Telecommun SystDOI 10.1007/s11235-011-9431-6

Cost models for QoS-differentiated interconnecting and wholesaleaccess services in future generation networks

Alberto E. Garcia · Laura Rodriguez ·Klaus D. Hackbarth

© Springer Science+Business Media, LLC 2011

Abstract Currently, network operators and Internet serviceproviders are offering “Triple Play” products integrating ser-vices with different Quality of Service (QoS) requirements.It is leading to Internet traffic with strong service inte-gration under an all-IP-based broadband network platform.However, new multimedia service offers require individualQoS guarantees for each type of services. The interconnec-tion between different providers necessitates the reconsider-ation of the actual cost schemes. Interconnection and whole-sale access services (It is an extension of “wholesale net-work” definition, where Telco’s physical network and equip-ment are “shared” to many independent Service Providers. Ifthe incumbent offers broadband access services, the rest ofthe alternative providers have recourse to the incumbent’s“wholesale access service”. Bitstream service is the mostimportant service of this type, actually regulated over DSLand cable networks.) appear to be a simple solution, butthe consideration of QoS parameters requires an extensionof the current network dimensioning methods based mainlyon the average bandwidth demand from each user. This pa-per proposes a cost model which considers QoS parametersand, based on the “Total Element based Long Run Incre-mental Cost” (TELRIC) model, is applied to the wholesaleaccess and interconnection paradigm. Three traffic engineer-ing methods are considered and studied for network dimen-sioning. Hereby the aim is to guarantee the QoS of the differ-ent services: complete traffic segregation under virtual tun-

A.E. Garcia (�) · L. Rodriguez · K.D. HackbarthGIT/DICOM University of Cantabria, Santander, Spaine-mail: agarcia@tlmat.unican.es

L. Rodrigueze-mail: laura@tlmat.unican.es

K.D. Hackbarthe-mail: klaus@tlmat.unican.es

nels, complete traffic integration by over-engineering andpartial traffic integration using a priority queuing scheme.The proposed method enables the development of a specificcost scheme based on a complete scenario considering dif-ferent types of users. The variety of used IP applications sup-pose direct implications over different levels of interconnec-tion, mainly at the low-level Metro access and the high-leveledge node.

Keywords Cost models · Future generation networks

1 Introduction

The future generation networks’ paradigm presupposes anevolution of the next generation networks following thequality and Grade of Service (GoS) requirements accordingto the new user’s necessities and the operator’s capabilities.However, in the current practice of interconnection of IP net-works, the technical implementation of QoS assurance is notcarried out. Its application follows the necessities imposedby a new global scenario, in which a compound new marketfor transport interconnection appears. Besides the transport,connectivity is the second factor included within the newmarkets. The new concept is to pay for each stream depend-ing on the origin and the termination nodes. These ideas re-quire specific solutions based on different transport classes,including specific QoS differentiation.

As an initial solution, most telecommunications suppliershave developed corresponding equipment and various oper-ators are changing their networks with the objective of inte-grating all of their telecom services into just one unified plat-form, see [1]. This requires a corresponding investment andhence an increased value of the CAPEX (Capital Expendi-tures), but allows a reduction of the effort for the OAM (Op-erations, Administration, and Maintenance) functions and

A.E. Garcia et al.

Fig. 1 General structure of ageneric Internet network basedon three layers: SubscriberAccess Network, BroadbandAccess Network and CoreNetwork (POP = Point ofPresence, SPE = ServicePremise Equipment)

hence provides a reduction of the OPEX value(OperationalExpenditures). It is expected that in the long-run traffic in-creases due to multimedia services which will compensatepart of the CAPEX. Additionally, the paradigm change im-plies a number of telecom regulation problems consideringthe access and interconnection rule. Therefore, the develop-ment of FGN implies the need to study cost and price modelsfor different types of wholesale and retail services by oper-ators but also by regulation authorities considering an ade-quate network dimensioning (bottom-up approach), see [2].The most important wholesale services are interconnection,call termination and wholesale access requiring QoS ser-vices such as bitstream. These new models for service costsare mainly important in the access and aggregation networkpart due to the limited traffic aggregation, and hence thereduced bandwidth demand. In contrast, as will be demon-strated in this article, the influence of the new cost model inthe core part of the network is limited in the case of a hightraffic concentration on a limited number of interconnectionpoints and hence the applied bandwidth lies in STM-4 up tothe 16 Gb/s. In the paper we consider the connection fromthe user up to the first aggregation point, the access network,and from the first aggregation point to the edge node of thecore part such as the aggregation network. Figure 1 shows atypical Internet network scenario and its division into accessand core ones. Aggregation occurs along the entire scenariobut especially at interconnection points. However, the mostimportant effects of the aggregation appear during the tran-sit from Subscriber Access Network, into so-called Point ofPresence (PoP) and from the Access Network (SubscriberAccess Network—SAN), into the Edge routers. The sce-nario formed by both parts is usually denominated aggrega-tion network. This paper concentrates on bandwidth calcula-tion for interconnection cost analysis based on the TELRICmodel, considering a set of services with their correspondingQoS requirements, expressed mainly in terms of the meandelay. However, the model is sufficiently general to be ap-plied to any network elements within the chain of an end-to-end connection. The use of a Gi/Gi/1 model improvescommon regulator praxis based on simple mean bandwidthvalues or in the best case using an M/M/1 model. TheGi/Gi/1 model allows a cost approximation based on an

equivalent bandwidth higher than using its mean value de-pending on the traffic characteristic for each service. Thecomplete mathematic model appears in [3] and its practi-cal application is exposed here. It is hence a first step inimproving TELRIC models for networks based on packetswitching. The application of alternative models like fluidflow model is for future studies.

2 A generic FGN network scenario

The evolution of the network structure imposes restrictionson the QoS implementation. Traditional structures, basedon a hierarchical distribution from a geographical point ofview, evolved towards a more functional one. The classi-cal scenario divided the network into local, regional andnational/international layers which was substituted by theFuture Generation Network (FGN) concept, using the func-tionality of each part to establish the subdivisions amongdistribution, aggregation and core networks. Its natural evo-lution towards the future networks concepts causes a drasticreduction in the number of intermediate high-level nodes,simplifying the routing schemes, and upgrading all the inter-connection, moving all the functionalities towards the higherlevels, specifically towards the edge nodes. The Access andInterconnection Directive makes a clear differentiation be-tween Access and Interconnection, see [4]. The first one en-ables the use of services by different operators under de-fined conditions. The second one enables the establishmentof communication connections with the customers of otheroperators. These differences have to be included within thecorresponding cost structure. FGN is based on estimationsof the global costs corresponding to the combination of allthe considered services without accounting for the particulartraffic volume for each individual service. In this situation,only the transport is considered, while the particularities ofeach service are considered only in exceptional case, as afirst approximation to QoS provisioning. At the core net-work level, the operator decides about the bandwidth for in-terconnections to assure proper QoS without considering apossible degradation outside their own network, at foreign

Cost models for QoS-differentiated interconnecting and wholesale access services in future generation

Fig. 2 QoS/QoE genericschema: applications andservices require specific ServiceLevel Agreements which thetransport and IP layer provide,usually by traffic engineeringmechanisms

edges belonging to other operators in transit or peering ac-tions. This situation is aggravated due to the lack of a cost-based regulation which includes QoS provision within thecorresponding interfaces. The evolution towards the FGNsupposes the introduction of a total independence betweenthe operational and capital expenditures (OPEX&CAPEX)with respect to legacy technologies. In this way, cost stan-dards are based on a cost service provision considering QoStransition from the Calling Party’s Network Pays (CPNP)paradigm where the caller is subject to pricing for the com-plete end-to-end connection, to the Bill and Keep whereboth users contribute mainly through their flat rate tariffsand where no clear scheme between both operators is ap-plied. Note that Bill and Keep corresponds to the commonlyapplied “peering” between large Internet Service Providers(ISP’s), while CPNP corresponds to “transit” from a smallISP to a large one.

2.1 QoS provisioning

In the new FGN scenario, customers decide the set of ser-vices they want to use with specific requirements. The op-erator establishes a Service Level Agreement (SLA) associ-ated with each service, according to the requirements of thecustomers, and introduces the corresponding mechanisms attransport level to assure these SLAs. The transport layer pro-vides the required service quality for the different customersand services. In this situation, different types of service pro-files represent several combinations of the bandwidth re-quirements and QoS parameters and in a first approximationthe average delay. The IP transport platform might provideQoS parameters in an always-assured mode or on statistical

basis, using the corresponding traffic engineering concepts.Each different set of QoS requirements depends on serviceclasses. QoS assurance is mandatory for the end-to-end con-nection. In case of a connection over more than one networkplatform each access, core network and their interconnec-tion facilities maintain their own control mechanism assur-ing the correct compliance to QoS requirements. Basically,[5] distinguishes between three main methods for QoS pro-visioning in multiservice environments. Figure 2 shows thecorresponding scenario.

1. Traffic aggregation and routing over common capacitieswithout additional traffic engineering mechanisms: Thismethod uses the over-dimensioning of the capacities as-suring the required QoS corresponding to the most re-strictive service. The utilization of the network capaci-ties falls between 70 and 75 percent assuring QoS cor-responding to real-time and streaming services, withoutfurther traffic engineering efforts.1 The worst case ap-pears in spite of unexpected overloads, decreasing thenumber of resources and increasing the QoS degradationof the real-time services.

2. Traffic aggregation and routing over common capaci-ties using prioritized waiting mechanisms: The DiffServarchitecture uses priority-based waiting systems, assur-ing the independence of high priority and low priorityservices. This solution obtains different QoS schemesfor each class of service but with limitations. Prioritizedrouting assures the fulfillment of QoS only on a statisti-

1This range was used as reference value in some studies of regulation.However, the actual range might be broader, from 50 to 90 percent.

A.E. Garcia et al.

Fig. 3 Classification of service providers depending of their layer in-tegration. Basic providers of individual layers (Service or transport) areknown as Bearers or Resellers

cal basis and mainly for the services with highest priori-ties, while increased traffic of these services might blockthe rest. Traffic access control minimizes this effect us-ing specialized mechanisms, e.g. Weighted Fair Queuing(WFQ) is a data packet scheduling technique which al-lows different scheduling priorities to statistically multi-plexed data flows. FGN might provide connection controladmission and hence allow a better fulfillment of the QoSguarantees and a higher use of the network capacities.

3. Traffic segregation and routing over separated tunnels.IntServ architecture proposes assuring the QoS spec-ifications individually, depending on the traffic class.This method establishes fixed resource allocation, with-out shared capacities among different classes.

Overall scenarios, configuration of services and their cor-responding QoS depend directly on the degree of service in-tegration in an IP-based network. As Fig. 3 shows, a marketparticipant might be fully integrated, providing the applica-tion and its provision with their corresponding QoS and SLAspecifications; it might provide only the application or theservice layer provision while the QoS depends on the trans-port provider; or it might only provide the underlying trans-mission, see [6]. In any case, interconnection is solved at IPlevel, assuring the connectivity between different providersusing transit and peering agreements as shown in Fig. 4 andexplained in [7]. Peering allows two providers to exchangetraffic between their respective customers. The transit casesupposes that a provider pays another to deliver its trafficto third parties. The difference between peering and transitis a technical distinction and not an economic one, and thedifference in charging arrangements are an economic con-sequence. Traditionally peering was free of charge and tran-sit provided full global connectivity, but the future showsa clear tendency towards a paid peering and partial transit,see [8].

These requirements make the “Total Element based LongRun Incremental Cost” (TELRIC) model the most suitablefor studying service interconnection costing in networks ofFGI type. The TELRIC cost model in combination withnetwork engineering by a corresponding medium/long-term

Fig. 4 Transit and Peering concepts and their relationship with thedifferent provider types

network design and dimensioning is a bottom-up approach.It has already been widely applied for telecom regulationissues mainly in legacy PSTN/ISDN and mobile GSM net-works. TELRIC is based on determining the cost of a net-work element under a medium-long term perspective anddistributing its CAPEX over the different services depend-ing on each service’s intensity of usage of the element. Inthis situation the objective of a TELRIC model is to obtainthe network dimensioning with the aim of guaranteeing theQoS of the different services.

The first TELRIC models for cost studies for bitstreamservices considering Broadband Internet Access alreadyconsider both average values for the bandwidth require-ments and the mean delay assuming a Poisson arrival streamat the IP layer, which in reality is only a poor approxima-tion. In this paper, the model is extended considering a gen-eral arrival stream and a general packet length expressed byits first two statistical moments, see [9]. Corresponding costmodels are considered for the three most important trafficengineering schemes which are: traffic segregation, trafficintegration under over-engineering and under priority queu-ing. TELRIC models for FGN have to consider traffic aggre-gation and routing over common capacities assuming prior-itized waiting mechanism as current best praxis. Obviouslythe cost for a bandwidth unit resulting from traffic of higherpriority should be larger than the one with lower priority.For this propose we propose calculating the individual andtotal bandwidth under traffic separation considering for eachtraffic type the corresponding mean delay requirement. Weuse the relative bandwidth values resulting from this estima-tion for calculating the cost for the prioritized mechanism.Finally the results are compared with the reference valuesprovided from the traditional over-dimensioning method.

2.2 Services and QoS restrictions

The dimensioning in a bottom-up approximation is basedon the configuration of a hypothetical network, optimallydesigned according to the demand generated by the usersand applying current best or emerging technology. Under the

Cost models for QoS-differentiated interconnecting and wholesale access services in future generation

TELRIC model the cost of each network element is distrib-uted to the different services depending on the intensity ofelement usage. The total cost for a service unit is calculatedby adding the corresponding unit cost of all networks in-volved in the service provision. Hence, the TELRIC modelcovers the possible economies of scope and scale derivedfrom service integration, implying a cost reduction over allservices. As the bottom-up cost study is not based on theaccounting information of a specific operator, it will be themost appropriate method for regulation studies. Internet ser-vices are generally grouped into “service classes” accordingto their traffic characteristics and QoS requirements, leadingto four main classes as explained in [10].

1. The least restrictive class groups are so-called Best-effortservices. Their weakest requirements for delay are incontrast with their highest variability of data transfer.This type ranges from Web-based applications (includingmost so-called social-networks, i.e. Twitter or Facebook)to P2P (peer-to-peer) services.

2. Services related with video/audio transmission and dis-tribution, are grouped under the classification of Stream-ing applications. This class shows medium delay require-ments but a great variability of the data.

3. When the service requires intensive transfers over de-lay restrictions and QoS consideration, for example overVPN (Virtual Private Network) environments, the classis called Guaranteed data services.

4. Finally, the most restricted delay requirements are de-fined by specific applications, for example VoIP (Voiceover IP) and personal communications, and they arecalled as Real Time applications.

In this paper, we consider that all the services integratedin a FGN network and interconnection via peering or transitare grouped into these four service classes, with individualQoS parameters that have to be considered by dimension-ing rules and capacity provision. The corresponding data foreach service class are the mean bandwidth requirement ofthe service, the mean packet rate λ and the coefficient ofvariation of inter-arrival time C(Ta), the mean IP packetlength and its coefficient of variation C(L), and for QoSpurpose, the mean delay τ required in the considered net-work element. Note that we assume that the overall valueτ is determined by a distribution of the expected end-to-end mean delay over all network elements involved in thecorresponding service under consideration. However, typi-cal service and traffic scenarios consider different types ofusers establishing corresponding differences depending onthe main services required. Internet Service Providers (ISPs)offer retail services to different user type classes, typicallyfour classes: standard and premium residential, standard andpremium business). We assume that each user type gener-

ates a corresponding packet stream. Depending on Internetconnection and its utilization, each type of user is charac-terised by corresponding values for the concurrence factorac(t) and its service mix Internet services pattern). Addi-tionally, we assume that a user scenario indicates the distri-bution of a predetermined total number of users over the dif-ferent user types, the concurrence factor for each user typeac(t) and a parameter of the Internet Service Pattern indi-cates the demand of the different services in the Busy Hour(BH), Fig. 5 shows the complete set of parameters, for moredetails see [11].

3 Applying QoS mechanisms for the dimensioning ofinterconnecting scenarios

Our proposed model assumes that the arrival streams for ex-isting and future Internet services are generally bursty and insome particular case near to the Poisson case, the coefficientof variation of the packet inter-arrival time is calculated asC(Ta) ≥ 1 with Ta = 1

λas the mean value of inter-arrival

time. The packet length (and hence Ts ) covers any distribu-tion according to C(Ts = C(L)) ≥ 0. To meet this require-ment we use a Gi/Gi/1 model to be applied for the small-est network element in the interconnection facilities. Thismodel can be applied directly when over-engineering or traf-fic separation is used e.g. by applying Kingman’s formula,see [12]. In the case of priority queuing there is no analyticalmodel for the set of K Gi/Gi/1 systems under priority butfor a set of K M/Gi/1 such a model can be found. Hence,we propose the transformation of the general traffic streamfrom each service into an equivalent Poisson traffic streamobtaining a M/Gi/1 model. This is done by projecting thevariance of the packet-inter-arrival time into the variance ofthe packet service time and applying a corresponding K∗M/Gi/1 non-empty priority model for the k = 1, ..K ser-vices. For each service k, giving Tak = 1

λk, C(Tak), C(Tsk)

and the required mean delay τk (from QoS/QoE require-ments), the mean service delay is calculated by applyingKingman’s formula:

n̄ = ρ

[1 + ρ[C2(Ts) + C2(Ta)]

2(1 − ρ)

](1)

Which leads to τk using Little’s formula. With Tsk , the re-quired bandwidth is:

Vk = Lk

Tsk

(2)

Applied to the Virtual Tunnel case, Gi/Gi/1 is applied di-rectly calculating the bandwidth for each tunnel k, and the

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Fig. 5 QoS based on services: global requirements vs. services and user characteristics

common bandwidth is:

VT =∑

k

Vk (3)

Applied to over-dimensioning and integrating k services, wecalculate the common parameters: λ0, L0, C(Ta0), C(L0),and apply them for τ0 = mink=1..K{τk}. For this purposeeach service k is modeled with Tak = 1

λkand C(Tak) ≥ 1 by

an equivalent H2(Tak) distribution which provides the cor-responding xk , ηk . The H2(Tak) enables an easy aggregationof the traffic resulting from the different service classes byK parallel H2(Tak) models, applied for each service k withλk and Tak , where the corresponding parameters xk and ηk

are calculated by the first and second moment of Tak . Usingthe common arrival stream λ0, the pdf of Ta is:

fTa = α

λ0

K∑k=1

λkηke−ηkt + (1 − α)

λ0

K∑k=1

λkxk · ηk · e−xkηkt

(4)

Overall Ta and C(Ta) can be calculated by

C2(Ta) = T̄ 2a

T̄a2

− 1 (5)

and

T̄a = α

λ0

K∑k=1

λk

ηk

+ 1 − α

λ0

K∑k=1

λk

xkηk

(6)

with

T̄ 2a = 2α

λ0

K∑k=1

λk

(ηk)2+ 2(1 − α)

λ0

K∑k=1

λk

(xkηk)2(7)

Applied to the Priority Queuing model, the Gi/Gi/1model under priority queuing cannot be applied directly.In this case, the proposed model uses a Mk/Gik/1 modelwith decreasing priority k = 1..K , transforming the parame-ters of Gik/Gik/1 into an equivalent Mk/Gik/1, assumingC(Tak) ≥ 1 and the following approximation for each k:

C2(Tsk)eq = C2(Tak) + C2(Lk) − 1 (8)

Results from corresponding analytical and simulation stud-ies demonstrate that this approximation is valid. A completeexplanation of the proposed calculation appears in [11].

The TELRIC model distributes the total cost of the net-work element over all the users, taking into account the us-

Cost models for QoS-differentiated interconnecting and wholesale access services in future generation

Table 1 Parameters used in thecost calculation Parameter Description

k [p/s] Packet arrival rate of service class k during an active connection of one user

C(Tak) Coefficient of variation of the packet inter-arrival time of service class k

L̄k [oct.] Average packet length of service class k

C(Lk) Coeff. of variation of the packet length of service class k

Vk [Mb/s] Bandwidth of the network element provided for service class k

VT [Mb/s] Total bandwidth provided from the network element

τk [ms] Required delay associated with the network element of service class k

Tsk [ms] Service duration of service class k

C(Tsk) Coeff. of variation of the service duration of service class k

Nu Total number of users

Nut Relative number of users of type t with respect to Nu

ac(t) Concurrence factor indicating the probability that a user of type t is active in the BH

δk(t) Probability of user of type t using service class k in the BH

nauk Number of active users in the high load period using service class k

V sk Bandwidth required by an active user for service class k

V ut Bandwidth required for a user of type t

Cu Cost per bandwidth unit of the network element

α Concavity factor for the cost function

Cf Fixed cost of the network element

Ctot Total cost of the network element

Cut Cost associated with a user of type t

Fig. 6 Results from the userand service scenario under atotal bandwidth of 100 Mb/s(PQ: Priority Queuing)

age of the element that each type of user has. This modelassumes that the total bandwidth of an interconnection ele-ment is given and tries to maximise the usage of this capac-ity, which is equivalent to maximising the number of users

which can use this element. The parameters used in the TEL-RIC model are shown in Table 1. The total cost of the net-work element is calculated as a function of the bandwidththat it offers as follows:

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Fig. 7 Unit cost (in monetary units) per user class under real cost function (Segg: segregation, Over-eng: over-engineering, P.Q.: Priority Queuing)

Ctot = Cu · V αtot + Cf (9)

The following TELRIC model provides the cost incurred byone user of type t for the usage of the network element.

nauk =∑

t

Nut · Nu · ac(t) · δt (k) (10)

V sk = Vk

nauk

(11)

V ut = ac(t) ·∑

k

V sk · δt (k) (12)

Cut = Ctot · V ut

Vtot(13)

This model enables the calculation of the total cost by sum-ming up the cost over all network elements of the trafficrouting chain.

4 Application

The network dimensioning and cost model is applied to thedimensioning problem of the interconnection facilities be-tween two FGI or an FGI and any other network type e.g.NGN or 3G mobile networks. The corresponding bandwidthto be provided depends on the network level (access or ag-gregation network)where there is interconnection and hence,the amount of traffic to be interchanged. The wholesale ac-cess or interconnection might be at the lowest level on theend of SAN at an aggregation or Metro switch or at an IPedge switch at the highest one. Differences between eachinterconnection point are directly dependent on the aggre-gated bandwidth, and so the related cost follows differentbehaviors adapted to the specific scenario. A typical caseof interconnection at Metro level would be considering theinterconnection between two Metro nodes, operated by dif-ferent operators. The main objective would be to maximizethe total number of users of the different user types who

Cost models for QoS-differentiated interconnecting and wholesale access services in future generation

Fig. 8 Relative costs for the example scenario (four applications: best effort, real-time, streaming and guaranteed data)

Fig. 9 Costs per user andservice for each QoSmechanism up to a 3 Gbpsinterconnection facility

can be served by the bandwidth provided by the intercon-nection facility. The corresponding individual cost calcu-lations following the proposed cost model. Given the sce-nario explained in Sect. 2.2, with values taken from differ-ent references; see [13, 14], a 100 Mb/s connection providesthe characteristic values shown in Fig. 6. A large numberof users can be aggregated and there is quite a small dif-ference in the maximum number of users mainly betweentraffic separation, integration and over-engineering. Underthe DiffServ concept the application of a priority queuingscheme allows an increment of nearly 10% in users, greaterbandwidth use and a decreasing bandwidth value for eachservice of an active user. This high aggregation of users isonly possible if the aggregation node has a high market pen-

etration of Internet access service. At lower level or whole-sale access points, e.g. at a concentrator or even an xDSLnode, only a low number of users are connected and hencethe corresponding bandwidth of the connection can be re-duced. Additionally, in most European countries there arebetween three and five ISPs offering broadband access toretail users, where in general only the most important nodesaggregate high user values. Figure 7 shows the correspond-ing unit cost development in relation with the bandwidthprovided for the wholesale access connection. Obviously,the reduction of the unit cost under a higher bandwidth anda corresponding higher user aggregation is greater than theincrement of the usage degree might justify. This is causedby the cost function which provides an economy of scale

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effect determined by the concavity factor and the economyof scope effect determined by the fixed cost. The values ofthe figure also show that the influence of the traffic engi-neering mechanism is reduced under increasing bandwidthand the corresponding number of aggregated users. A lowbandwidth access connection implies low usage while underincreasing bandwidth requirements the usage degree of theconnection improves. The total usage of the bandwidth ap-pears in Fig. 6. As the main conclusion we deduce that underincreasing bandwidth of a network element the traffic engi-neering methods become less important. From this, it fol-lows that the most important ISPs have a dominant positiondue to their high bandwidth interconnections and the rest ofthe ISPs have to situate their access point at a higher level ofthe network to reduce the corresponding cost, see [15, 16].Hence, for higher level interconnection facilities beyond theMetro node where the bandwidth of the connections mightbe in the range of OC-12 or 1 Gb/s the aggregated user num-ber and its corresponding traffic is nearly independent of thetraffic engineering methods e.g. in our example results, fora Gbit Ethernet connection, 14586 aggregated users undertraffic separation, 14567 under over-engineering and 14731under a priority queuing scheme with a usage degree of thebandwidth of nearly 99% in the three cases. The service sce-nario establishes a fixed scheme of costs depending on thecharacteristics of the applications independently of the con-nection bandwidth as Fig. 8 shows. Similar results appearfor each QoS provision mechanism. Figure 9 shows theseresults with more details in a range of up to 3 Gb/s. From500 Mbps the behavior of the different mechanisms is notdecisive in the cost scheme calculation, with a clear ten-dency towards a flat cost over 5 Gbps.

5 Conclusions

This paper exposes the practical application of a dimension-ing model for wholesale access and interconnection networkelements among FGN considering different traffic engineer-ing mechanisms (over-engineering, DiffServ and virtual tun-nels), providing QoS in terms of the average delay and ob-taining a statistical behavior of the resulting aggregation,with the objective of reducing the corresponding cost re-lated to wholesale access or interconnection arrangementsamong different providers. As a first consequence of its ap-plication, in high bandwidth scenarios, the traffic engineer-ing mechanism and the QoS consideration does not signif-icantly influence the estimated cost. On the other hand, forlow bandwidths, the unit cost will strongly depend on theselected traffic engineering method. In any case, the ser-vice/application scenario enables the definition of a specificcost distribution, fixed with increasing interconnect band-width. As a conclusion, this paper shows that a TELRIC

model considering QoS and traffic-engineering mechanismsshould be applied mainly for regulating wholesale accessand interconnection in the aggregation network part in or-der to provide a correct cost calculation and price determi-nation.

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Cost models for QoS-differentiated interconnecting and wholesale access services in future generation

Alberto E. Garcia studied telecom-munication engineering at Univer-sity of Cantabria where he receivedhis Ph.D. in 2009. Since 2002 heis Assistant Professor in the Te-lematics Engineering Group of theDepartment of TelecommunicationUniversity of Cantabria (Santander,Spain). He is actually involved inseveral national and internationalprojects. He has participated in spe-cialised conferences and technicalcourses, including more than 30publications.

Laura Rodriguez studied telecom-munication engineering at Univer-sity of Cantabria (Santander, Spain)where she received her Master De-gree in 2002. Currently, she is Ph.D.student in Communication Engi-neering. Since 2002, she works asproject engineer in the TelematicEngineering Group of the Univer-sity of Cantabria, participating inseveral national telecommunicationnetworks cost studies.

Klaus D. Hackbarth studied elec-trical engineering at Berlin Tech-nical University where he receivedhis master degree in 1974 and hisPh.D. in 1984. Since 1992 he holdsa Full Professorship in the Depart-ment of Communication Engineer-ing of the University of Cantabria(Santander, Spain). He worked inDeutsche Telecom (Germany) andTelefónica (Madrid, Spain). He col-laborates with WIK-consult (BadHonnef, Germany) with more thanfifteen techno-economical studiesfor telecom operators and regula-

tors. Klaus Hackbarth published more than 100 papers in scholarshipJournals, book contributions, congresses and conference proceedings.