Software Defined Enterprise Passive Optical Network

Ahmed Amokrane∗† Jinho Hwang† Jin Xiao† Nikos Anerousis†

∗LIP6 / Pierre and Marie Curie University, Paris, France†IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

Abstract

In the last few years, changing infrastructure and busi-ness requirements are forcing enterprises to rethink theirnetworks. Enterprises look to passive optical networks(PON) for increased network efficiency, flexibility, andcost reduction. At the same time, the emergence of Cloudand mobile in enterprise networks calls for dynamic net-work control and management following a centralizedand software-defined paradigm. In this context, we pro-pose a software-defined edge network (SDEN) designthat operates on top of PON. SDEN leverages PON ben-efits while overcoming its lack of dynamic control. Thispaper is a work-in-progress focusing on enabling keyflow control functions over PON: dynamic traffic steer-ing, service dimensioning and realtime re-dimensioning.We also discuss how SDEN edge network can integratewith core SDN solutions to achieve end-to-end manage-ability. Through case experiment studies conducted ona live PON testbed deployment, we show the practicalbenefits and potentials that SDEN can offer to enterprisenetworks redesign.

1 Introduction

Enterprise networks today are under tremendous pres-sure to change. A recent study conducted by theEconomist Intelligence Unit Research, sponsored by Ju-niper Networks, points out that over 50% of the busi-nesses surveyed consider IT operations a core businessenabler, and yet they find that their current IT infrastruc-ture largely falls short of expectations in driving businessgrowth [1]. The problem stems from changes in infras-tructure and business requirements. Infrastructure wise,enterprise networks desire operational efficiency, man-agement simplicity, green and cost effectiveness; Busi-ness requirement wise, enterprise networks need to copewith disruptive yet business vital technologies such asCloud and mobile. In fact, Cloud and mobile are funda-mentally changing the traffic characteristics of enterprisenetworks, and how best to manage them. It comes fromthe fact that network traffic pattern is far more dynamicand uncertain when enterprise embraces these new tech-nologies in their amidst. Cloud workload varies signif-icantly with time and mobiles’ traffic is migratory andvolatile. Taking the stadium enterprise as an example,the traffic patterns exhibited during a game day is highly

dependent on the phase and condition of a game. Beforethe game starts, the majority of the traffic comes fromthe gate entrance; during game periods, they are concen-trated at the seating areas. During half-time, the concen-tration shifts to the concourse; and after the game, theymigrate to the parking lots. The transitory traffic volumeand burst intensity is also highly related to changes ingame states (e.g., a remarkable touchdown scored by thehome team is likely to trigger a large surge in mobile traf-fic). Over the past few years, a vast majority of the sta-diums that have hosted the final games of the Superbowlhave experienced significant network congestion/failureon game days. Many campuses also experienced simi-lar conditions on the eve of a major iOS or mobile gamerelease.

In this context, Passive Optical Networks (PON) is apromising technology that contains the key ingredientsin addressing the new infrastructure requirements. Orig-inated from Fiber-to-the-Home (FTTH) sector, PON isbecoming an attractive fiber-based LAN edge networksolution for enterprises. Some of the key benefits PONbrings to enterprise networks are: significant reductionin capex and opex, centralized control and management,high capacity, flexible deployment, and strong physicaland communication security. IBM and its PON alliancepartners have observed significant increase in the de-mand for enterprise PON since 2013. This is exempli-fied by a recent 10 million plus USD deal with TexasA&M Kyle Field stadium to renovate their network in-frastructure. From an infrastructure perspective, muchof the savings PON brings to enterprise is due to the re-placement of distribution layer active equipments (i.e.,network switches) with passive optical splitters, whilerelying on the core for flow control and traffic manage-ment. On the other hand, there is a need to redesignedge network control and management that is flexible,responsive, and adaptive to realtime conditions. Wethink Software Defined Networking (SDN) is a promis-ing paradigm that satisfies the new enterprise networkrequirements.

In light of this, we are actively investigating, at IBMResearch, the application of SDN on top of PON toachieve enterprise network efficiency and agility. Inthis paper, we discuss two challenges we have encoun-tered and addressed: firstly, SDN is a layer 3 tech-nology that does not have corresponding translation tolayer 2 edge network, which is required for End-to-

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End manageability; secondly, flow control and manage-ment in PON cannot be achieved by traditional edgeswitching due to PON’s lack of distribution switchingfabric. Innovation is therefore required to enable pri-mary flow control functions such as flow steering, di-mensioning and performance management. In this paper,we introduce software-defined edge network (SDEN), asoftware-defined enablement of enterprise PON that hasthe flexibility, responsiveness and realtime control capa-bility to meet the new enterprise network requirements.As this paper reports on our work-in-progress, we fo-cus on how flow management functions such as steering,dimensioning and re-dimensioning can be supported inPON, and discuss how SDEN interacts with SDN con-troller to achieve end-to-end manageability. For feasibil-ity study, we implemented SDEN flow control functionsin software and conducted case experiments on live PONtestbed deployment.

The rest of this paper is organized as follows. Section2 presents PON and SDN technologies and related worksin the literature. Section 3 presents our SDEN frame-work, followed by the experiments in Section 4. Section5 presents our vision in terms of End-to-End manageabil-ity. Finally, Section 6 concludes the paper.

2 Background and Related Work

2.1 Passive Optical NetworksA typical PON is a set of Optical Network Terminals(ONTs), passive splitters and the Optical Line Terminal(OLT). The ONTs connect edge devices into the PONnetwork via Ethernet ports. Digital signals from edge de-vices are converted to optical signal in the ONT. The op-tical splitters split the light signal multiple ways to ONTsand transmit the multiplexed signal to the OLT. The OLTaggregates all optical signals from the ONTs and con-verts them back to digital for the core router. The OLTmay support a range of built-in functionalities such asintegrated Ethernet bridging, VLAN capability and secu-rity filtering. Compared with traditional copper network,PON replaces switches in the access and aggregation lay-ers with splitters, and the traditional distribution layer iscollapsed back to a few OLTs at the core. An OLT maysupport 8-72 fiber ports, with each port connecting a fibercable to the splitter. The splitter can support differentsplitting ratios with 1-32 or less being the recommendedratio. Therefore each OLT port can potentially support32 ONTs. Different ONT configurations are availableranging from 2 to 24 Ethernet ports. Enterprise PON usesthe ITU-T Gigabit PON (GPON) standards [2, 3, 4]. We,therefore, use PON and GPON interchangeably in thispaper.

Compared to traditional copper networks, PON has a

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number of salient advantages. In fact, the optical fibersin PON can travel up to 20 Km from the core to the ac-cess, capable of delivering upstream to 1.2 Gbps up and2.4 Gbps downstream to the port, in current generation,and the fiber is much lighter than copper cables. More-over, PON eliminates active equipments in the distribu-tion resulting in significant capex and opex savings (up to40% and 60% respective savings compared to traditionalenterprise copper networks [5]). Furthermore, PON of-fers much stronger security with enhanced data encryp-tion and physical protection [6]. For more details aboutthe enterprise PON technology and its benefits over tra-ditional copper network, please refer to [5].

The entire PON network constitutes an Ethernet LAN.In fact, users’ Ethernet frames are encapsulated in GTCEncapsulation Method (GEM) frames. Each GEM framebelongs to a GEM port. A GEM port represents a logi-cal connection (channel) between an ONT and an OLT,with a class of service and a unique identifier. A typi-cal architecture for traffic management in GPON is illus-trated in Figure 1. A Transmission Container (T-CONT)is an ONT object representing a set of GEM ports that ap-pear as a single entity for the purpose of upstream band-width assignment on the PON. In the upstream direc-tion, bandwidth allocation for ONTs is done in a TDMAmanner by the OLT, where each slot is allocated for agiven T-CONT. More specifically, users’ Ethernet framesare assigned N-VLAN tags (Network VLAN) and CoS(802.1p) values based on Physical Port of the ONT, Sub-scriber VLAN ID, 802.1p bits and/or DSCP, as definedby the ITU-T GPON standard. Then, each of these N-VLAN and CoS combination is mapped into a specificGEM port, and the QoS of the T-CONT to which theGEM port belongs applies to the frame for scheduling.In the downstream direction, traffic is transmitted in aTDM manner, where each ONT forwards the traffic tothe appropriate GEM port.

2.2 Software Defined Networks

SDN has recently emerged as new norm for networks. Ina nutshell, SDN relies on (i) decoupling the control planefrom the data plane, (ii) logically centralized controllerand (iii) a standard protocol, such as OpenFlow [7], forcommunication between the controller and the forward-

ISBN 978-3-901882-67-8, 10th CNSM and Workshop ©2014 IFIP 407 ManSDN/NFV Full Paper

ing elements in the network. SDN has mainly been usedin data center networks, with mainly an Ethernet copper-based switching fabric. As SDN offers flexibility, man-ageability and agility, number of proposals advocated toextend SDN for wireless networks, be it cellular [8] orWLANs wifi-based networks [9, 10], wireless mesh net-works [11], campus copper-based networks [12]. More-over, one active and interesting effort is to extend SDNto optical networks [13, 14, 15]. The objective is to easemanagement and flexibility that are often rigid and cum-bersome. In enterprise networks, SDN helps to addressthe problems of flow control, network load balancing andperformance management (quality assurance and con-gestion control), required by increasingly heterogenous,mobile and dynamic user traffic profiles.

On the other hand, optical networks are becoming anattractive solution as they offer higher capacity and re-duced opex and capex. Logically, SDN should even-tually be extended to incorporate PONs in the years tocome. In fact, the ONF created The Optical TransportWorking Group (OTWG) [13]. The OTWG will worktowards identifying use cases, defining a target refer-ence architecture for controlling Optical Transport Net-works (OTNs) incorporating OpenFlow, and identifyingand creating OpenFlow protocol extensions. Gringeri etal. [15] identified some of the key requirements, bene-fits and challenges of extending SDN concepts to OTNs.However, these works focused on OTNs, which are ca-pable of active switching and use GMPLS for creatingvirtual circuits on top of the optical backbone, and didnot address the challenging aspects of PONs. The firstwork to introduce SDN paradigm in PONs was proposedby Parol et al. [16]. In this work, authors proposed ex-tensions to OpenFlow protocol, which consist mainly onmapping flows (as defined by the OpenFlow protocol) toGEM ports, in addition to pushing and popping VLANtags from the packets. However, such proposal requireschanges in the ONTs and OLTs to be implemented. Ad-ditional works, such as [17], which considers the specificrequirements of an ISP GPON-based networks, have alsoproposed hints for integrating SDN in optical networks.However, the dynamic and mobility pattern of enterprisenetwork traffic and the need for agility have not been ad-dressed in this work.

3 Software Defined Edge Network

3.1 SDEN Framework

Figure 2 illustrates our proposed architecture for SDEN.SDEN defines a common interface through APIs be-tween the controller and the PON nodes (OLT). The in-terface provides a standardizable and vendor neutral setof functionalities that a controller can use. On top of the

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controller, one can have different applications for net-work management and optimization. For instance, in thispaper, we show how an application can perform dynamictraffic and capacity steering in PON.

To realize this design, we need to tackle two majorchallenges. First, there is no concept of flows in PON,and the existing PON nodes (i.e., OLT and ONT) do nottalk or understand the OpenFlow protocol [16]. There-fore, we define in SDEN a mapping between a flow anda set of PON primitives (fiber connectivity, PON portsand service profiles). Moreover, PON can not performflow control in the conventional sense as there is no ac-tive switching fabric. Instead, PON management is con-ducted centrally at the OLT by setting service profilesand defining PON ports attributes. Second, PON na-tive management interfaces in the OLT allow a humanadministrator to perform these configurations manually(e.g., Tellabs PON provides a command line interface).To enable automatic real-time flow control in PON, Anew SDEN module is appended to the SDN controller tocall the APIs of the SDEN agent located in the edge net-work. More specifically, the SDEN agent translates highlevel flow control requests from a controller into a set ofnative PON configuration commands, and sends them tothe OLT via the command line interface (CLI).

In this way, we are able to follow a software-definedparadigm to dynamically control and manage flows onthe fly in response to changes in traffic characteris-tics induced by end user workload changes and mobil-ity. To this end, there are three key functionalities theSDEN agent needs to support: online flow and capacitysteering, service dimensioning, and realtime service re-dimensioning. In the following subsections, we discussthe motivation and how each one of these functionalitiesis enabled in PON.

3.2 Flow Control and SteeringOne issue in enterprise and campus networks is toachieve agility. In fact, in most of the current deploy-ments, capacity is statically allocated to parts of the net-

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work. However, nowadays enterprise traffic patterns varysignificantly with time and mobiles’ traffic is migratoryand volatile. As a matter of fact, it is of paramount im-portance to provide capacity in an on-demand fashion toparts of the network. Taking the stadium enterprise as anexample, the capacity should be allocated to the differentparts of the network depending on the phase and condi-tion of the game. To achieve this, we propose a two-foldsolution.

First, we advocate a crisscross deployment where mul-tiple fibers run from different GPON cards and/or portstowards the same area. Note that other fibers from thesame GPON cards and/or ports might run to different ar-eas of the campus. For instance, a single WAP is con-nected to multiple ONTs, each of the ONTs is connectedto a different GPON card/port. As such, we achieve anN:N mapping of the WAPs and the ONTs-OLTs. Notethat this deployment allows traffic steering and band-width management in a dynamic manner.

Second, we propose a dynamic approach to direct thecapacity in the PON network towards specific areas, de-pending on the traffic conditions in the areas. To doso, we propose a dynamic approach that (i) monitorsthe GPON links (from the ONT towards the OLT) and(ii) dynamically reroutes traffic through different GPONports to provide more capacity to overloaded areas of thenetwork. More specifically, we propose a simple yet ef-ficient algorithm that uses predefined thresholds to dy-namically perform capacity steering in the network. Ina nutshell, if a link utilization (i.e., fiber at the GPONport) is above a threshold α , we redirect part of the trafficthat runs through an ONT (one Ethernet port at the ONT)to use a different path, going through a different GPONport. At the same time, if the utilization of a link is belowa threshold β , we consolidate the traffic through an un-derutilized GPON port. The objective is to achieve elas-ticity in resource utilization in the network in response tothe traffic load.

It is worth noting that our proposed dynamic capac-ity steering can run as an application on top of the SDNcontroller. For ease of explanation, we do not include thecontroller in this paper and consider the application to bethe only one running on the controller.

3.3 Dynamic Flow Dimensioning

As traffic in enterprise networks becomes heterogeneous,differentiating flows with priorities and requirement isanother key functionality that PON should offer. Morespecifically, one should be able to offer guaranteed QoSfor classes of traffic independently of the network state.

In our proposed framework, we provide guaranteedbandwidth for specific traffic flows based on the userdevices. In fact, we can provide guaranteed committed

rates regardless of the traffic and state of the network.The idea is to isolate critical traffic from congestions thatmight occur in the network by providing classes of ser-vices, with strict priority. In an enterprise network, onecan think of VOIP traffic as being critical and should notbe affected by the other traffic flowing in the network.

3.4 Real-time Flow Re-dimensioningIn addition to initial flow dimensioning, PON should alsoallow for realtime flow re-dimensioning by dynamicallyadjusting the allocated resources. The aim of dynamicre-dimensioning is to free more resources for traffic withhigher priority and efficiently use the resources in thenetwork. For instance, in the absence of VOIP traffic,one can allocate the available bandwidth to data traffic.However, in the case of high VOIP traffic, data traffic isdelayed to leave room for VOIP traffic.

Our proposed framework enables dynamic re-dimensioning of services on the fly and in realtime. Morespecifically, we propose to prioritize certain services overothers by dynamically adjusting the allocated resourcesin the network to the different services based on theircorresponding priorities. Similar to capacity steering,dynamic service re-dimensioning is performed thanks toresource and demand monitoring in the network.

4 Experiments

In this section, we demonstrate the effectiveness of ourproposal, and illustrate the benefits of the three key en-ablers for SDEN: traffic and capacity steering, servicedimensioning and dynamic service re-dimensioning. Todo so, we conducted experiments on a real PON testbeddeployed in our lab. Figure 3 illustrates the experimen-tal setup. We used a Tellabs 1150 OLT with one singlemounted GPON card. We run two fibers from two differ-ent GPON ports (GPON port 1 and 2) of the same GPONcard. We attach to each of the two ports one ONT, Tellabs

Figure 3: Experimental setup

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728 and 709, to GPON port 1 and 2, respectively. Notethat we put a splitter between each ONT and the corre-sponding GPON port. Two laptops are connected to thesame switch, and the switch is connected to ethernet port1 and port 2 of ONT 1 (Ethernet port 1-1 and 1-2, re-spectively), and port 1 of ONT 2 (Ethernet port 2-1), asillustrated in Figure 3. From each laptop, traffic can floweither through Ethernet port 1-1, Ethernet port 1-2 or Eth-ernet port 2-1, using the L2 unmanaged switch. Note thatthe switch is used only to offer different paths for eachlaptop and has no active function. In the following, wepresent and discuss the experiments that showcase capac-ity steering, service dimensioning and dynamic servicere-dimensioning.

Dynamic Capacity Steering: To illustrate the dynamicbandwidth management and capacity steering, we runthe first set of experiments. We launch FTP download-ing sessions from Laptop 1 and 2 and observe the traf-fic flows at the GPON ports, and the ethernet ports towhich the switch is connected. Note the upper bound α

and lower bound β are set to 4 Mbps and 1 Mbps re-spectively. The results are shown in Figure 4. We grad-ually increase the downloading rate in the two laptopsover time. At the beginning, all traffic is routed throughthe GPON port 1 (see time ≤ 260 s). As traffic load in-creases and reaches the upper threshold α (see time 260-270 s), our algorithm switches the traffic of Laptop 1 to

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flow through GPON port 2 (see time 270-400 s). Whenone of the GPON ports is underutilized (see GPON port2 at time 400-450 s), its traffic is consolidated with thetraffic flowing through the second GPON port (GPONport 1, time 450-610 s).

Service and Flow Dimensioning: In the second set ofexperiments, we illustrate how our framework providesbandwidth guarantees and service dimensioning. To doso, we run two different services (Service 1 and Service2) from the two laptops (Laptop 1 and Laptop 2, respec-tively). Service 2 is set to have a guaranteed bit rate. Ser-vice 1 is assumed to be of variable bit rate. Note that weuse in this case the same ONT for both laptops, i.e., thetwo laptops use the same GPON port. We vary the trafficrate from Laptop 1 over time and monitor the bandwidthat Laptop 2. The results are plotted in Figure 5. Thefigure shows a guaranteed bandwidth for Laptop 2 eventhough Laptop 1 increases its traffic rate. However, notethat the traffic at Laptop 1 is bounded to prevent it fromdisrupting the traffic of Laptop 2.

Dynamic Service Re-dimensioning: Let us now illus-trate the dynamic service re-dimensioning. To do so, werun two different services (Service 1 and Service 2) fromthe two laptops (Laptop 1 and Laptop 2). Service 1 is setto have higher priority than Service 2. Similar to the pre-vious experiment, the two laptops use the same GPONport. We vary the bandwidth demand from Laptop 1 overtime, while keeping the traffic in Laptop 2 at a fixed rate.The results are plotted in Figure 6. From the figure, wenote that the traffic in Laptop 2 is reduced as traffic inLaptop 1 increases. This is done in our framework bydynamically adjusting the committed rate of Service 2 tocope with the increase in traffic of Service 1 as they sharethe same network resources.

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5 Ongoing Challenges: End-to-End Man-ageability with SDN

In our work, we presented dynamic flow manage-ment through steering, dimensioning and realtime re-dimensioning. A flow is defined by the SubscriberVLAN, 802.1p bits and/or DSCP, as defined in theGPON standard. Each flow is then mapped into a singleGEM port, with a CoS. As such, a flow defined in ourGPON is the aggregation of multiple flows, where eachof them is a single flow defined in OpenFlow standard.One difficulty is that our current definition of a flow, us-ing GPON standard, is coarse grained. In fact, to get a1:1 mapping of our GPON flows and the flow definitionof OpenFlow, we need a more detailed inspection of theEthernet frames, by looking at L3 and L4 headers, at theONT for upstream and OLT for downstream.

Currently, in our effort towards a full End-to-End SDNmanageability, we embrace the incremental SDN deploy-ment and integration in networks [18]. To do so, we de-fine a mapping of the aggregate flows to integrate theSDEN into an SDN managed core network. The trafficsteering, service dimensioning and dynamic service re-dimensioning offer a considerable agility and manage-ability in PON, without using active equipment at theedge, nor modification in the PON equipment design. Infact, this allows us to direct capacity dynamically basedon the traffic in the network, assuring premium traffic andguaranteed QoS. However, defining fine grained flowsand match the same definition of flows as OpenFlow, isone of our key challenges to address.

On the other hand, we are actively investigating theimplementation of OpenFlow in SDEN. One promisingtrack is to define a mapping of OpenFlow messages andcommands into PON commands. Another option to buildplugins for SDN controllers such as OpenDaylight, with-out going through OpenFlow, is also under investiga-tion.

6 Conclusion

In this paper, we investigated the implementation ofsoftware defined control and management in enterprisePON. Our objective is to introduce agility, flexibilityand dynamic adaptation to the PON network in order tomeet the new enterprise business requirements, and tocope with traffic dynamicity introduced by Cloud andmobile. To this end, we proposed the SDEN frame-work, discussed how traffic steering, dimensioning andre-dimensioning can be achieved in PON. Through ex-periments conducted on a live PON testbed network,we demonstrated the practicality and potential bene-fits software-defined control brings to enterprise PON.Based on what we have learned and established in this

paper, we are actively investigating the integration ofSDEN agent with SDN controller and the translation ofOpenFlow protocol to PON.

References[1] Juniper Networks. Scaling the new service provider network at

the edge. Juniper Networks Whitepaper, 2013.[2] ITU-T Gigabit capable Passive Optical Networks (GPON). Gen-

eral characteristics. ITU-T G.984.1, 2008.[3] ITU-T Gigabit capable Passive Optical Networks (GPON).

Transmission convergence layer specification. ITU-T G.984.3,2008.

[4] ITU-T Gigabit capable Passive Optical Networks (GPON). Ontmanagement and control interface specification. ITU-T G.984.4,2008.

[5] IBM Global Technology Services. Smarter networks with passiveoptical lans. IBM Whitepaper, 2013.

[6] Jason Young. Comparative Risk Analysis Between GPON Opti-cal LAN and Traditional LAN Technologies. White Paper, SANSInstitute InfoSec Reading Room, October 2013.

[7] Nick McKeown, Tom Anderson, Hari Balakrishnan, GuruParulkar, Larry Peterson, Jennifer Rexford, Scott Shenker, andJonathan Turner. Openflow: Enabling innovation in campus net-works. SIGCOMM Comput. Commun. Rev., 38(2), March 2008.

[8] L.E. Li, Z.M. Mao, and J. Rexford. Toward software-definedcellular networks. In European Workshop on Software DefinedNetworking (EWSDN), pages 7–12, 2012.

[9] Julius Schulz-Zander, Lalith Suresh, Nadi Sarrar, Anja Feld-mann, Thomas Huhn, and Ruben Merz. Programmatic orchestra-tion of wifi networks. In 2014 USENIX Annual Technical Confer-ence (USENIX ATC 14), pages 347–358, Philadelphia, PA, June2014. USENIX Association.

[10] Lalith Suresh, Julius Schulz-Zander, Ruben Merz, Anja Feld-mann, and Teresa Vazao. Towards programmable enterpriseWLANS with Odin. In Proceedings of the first workshop onHot topics in software defined networks, HotSDN, pages 115–120, 2012.

[11] P. Dely, A. Kassler, and N. Bayer. OpenFlow for Wireless MeshNetworks. In Proceedings of 20th International Conference onComputer Communications and Networks (ICCCN), pages 1–6,Aug 2011.

[12] ONF. SDN in the Campus Environment. ONF Solution Brief,October 2013.

[13] The ONF Optical Transport Working Group (OTWG),http://bit.ly/1mRiYVE.

[14] P. Parol and M. Pawlowski. Towards networks of the future: Sdnparadigm introduction to pon networking for business applica-tions. In Federated Conference on Computer Science and Infor-mation Systems (FedCSIS), pages 829–836, Sept 2013.

[15] S. Gringeri, N. Bitar, and T.J. Xia. Extending software definednetwork principles to include optical transport. IEEE Communi-cations Magazine, 51(3):32–40, March 2013.

[16] Pawel Parol and Michal Pawlowski. Towards networks of thefuture: Sdn paradigm introduction to pon networking for businessapplications. Federated Conference on Computer Science andInformation Systems (FedCSIS), 2013.

[17] H. Woesner and D. Fritzsche. Sdn and openflow for convergedaccess/aggregation networks. In Optical Fiber CommunicationConference and Exposition and the National Fiber Optic Engi-neers Conference (OFC/NFOEC), pages 1–3, March 2013.

[18] Dan Levin, Marco Canini, Stefan Schmid, Fabian Schaffert, andAnja Feldmann. Panopticon: Reaping the benefits of incrementalsdn deployment in enterprise networks. In 2014 USENIX An-nual Technical Conference (USENIX ATC 14), pages 333–345,Philadelphia, PA, June 2014. USENIX Association.

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