Incremental Planning of Multi-layer Elastic Optical Networks P. Papanikolaou, K. Christodoulopoulos, E. Varvarigos School of Electrical and Computer Engineering, National Technical University of Athens, Greece ONDM 2017 21th International Conference on Optical Network Design and Modeling May 15, 2017 Budapest, Hungary RS1: Elastic Optical Networks High Speed Communication Networks Laboratory National Technical University of ATHENS
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Incremental Planning of Multi-layer Elastic Optical Networks · 2017-05-15 · Incremental Planning of Multi-layer Elastic Optical Networks P. Papanikolaou, K. Christodoulopoulos,
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Emerging elastic optical technology and Software Defined Networking paradigm increaseflexibility, enabling a joint multi-layer operation and short network re-optimization/upgrade cycles:
þ operate the network close to its true capabilities and postpone or avoid investmentsþ multilayer coordination allows more efficient resources usageþ capture traffic dynamicity and technology maturation (depreciation & better technology)
Multi-periodplanningtechniquesTechniqueI(reference):Jointmultilayerplanningwithoutpreviousstate (J-ML)î Dimension each period from scratch (as if period is the initial) – lowest possible cost
TechniqueII:Incrementalmultilayerplanningontopofthepreviousstate(Inc)î Incremental dimensioning with no reconfiguration of transponders & IP equipment(maintain the previous network state)
TechniqueIII:Incrementalmultilayerplanningwithoptimizedadaptationsî Allow but penalize the adaptations from the previous network stateî Study two variations:
ê Allow (for free) IP layer adaptations, forbid optical layer adaptations (Inc-ML)ê Allow IP and allow but penalize optical layer adaptations (J-Inc-ML)
Input• ThenetworktopologyrepresentedbygraphG(V,L).• ThemaximumnumberZofavailablespectrumslots(of12.5GHz)• ThetrafficdescribedbythetrafficmatrixΛ.• AsetBoftheavailabletransponders(BVTs).• A set T of feasible transmission tuples, which represent the
transmission options of the available transponders, with tuplet=(Dt,Rt,St,Ct)indicatingfeasibilityoftransmisionatdistanceDt,withrateRt(Gpbs),usingStspectrumslots,forthetransponderofcostCt.Also,Tbrepresentsthetransmissiontuplesoftransponderb B.
• A set of line-cards represented by H, where a line-card fortransponderb Bisrepresentedbyatuplehb=(Nh,Ch),whereNhisthenumberoftranspondersoftypebthattheline-cardsupports.
• The IP/MPLS router cost, specified by amodular costmodel.WeassumethatanIP/MPLSrouterconsistsofline-cardchassisofcostCLCC,thatsuportNLCCline-cardseach,andfabriccardchassisofcostCFCC,thatsuportNFCCline-cardchassis.
Ý J-ML : the minimum CaPex, as if the network was planned from scratch on each yearÞ Inc: exhibits the worst performance, due to the inability to exploit IP & optical equipment reconfigurations
Ý Inc-ML : exploits reconfiguration capabilities of IP layer to achieve cost savingsÝ J-Inc-ML: exploits reconfiguration capabilities of both layers and achieves even higher cost savings
Inc: Incremental multilayer planning on topof existing state (no adaptation of optical andIP equipment)
Inc-ML: Incremental multilayer planning(allow for free IP layer adaptation, noadaptation of optical layer)
J-Inc-ML: Incremental multilayer planning(penalize IP and optical adaptations)
IllustrativeResults(2/2)
Spectrum UtilizationÝ J-Inc-ML also achieves spectrum savingsThe savings are slightly lower compared to CapExdue to deployment of more regenerators* for Incand Inc-ML*(regenerators provide wavelength conversionpossibilities)
Trade-off betweenthe added equipmentand reconfigurationsbetween consecutivenetwork states
q Challenge: optimize the reconfigurations made together with the minimization of the cost
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ExtendedmodelsWorkinprogress
Short network cycles:þ are able to capture the effects of traffic dynamicity and avoid overprovisioning (smallbutfrequentnetworkupdates)
þ postpone the investments and exploit technology maturation
ONDM 2017
cost vs network upgrade cycles
2-months vs multi-year
network upgrade cycles
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2-months increments12-months increments24-months increments60-months incrementswithout previous state
Conclusionsq Long and independent (between network layers) upgrade cycles lead tocapacity overprovisioning, underutilized equipment and unnecessaryinvestments
q Shorter upgrade cycles and joint multi-layer upgrades increase thenetwork efficiency, operate the network closer to its true capabilities,and postpone or avoid investments
q ILP model that combines multi-layer and incremental planning andtradeoffs:ê the capital expenditure (CapEx) of the added equipment at both layers
ê the reconfigurations for the transition between two consecutive periods