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GLOBECOM, Dec. 2016

BySedef Savas

NetworksLab,April14,2017

ControlPlane MappingProblem

Forhighresiliencyà solvecontrollerplacement(bothnumber&placement.)

CPaffectsalloftheresiliencedisciplines

• survivability(asasupersetoffaulttolerance),

• dependability(asasupersetofreliability),

• security,

• performability,

• traffictolerance,and

• disruptiontolerance.

Focus isonthecontrollers’failureswhiletakingintosomefactorswhicharemissinginexistingworks

suchasflowsetuplatency,switches’demands,andthecapacityofthecontrollers.

RelatedWork

A.ControllerPlacementRound-trippropagationlatency,calculatedbyusingthe lengthoftheshortestpathbetweens-c

• FacilityLocationProblem(FLP)

• Capacitatedk-centerproblem:positioningthecontrollerstominimizethepropagation

latencywhileconsideringcapacityofthecontrollersanddemandoftheswitches.

• Pareto-basedOptimalCOntroller (POCO)placementframeworkprovidespareto-optimal

placementswithregardtodifferentmeasures,includingswitch-controllerlatency,

controller-controllerlatencyandcontrollerloadimbalance

RelatedWork(cont.)

B.ResilientControllerPlacementMainlyconcernedwithresilient controllerplacement toimprovetheresilience ofthesouth-

boundconnections(controller-switchconnections)inSDN,resilient controllerplacement to

enhance theresilience ofthecontrolplane(dealingwithcontrollernodefailures).

FaultTolerantControllerPlacement (FTCP)problemtoachievehighsouth- boundreliability. Inthe

proposedformulation,eachswitchisrequiredtosatisfyareliability constraintinawaythatthe

operationalroutetoanyofitsconnectedcontrollersremainswithatleastagivenprobability.

Thesimulationoutcomeofapplyingtheproposedheuristicalgorithmtoseveralnetwork

topologies,demonstratedthatbeingconnectedtotwocontrollerssufficesforeachswitch.[*]

[*]F.J.Ros andP.M.Ruiz,“FiveNinesofSouthboundReliabilityinSoftware-definedNetworks,”inProceedingsoftheThirdACMSIG- COMMWorkshoponHotTopicsinSoftwareDefinedNetworking,2014,pp.31–36.

ProblemDefinition

Tomeettheresilience constraintsaswellastoaddresstheperformance(mostly relatedtothepropagation

latency),thecost,andcapacitylimitation.

• Costlimitations areassociatedwiththenumberofrequiredcontrollersorhavingabudgetinterms

ofthethenumber ofcontrollerinstances, andtheinherentcostofdeployments (e.g.,CAPEX and

OPEX).

• Also, thecapacityconstraintsassistindealingwiththeloadonacontroller(CPU,memory,and

accessbandwidth).

Ifcontrollerbecomesoverloaded, processing latencywillgoup,affectthelatencybetweenaswitchandthe

controller(itbecomesanon-negligible partofthetotallatency).

Moreover,overloaded controllershaveahigherprobability offailure[6].

Assumptions

Allnodesaresuitableforcontrollerdeployment.

Switcheshavecertainload,controllershavecertaincapacity.

Allcontrollershaveauniformfailureprobabilityandtheyfailindependently.

Multi-levelbackupcontrollerlist

Objective:minimizetheswitch- controllerre-assignmentcostsafterthe

possiblecontroller(s)’failures.InRCP,rdenotestheresiliencelevelatwhicha

controllerservesagivenswitch.

Forinstance,r=0indicatesaprimaryassignmentofacontrollertoaswitch,

andr=1denotestheassignmentofthefirstbackupcontrollertoaswitch.

Todocapacitymanagementafterthereassignment– reassignseveryswitch.

PerformanceEvaluation

Networktopologies ofUScontinentaltier- 1serviceprovidersobtainedfromthe

InternetTopology Zoo.

PointofPresence(PoP)-leveltopologies areSprint,ATTNorthAmerica(twomaps,one

before2008andanotherin2008),PSINeT (nowpartofCogentCommunications), and

UUNET(nowpartofVerizonBusiness).

CostofaController

Thehigherthedegreeofapotentialnode(location)forthecontroller,the

lessthecostis.

• nodeswithbetterconnectivityarereachablefrommorenodes,and

placingthecontrollersonsuchnodesmostprobablydecreasesthe

costintermsofthenumberofcontrollers.

In-bandcontrol,i.e.,nodedicatedlinksbetweencontrollersandswitchesfor

controltraffic.Also,shortest-pathlengthbetweenaswitchandacontrolleris

thesumofthepropagationlatenciesofallthelinksalongthepath.

3scenarios

1) homogeneous switches(i.e.,switcheswithhomogeneous demandsequalto500kiloreq/s)

andcontrollers(i.e.,controllerswithhomogeneouscapacitiesequalto5,000kiloreq/s).

Theprobabilityofthenodefailure(i.e.,pf)isassumedtoberandomlychosenfrom[0.010.25]

2)Thecorrespondingdemandsoftheswitchesareconfiguredwiththeminimumandmaximum

valuesof150kiloreq/sand1,000kiloreq/s(withstepsizeof50),respectively.Thecapacitiesof

thecontrollersandpfarethesameasthefirstscenario.

3)demandsoftheswitchesareuniformlydistributedin[2001,000]kiloreq/sandcontrollers’

capacitieshavevaluesin[1,8008,000]kiloreq/swithfixedpfas0.05.

Results

1)numberofassignedcontrollers,

2)propagationlatencybetweens-c,

3)controllerlocationsatdifferentresiliencelevels,and

4)distributionoftheloadsamongthecontrollers.

It can be seen that having a higher resilience

level is more cost-effective (in terms of the

number of required controllers) for the UUNET

which has larger network size as well as more

redundant paths and higher node degree

Regardlessoftheassignedprobability offailuretothenodes, thenumber of

requiredcontrollersarequitesimilarinthefirstandsecond scenarios.

Results(1)- #ofassignedcontrollers

Results(2)

Propagationlatencyasthemaincontributortotheflow-setuplatency

• thedistancebetweeneachtwonodesanapproximationoftheair-line

distance.Notactualfiberlengthsusedinashortestpath.

• Thepropagationlatencythreshold(ontheshortestpath)fromaswitchto

itsassignedcontrolleratanyresiliencelevelisassumedtobe250ms

Considering thehighestresiliencelevel(i.e.,m=2),themaximumpropagation

latenciesforallofthetopologies arebelow50ms,whichisfarlessthanthe

latencythreshold andleavestheroomforothercontributorsoftheflow-setup

latency,including transmission delay,processing delayandprobably thedelay

incurredbycongestioninthenetwork.

Result(2)cont.

In most cases, when the resilience level isincreased (e.g., from m = 0 to m = 1), themaximum latency between a switch and itsassigned controller in a topology goes up.

But this is not always the case; for scenario 3and ATT NA (2), the maximum latencydecreases when the resilience level increasesfrom 1 to 2 in the second experiment.

Results(3)- Controllerlocation

Due to their higher connectivity (higher node degree) and subsequently, better reachability from other nodes. This is reflected by our assumed location-dependent deployment cost (fc) which increases in inverse proportion to the node degree.

Kansas City (common in all scenarios) has a strategic location in most of topologies since it connects east and west of the US in the maps.

Results(4)– controllerloaddistribution

4-tuple shows the minimum, maximum, mean and standard deviation for the number of switches managed by the controllers in a given topology.

While increasing the resilience level results in more load imbalance for some topologies in different scenarios, it leads to less load imbalance for the others. This again confirms the reliance of the solution on the network topology.

Conclusion

Resilientcontrollerplacementproblem, takesintoaccountthecapacityofthe

controllersaswellasthedemandsoftheswitches.

Minimizing thetotalcost(including thecostofdeployment,thepropagationlatency,andthenumberofrequiredcontrollers)achievedwhileconsideringdifferentresiliencelevelstoenhancetheresilienceofthecontrollerplane.

Futureresearchdirections involvedesigning heuristic/approximationalgorithms to

dealwithlargenetworksizesaswellastestingmorerandom/synthetictopologies to

gainusefulinsightsontheresults.