The document discusses six technology trends seen by the author that will shape the future network platform for innovation. It summarizes two key trends: 1. The Internet of Skills and cyber-physical systems (CPSs), which will require the network platform to support high-quality, remote interactions between humans and things with low latency and bandwidth demands. 2. Distributed compute and storage, ubiquitous radio access, security assurance and zero-touch networks, which the author sees as four crucial technology areas that will drive the evolution of the future network platform.

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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 ✱
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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.

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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.
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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.
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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

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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.