworkandincorporate connectivityamongclustersofdevices throughacombinationofwirelessand wiredaccesstechnologies.Thewireless connectionsarebasedonbothwidearea andshortrangetechnologies. SEMANTICAPPLICATIONSAND SERVICESOLUTIONS TheextendeddistributedIoTplatform bringsmajoropportunitiestothebusiness landscapewhenenablingawiderange ofnewdigitalservices.It’salsoamodel thatmovesfromtraditionalheavycapital investmentstowardanoperational- expenses-centricmodel.Thisismanifested throughanadoptionandevolutionofvarious typesof“asaservice”models. #4
  6. 6. 12 #02, 2017 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ #02, 2017 13 TECHNOLOGY T R E N D S ✱✱ TECHNOLOGY T R E N D S 1211 #02, 2017 ✱ ERICSSON TECHNOLOGY REVIEWERICSSON TECHNOLOGY REVIEW ✱ #02, 2017 overlaying reality with knowledge #5 IN THE LAST couple of years, many devices capable of rendering immersive experiences have reached the consumer market. The virtual reality (VR) market has mainly been driven by the gaming industry but the technology has now been picked up by studios and other content creators. Augmented reality (AR), which offers a user experience that connects to the physical location, is also becoming popular. Real-time information is overlaid on whatever the user looks at, which enables the user to understand reality in greater depth. AUGMENTEDKNOWLEDGE VIRTUALLYEVERYWHERE OneexampleofARisatask-baseddigital assistantthatsimplifiescomplextasks withreal-timeguidance.Thistypeof systemisabletoprovidefeedbackassoon asamistakeismadebyanoperatororfield serviceengineer.Thefeedbackhelpsthe practitionerbecomemoreknowledgeable andtakeimmediateactiontofixthe mistake. Anotherpromisingusecasecombines VRandARservices.Inthisscenario,a userisassistedbyaremotetechnicianto solveadifficultproblem.Theusershares areal-timevideoofthesurroundingswith theremotetechnician.Thetechnician analyzesthevideoandinstructstheuser onhowtosolvetheproblembysending audioandoverlaidgraphicstotheuser’s ARglasses. WithintheareaofAR,awiderange ofusecasesemergebesidesremote mentoring.Manypracticalapplications arealsorecognizedindigitalindustrial workplaces,whicharesensor-rich environmentswithnetworkedmachine andcomputationalpoweravailablefor analyticsofsensorandmachinedata. Objectsthatarecurrentlyofflinecan easilybeconnectedandaugmented throughcomputervisiontechnologies. Thisisanextensionofimmersive applicationsinatypicalIIoTscenariothat providesincreasedproductivitythrough improveduptime,qualityandsafety. AdditionalsupporttoolswithinIIoTinclude visualizationofdata,documentnavigation andemployeetraining. PUSHINGTOWARDREALITYPARITY Thetechnologyevolutionforimmersive solutionsrequiresawiderangeoftools andinfrastructure.Thesetoolsinclude displaytechnology,real-timeeyetracking, volumetriccapture,perceptualcomputing forlocationsandsurroundingpositions, bodymovementandmore.High-resolution cameras,microphones,GPS,gyros, connectivity,battery,voiceandgesture controlarealsoexamplesofcomponents includedintheconcept.Compared withtoday’ssmartphones,theobvious differenceiswithintheman-machine interaction. Overthenextdecade,computervision willgetbetterthrough3Dmapping, improvedfieldofview,full-colordepth andholographictechnologies.With improvedcomputecapabilitiescomes reduceddisturbancesfromlatencyand rendering.VRisexpectedtoreachparity withrealityandtherebyenabletrue3D communication. VRandARarecompellingusecases for5Gbecausetheyrequirehighdata ratesandlowlatency.Changeofviewport whenturningtheheadrequireslow latencyortheuserwillsuffervertigo. Motiontophotondelayshouldbeless than20ms.End-to-enddelayandlatency requirementsarekeytoprovidinga pleasantuserexperience.Bandwidth maybecomehigh(fortheuplinkvideo) dependingontheusecase. Unfortunately,thecurrentVR/AR marketisfragmentedwithmanyverticals fordifferentcameras,workflowsand headsets.Toaddressthisissue,Ericsson becameafoundingmemberoftheVR IndustryForum,whichcreatesguidelines andinteroperabilityalongtheentireend- to-endchain.Thescopeistofurtherthe widespreadavailabilityofhigh-quality audiovisualVRandARexperiencesforthe benefitofconsumers.

×