Abstract

With the emergence of cloud services based on data centers, demands for bandwidth-intensive applications have increased dramatically, and application services have transferred to a more diversified direction. Management as well as capacity of the backbone network needs further development to catch up with rapidly evolved application demands. Optical network virtualization can facilitate the sharing of physical infrastructure among multiple network applications. Virtual Network Embedding (VNE), the main implementation of network virtualization, determines how to map a virtual network request onto physical substrate. To expand the network capacity, flexible-grid elastic optical networks have been considered as a promising supporting technology for the future infrastructure of the next-generation Internet. However, due to the expense of key enabling equipment for flexible grid optical networks, the brown-field migration from a fixed grid to a flexible grid gave birth to the co-existing fixed/flexible grid. Based on the co-existing fixed/flexible grid optical networks, we investigate the problem of Virtual Optical Network (VON) provisioning, and present a flexible-grid-aware virtual network embedding algorithm to map the virtual networks onto the substrate network. In addition, the performance of the algorithm was evaluated under four different network scenarios. Simulation results show that the proposed algorithm can achieve better performance in all four scenarios.

Highlights

  • With large-scale deployment of data centers and continuing proliferation of cloudbased applications, traffic has grown dramatically and is imposing a huge demand on network bandwidth

  • Each virtual node requires a certain amount of computing resources from the substrate nodes, while each virtual link requires a spectrum path consisting of one or multiple substrate fiber links between two substrate nodes associated with two virtual nodes [2]

  • A fragmentationaware Virtual Optical Network Embedding (VONE) algorithm is designed by coordinating node and link mapping during VONE to reduce spectrum fragmentation and improve resource unitization [22]

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Summary

Introduction

With large-scale deployment of data centers and continuing proliferation of cloudbased applications, traffic has grown dramatically and is imposing a huge demand on network bandwidth. A fragmentationaware Virtual Optical Network Embedding (VONE) algorithm is designed by coordinating node and link mapping during VONE to reduce spectrum fragmentation and improve resource unitization [22]. There are some works that addressed the RSA problem [27,28,29,30] or considered costs [31,32,33,34] in co-existing fixed/flexible grid networks. Our previous work addressed the VON provisioning issues in co-existing fixed/flex grid optical networks for the first time [35]. We extend the above work and evaluate performance of the proposed flexible-grid aware VNE algorithm. PrTohbelepmhySstiactaelmoepnttical network infrastructure is simplified to substrate nodes and substrTahteelipnhkyss, iwcahliloeptthiecavlirntuetawl ooprkticianlfrnaesttwruocrtkuirseciosmspimospeldifioefdvitrotusaulbnsotrdaetseannoddveisrtaunadl lisnukbss.trWatheelninkVsO, wNhrileeqtuheestvsirctoumaleopotnicealafnteetrwaonrokthisecr,oma pVoOseNd pofrovviritsuioanl innogdepsroacneddvuirretuiasl nleinedkse.d Wto hmeanpVthOeNvirrteuqaulensotsdecso/mlinekosnoef eaaftcehrVaOnoNthreerq,uaesVt OonNtoptrhoevsiusibosntrinatge pnorodceesd/luinreksi.s Ineceod-edxitsotimngapfixthede /vfliretxuiablenogdrieds/olpintikcsalonf etawchorVkOs,Nthreerqeuaerset otwntoo dthifefesruebnstrkaitnednsoodfens/oldineks:s. (1In) fcioxe-edx-igsrtindgnfiodxeds,/wflhexicibhlfeogllroidwotrpatdiciatilonneatlwroigrikds,ITthUe-rTe-adreefitnweoddceifnfetraelnftrkeqinudesnocifensoadneds: s(p1e)cfitrxuemd-ggrriiddsno(ed.egs., w50hGichHfzo);llaonwdtr(2ad) iftlieoxnibaler-iggrididITnUod-Tes-dwefihnicehd dceonntroatl nfreeeqduetoncsitersicatnlyd fosplleocwtruthme fgixrieddsf(ree.qgu.,e5n0cyGgHrizd);aannddc(a2n) sflwexiticbhles-pgercidtranlobdaensdwwhidicthh dasoannoitnntegeedrtmo ustlrtipctlley offolflionwer-tghreafinxueladriftryeqsuliecnecsy(ge.rgid., a6n.2d5cGanHszw).itTcoh sapchecietrvael bmaonrdeweifdftichieanstanutinlitzeagteiornmouflttiphele noeftwfionrekr-sgpraecnturulamritryessoliucrecse(se, .fgl.e,x6ib.2le5-gGrHidzn).odTeosaschhoiuevlde bmeosreeleecftfiecdiewnitthutailihziagthio-pnrioofritthye inetthweoprkroscpeescstroufmVNreEso, usrincecse, flmeoxrieblsep-gercitdranlloyd-esffsichioeunltdlibgehstpelaetchtsedcawnitbheasheitguhp-.pFriogruirtye i1n sthhoewpsroacnessilloufsVtrNatEiv, esinecxeamporle.spSuecptpraolslye-etfhfiecrieenitsliaghVtpOaNthsrecqanuebset setu.pT. hFeigucorem1psuhtoinwgs raenquililruesmtreantitvseoef xvairmtupalel .nSoudpepao, sbe, tchienre is aarVeO5Nunrietqs,uaenstdRth1.eTbhaencdowmidptuhtirnegqureirqeumirenmtsenotfs voirftvuiarltulianlknoadbe, ab,cba, rcein20R01 Garbe/s5. uTnhiets,suanbdstrthateeboapntdicwaildnthetrweqourkirecmonesnitsstsofovf i8rtufiaxleldin-gkriadb, nbocdaerse a2n0d0 G6bf/lesx. iTbhle-sguribdstnraotdeeosp, taicnadl ntehtewirorckomcopnustisintsgocfa8pfiaxceitdie-gsraidreno30d0esuannidts. Dfleuxeibtloeggeroigdrnaopdheics,caonndsttrhaeinirtcs,otmhepucatinndgidcaapteacmitaiepspairneg3n00oduensitfso.rDau, be,tco agreeo{g1r,a2p,h3i,c4c}o, n{5s,tr6a,i7n}t,sa,nthde {1ca0n, d1i2d, a1t3e,m1a4p},priensgpnecotdiveselfyo.rOa,bbv,icouasrely{,1t,h2e, 3c,o4n},su{5m, 6p,t7io},nanodf s{1u0b,s1tr2a, t1e3,o1p4t}i,carelsnpeetcwtivoerkly. rOesbovuirocueslwy,itlhl ebecomnisnuimpizteiodnifotfhseunbostdreatme oapptiicnagl nfoertworkisr{eas→ou3r,cbe→s w6,ilcl→be13m},insinmcieztewdoif fltehxeibnloed-germidaspuppinegr-cfohranRn1eilss{caa→n3b,eb→set6,ucp→(f1r3o}m, sinnocedetw3otoflenxoibdlee-6grfiodrsluinpkera-bch, aannndelfsrocman nboedsee6t utopn(fordoem1n3ofodrel3intko bnco)d. e 6 for link ab, and from node 6 to node 13 for link bc)

Flexible grid node
VON Provisioning Algorithm
Performance Evaluation
Findings
Conclusions
Full Text
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