A Bandwith Assigment Polling Algorithm to Enhance the Efficiency in QoS Long-reach EPONs

EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONSEur. Trans. Telecomms. 2011; 22:35–44

Published online 6 November 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/ett.1449

OPTICAL COMMUNICATIONS

A bandwidth assignment polling algorithm toenhance the efficiency in QoS long-reach EPONsN. Merayo*, T. Jimenez, P. Fernandez, R.J. Duran, R.M. Lorenzo, I. de Miguel and E.J. Abril

Department of Signal Theory, Communications and Telematic Engineering, University of Valladolid, Campus ‘Miguel Delibes’, 47011Valladolid, Spain

ABSTRACT

A novel polling algorithm is proposed to provide subscriber differentiation at the upstream channel in long-reach EPONs.As operators and service providers prefer to operate at loads with no congestion and losses, the developed algorithm hasbeen designed to improve the efficiency for those loads at which the network is likely to work. This new scheme permitsto anticipate the transmission of some packets in order to take advantage of the wasted bandwidth between consecutivetransmissions of ONUs. As a result, not only does this algorithm behave alike other polling algorithms for high loads, but italso improves the efficiency at low and medium loads, leading to a reduction in the mean packet delay. The new algorithmhas been tested in different scenarios, motivated by the increasing interest in enlarging the long-reach EPON distances.Simulation results show that as the distance increases, the algorithm achieves a significant reduction of the mean packetdelay for an extended range of loads. Copyright © 2010 John Wiley & Sons, Ltd.

*Correspondence

N. Merayo, Department of Signal Theory, Communications and Telematic Engineering, University of Valladolid, Campus ‘MiguelDelibes’, 47011 Valladolid, Spain.E-mail: [email protected]

Received 21 December 2009; Revised 27 July 2010; Accepted 2 September 2010

1. INTRODUCTION

Passive Optical Networks (PONs) are an excellent tech-nology to develop access networks, as they provide bothhigh bandwidth and Quality of Service (QoS) [1--2]. ThePON technology uses a single wavelength in each of thetwo directions and such wavelengths are multiplexed on thesame fiber by means of Wavelength Division Multiplexing(WDM). Since all users share the same wavelength in theupstream direction, a Medium Access Control (MAC) isnecessary to avoid collision between packets from differentOptical Network Units (ONUs). Time Division MultipleAccess (TDMA) is the most widespread control scheme inthese networks. However, it is inefficient because the natureof network traffic is neither homogeneous nor continuous[3--4]. In this way, algorithms which distribute the availablebandwidth in a dynamic way, called Dynamic BandwidthAllocation algorithms (DBA), are necessary in order toadapt the network capacity to traffic conditions by chang-ing the distribution of the bandwidth assigned to each ONUdepending on the current requirements [3--7].

Although PON infrastructures are able to provide enoughbandwidth for current applications, both the gradual

increase of the number of users and the bandwidth require-ments of the new emerging services, demand an upgrade ofsuch access networks. Consequently, it exists an increasinginterest in the development of optically amplified PONs inorder to extend the reach and the split ratio of these net-works, thus leading to the so-called long-reach PONs [8].These network architectures are quite cost-effective as theysimplify the infrastructure since the access and the metronetworks can be combined into a single network [8--10].This characteristic, together with advances in WDM allowan increment in the potential number of users in the accessnetwork. These hybrid architectures exploit the advantagesof wavelength assignment of WDM techniques and thepower splitting of TDM methods.

In these WDM architectures a number of powered long-reach PONs---each one with a specific wavelength assignedfor the upstream transmission---are combined using WDMmultiplexers [8--11], and they are treated as independentlong-reach PONs in terms of access level. Therefore, long-reach PONs are Point to Multi-Point (P2MP) high capacityaccess networks based on a tree topology between the OLTand the different ONUs. Moreover, the same medium con-trol access protocols are applied in such infrastructures.

Copyright © 2010 John Wiley & Sons, Ltd. 35

A bandwidth assignment polling algorithm N. Merayo et al.

Then, DBA algorithms are extensively used to distributethe available bandwidth among ONUs in the tree topologyof the long-reach PON.

Long-reach PON is a very promising and emerging archi-tecture in the access segment. However, if DBA methodsdesigned for typical PONs of 20 km are applied to long-reach architectures, they may show inefficient bandwidthutilisation due to the increase of the end-to-end propagationtime. Therefore, appropriate DBA algorithms are highlydemanded for this network architecture. The algorithmproposed for a long-reach architecture, called Two-StateDMB (TSD) [12], takes advantage of the wasted bandwidthbetween consecutive cycles applying a bandwidth predic-tion method by means of traffic estimation. As the nature ofnetwork traffic is neither homogeneous nor continuous, thetraffic estimation may become complex. On the contrary,polling schemes have demonstrated good performance forlong-reach PONs [13]. In these algorithms, the OLT allo-cates bandwidth to each ONU just after received its controlmessage. Thus, the OLT does not have to wait for everyONU control message to assign the bandwidth. This per-formance leads to an efficient bandwidth utilisation andmakes these schemes very simple to implement [14]. How-ever, they can be improved for low and medium networkloads. For this range of loads, it may exist idle time betweenthe transmission of two consecutive ONUs due to the highdistance and the low amount of bandwidth demanded bythe ONUs. Therefore, this idle time could be used in orderto anticipate the transmission of some packets before theyhave been granted, thus reducing their delay. Moreover,these wasted periods of time will appear more frequentlyas the distance increases. Consequently, algorithms whichtake this into account would achieve a better performancein terms of the mean packet delay for networks with higherreach. This would be relevant due to the increasing interestin extending PON distances over 100 km as in the litera-ture it can be found an extensive research and prototypesof PONs [15--20], which expand the distance up to 135 km.Hence, it can be found some prototypes focus on increas-ing the coverage distance but simultaneously optimisingthe optical components needed in such deployment. In thisway, Shea et al. [15] have demonstrated long-reach PONsable to operate at 10 Gbit/s over distances up to 110 kmusing a lower number of EDFA amplifiers in the backhaulsection. Machale et al. [16] proposed hybrid architecturesbased on DWDM-TDM PON able to transmit over 10 Gbit/sand 116 km. Besides, Prince et al. [17] expanded the exper-imental distance up 118 km of fiber. Following the samephilosophy, Kjaer et al. [18] proposed a bidirectional long-reach PON that operates at a symmetric rate of 10 Gbit/sover 120 km. On the other hand, there are other proposals,such as the architecture proposed by Davey et al. [19], whichsucceeds to achieve the deployment of the GPON standardover long-reach PONs up to 135 km. In this way, Shea et al.demonstrated in Reference [20] an experimental prototypeof a long-reach PON with wavelength conversion based onthe GPON standard able to support 1280 subscribers overdistances of 120 km.

On the other hand, in access networks Internet Ser-vice Providers (ISPs) assign multi-service levels accordingto customers’ requirements. End users contract a ServiceLevel Agreement (SLA) with a provider, normally relatedto a minimum guaranteed bandwidth. This forces the accessnetwork to treat each SLA subscriber in a different way.Consequently, DBA algorithms ought to support variousservice levels with bandwidth guarantees. Many studies arerelated to service providers, which offer multi-service lev-els according to subscribers’ requirements. The BandwidthGuaranteed Polling (BGP) method proposed in Reference[5] divides ONUs into two disjoint sets of bandwidth guar-anteed ONUs and best effort ONUs. While the guaranteedONUs receive the demanded bandwidth, the remainingbandwidth is delivered over the best effort ONUs. How-ever, this scheme only differs between guaranteed ONUsand best effort ONUs, but it does not distinguish other pro-files with specific restrictions. Other studies are based onguaranteed requirements to the high priority classes of ser-vice [21--22]. Authors in Reference [21] propose that everyONU supports the same classes of services and the algo-rithm distribute the bandwidth according to the requirementand the priority of each service. In contrast, the algorithmin Reference [22] assigns the available bandwidth to eachclass of service by means of weighted factors. They proposea different profile of weights depending on the congestionlevel of the ONU. If the available bandwidth is enough tocover every service requirements, the algorithm applies anaggressive scheme which offers more resources to the highpriority services. Otherwise, the algorithm applies a con-servative profile among services. However, these schemesdo not distinguish that different ONUs show different SLAprofiles and they only categorised the traffic into classesof service. Therefore, every ONU is similar as they sup-port the same range of services with the same requirements.Hence, a typical way to offer customer differentiation is touse a fixed weighted factor assigned to each ONU associ-ated with a specific SLA. Then, the bandwidth is allocateddepending on these weights. In the method presented inReference [6], each ONU is assigned a minimum guaran-teed bandwidth based on the associated weight, so that theupstream channel is divided among the ONUs in propor-tion to their SLAs. In long-reach architectures, in the TSDalgorithm [12], the OLT distributes the available bandwidthby assigning different weights to each client depending ontheir SLA following a centralised policy. Therefore, ONUsassociated with a higher weight will be assigned more band-width. Moreover, the algorithm proposed in Reference [13],assumes different weights to ensure a minimum guaranteedbandwidth to each profile following a polling policy.

In this paper, it is presented a novel DBA algorithmapplied to a long-reach TDM-EPON for a gradual upgradeof the existing infrastructures, able to differ between ser-vices level profiles. Unlike other DBA algorithms proposedin long-reach EPONs, the new algorithm takes advantage ofthe idle time between transmissions of consecutive ONUswith the aim of improving the mean packet delay for lowand medium loads at which the network is likely to operate.

36 Eur. Trans. Telecomms. 2011; 22:35–44 © 2010 John Wiley & Sons, Ltd.DOI: 10.1002/ett

N. Merayo et al. A bandwidth assignment polling algorithm

These loads are especially interesting for network opera-tors as the network does not show packet losses and thus itoperates under good conditions. Hence, it seems to be verysensible to focus on improving the network performance asmuch as possible for such loads. Furthermore, the Ethernetprotocol has been considered because it is a well knowninexpensive technology and interoperable with a variety oflegacy equipment [1--2].

The paper is organised as follows. Section 2 describesthe new DBA algorithm developed for a long-reach TDM-EPON. In Section 3 the environment and results achievedfrom simulations carried out are presented. Finally, in Sec-tion 4, the most relevant conclusions obtained in this studyare shown.

2. ALGORITHM DESCRIPTION

As well as other polling schemes, the presented algorithmcalled Long reach Highly Efficient Dynamic bandwidthAssigment (LOHEDA), achieves efficient upstream chan-nel utilisation since ONUs are able to transmit as soon asthe previous ONU finishes its transmission. The EPONstandard uses the Multi-Point Control Protocol (MPCP)to properly schedule the communication between the OLTand the ONUs. Two control messages of MPCP are usedto assign bandwidth at the upstream channel, the Reportand the Gate messages. In the Report, the ONU sends thedemanded bandwidth (in bytes) for the next cycle and theOLT sends a Gate message with the allocated bandwidth forthat cycle. Therefore, the OLT allocates bandwidth to eachONU just after receiving its updated demand (i.e. Report).Hence, the OLT assigns bandwidth to each ONU inde-pendently of the status of the remaining ONUs, and theOLT does not have to wait for the queue information ofevery ONU. This leads to an efficient bandwidth utilisationand avoids long packet delay. Contrary to other DBA algo-rithms proposed to long-reach EPONs, the new algorithmis focus on highly improving the network performance atloads which operators tend to use due to the lack of datalosses (low a medium loads).

In order to assign bandwidth at every cycle, the OLTgives to each ONU the required bandwidth as long as thedemand is lower than an established maximum bandwidth.On the contrary, if the demand is higher than the establishedmaximum, the OLT assigns this maximum. However, if anywasted time is detected between the transmissions of twoconsecutive ONUs, an extra bandwidth is added to this allo-cated bandwidth. With this scheme it is achieved an adaptivecycle, whose length depends on the updated demand of theONUs and the priority of the contracted SLA.

In order to explain how LOHEDA makes the bandwidthallocation, it is considered a network scenario with a num-ber of ONUs, Nonus, numbered as i = 0, 1,. . . ,Nonus −1 andk priority profiles (SLAs) numbered as k = 0, 1, . . . , k−1.The scenario assumes an infrastructure which considers oneuser connected to each ONU, which results in a Fibre to theHome (FTTH) architecture. We have taken into considera-

tion this general architecture as most of the proposed DBAalgorithms for PONs apply this approach [1--7, 12--14]. Asa consequence, each user connected to one ONU i con-tracts an only one service level agreement k, which ensuresa minimum guaranteed bandwidth to this user.

Consequently, the allocated bandwidth for eachONUB

onui

alloccan be defined according to Equation (1), whereB

onui

demandis the demanded bandwidth by each ONU at onecycle. This value is reported by each ONU in the con-trol message sent at the end of its transmission. Moreover,B

onui

wastedis the part of the extra bandwidth that correspondsto each ONU when any wasted time exists between thetransmissions of two consecutive ONUs.

Bonui

alloc ={

Bonui

demand + Bonui

wasted if Bonui

demand < Bslakmax

Bslakmax + B

onui

wasted Otherwise(1)

The maximum allocated bandwidth permitted for eachONU depending on its SLA at each cycle time, Bslak

maxis cal-culated using Equation (2). In this equation W slam representsthe weight associated with the SLA m, whereasBcycle available

is the available bandwidth at each maximum cycle (i.e. max-imum cycle time of 2 ms set by the EPON standard). Theterm Nslam

onus represents the number of ONUs associated withSLA m in the long-reach EPON.

Bslakmax = Bcycle available · W slak∑

m

W slam · Nslamonus

(2)

The extra bandwidth assigned to the current ONU(ONUi), when any wasted bandwidth is detected betweenthis ONUi and the following ONUi+1, depends on the cur-rent demand of bandwidth of ONUi in the present cycle.As it is shown in Equation (3), if the demanded bandwidthby this ONUi is higher than zero, all the wasted bandwidthis assigned to this ONU. On the contrary, if its demand isequal to zero, the whole detected wasted bandwidth is notonly assigned to ONUi because it cannot take advantage ofthe entire wasted bandwidth as its demand is null. However,this ONUi is allocated part of the wasted bandwidth sincesome packets may arrive to this ONU until it is allowedto transmit in the next cycle time. In this case, the ONUi

has some extra bandwidth which permits it to transmit thelast stored packets. Moreover, the remaining wasted band-width is distributed among the previous set of ONUs whosecontrol message reporting their allocated bandwidth for thenext cycle has not been sent yet. Then, the bandwidth isshared between several ONUs which may efficiently usethis bandwidth.

Bonui

wasted =

Bwasted if Bonui

demand > 0Bwasted ·W slak∑

k

∑i/onui∈�∩slak

W slakif B

onui

demand = 0 (3)

In Equation (3) Bwasted is the available bandwidth con-tained in the detected wasted time.�represents the groupof ONUs involved in the distribution, that is, the number

Eur. Trans. Telecomms. 2011; 22:35–44 © 2010 John Wiley & Sons, Ltd. 37DOI: 10.1002/ett


Figure 1. Example of operation of LOHEDA algorithm.

of ONUs whose control messages have not been sent yet.Moreover, the term i/onui∈�∩slak represents the numberof ONUs of this subgroup � which also belongs to thesubgroup of ONUs with a SLA k. Hence, the distributionof the wasted bandwidth is made not only considering thedemanded bandwidth, but also considering the priority ofthe associated SLA.

In order to comprehend better this algorithm, it is con-sidered the particular situation presented in Figure 1. Inthe instant t1, LOHEDA receives the bandwidth demand ofONU2 for the next cycle (N + 1). As LOHEDA follows apolling policy it schedules the transmission for every ONUjust after receiving its bandwidth demand in the controlmessage called Report, according to the EPON standard.Therefore, at t1LOHEDA assigns bandwidth to ONU2 andconsequently it calculates the time when this ONU ends itstransmission (t3) for the next cycle N + 1.

In order to know if there is idle time (i.e. wasted band-width) between the end of the transmission of ONU2(t3) andthe beginning of the transmission of the next ONU (ONU3)the algorithm follows the next steps. At t1LOHEDA knowsthe end of the transmission of ONU3 at cycle N, as it keeps atrack of the allocated bandwidth of previous ONUs. Then,it can schedule the transmission for ONU3 and send it acontrol message called Gate (according to the EPON stan-dard) to inform it about the allocated bandwidth for cycleN + 1. The OLT can send this Gate message immediatelyif previous ONUs in the cycle have ended their transmis-sion by the time this message arrives to ONU3. Otherwise,the OLT has to wait some time so that ONU3receives theGate when the previous ONU (ONU2) has just ended itstransmission to avoid collisions with it. As a consequence,under this situation there is not wasted time between consec-utive transmissions. Among both situations the minimumtime the ONU3 has to wait to transmit in the cycle N + 1

is achieved in the former one and under this situation itmay appear wasted bandwidth between the transmissionof ONU2and ONU3. Therefore, the transmission of ONU3

starts at least in t4 because even if one ONU does not needto wait to the end of the previous ONU transmission, it hasto wait a minimum time imposed by the propagation timeRTT (Round Trip Time) and the processing time of the Gatemessage (tgate). Then, if the ONU3 finishes its transmissionin cycle N by t2, its transmission for the next cycle startsas minimum in t4 = t2 + RTT + tgate since it does not haveto wait to the end of the transmission of ONU2. Since t4

is greater than t3, LOHEDA detects wasted time betweenthese two consecutive ONUs: ONU2and ONU3.

Then, following Equation (3), if the demanded bandwidthby ONU2 in t1 is different from zero, all the wasted band-width is entirely added to the assigned bandwidth of ONU2

as it is seen in Figure 1(a). On the contrary, if the demandedbandwidth of ONU2 is equal to zero, the detected wastedbandwidth is distributed between ONU1 and ONU2---Figure1(b),---because in such figure it is noticed that at t1 theircontrol messages Gate have not been sent yet.

3. PERFORMANCE EVALUATION

3.1. Simulation scenario

Simulations were made considering a TDM-EPON with 16ONUs and one user connected to each ONU using OPNETModeler 14 [23]. The transmission rate of the upstream linkbetween ONUs and the OLT is set to 1 Gbit/s and the accesslink from the user to each ONU to 100 Mbit/s [1--7, 12--13].The distance between ONUs and the OLT is set to 100 km,which is the typical distance assumed for a current long-reach EPON [8--11]. In order to avoid collisions between



adjacent ONUs, a guard time of 1 µs is chosen, a valuewithin the limits specified by the standard IEEE 802.3ahD1.414 [24].

As the long-reach TDM-EPON takes into considerationsubscriber differentiation, it is presented a scenario withthree priority SLAs: SLA0 for the highest priority ser-vice level, SLA1 for the medium priority service level andSLA2 for the lowest priority service level. In general, onlyvery few conventional users contract high level agreementconditions, whereas users tend to contract medium or lowpriority service level profiles. Therefore, in this study it isconsidered that the 6.25% of the users contract high levelconditions, the 31.25% contract medium level conditionsand the 62.5% contract the low level conditions. As a con-sequence, it is assumed that one ONU contracts the highestpriority service level agreement SLA0, five ONUs contractthe medium priority service level SLA1 and ten ONUs thelowest priority service level SLA2. Related to the assignedweights to each SLA(W slak ), it has been set the W sla0 = 4,W sla1 = 3and W sla2 = 2 as well as other other publishedstudies [12--13]. These weights are considered to complywith the NTT DSL service plans (50/70/100 Mbit/s) [25].Thus, each SLA should be offered this guaranteed band-width when the bandwidth demand of every SLA exceedsthe available bandwidth of the upstream shared channel.

Packet generation follows a Pareto distribution with aHurst parameter, H, equal to 0.8, considering them of vari-able length (from 64 to 1518 bytes). This maximum packetlength is assumed because it is the MTU of the standardIEEE 802.3. Moreover, the maximum cycle time is setto 2 ms, limited by the standard IEEE 802.3ah D1.414[24]. The relationship between the total network load(ρnetwork) and the ONU load (ρonu)is displayed in Equa-tion (4). In this equation,Nonusrepresents the number ofONUs in the network, EPON Line rate the transmissionrate of the upstream link between ONUs and the OLT andUSER Line rate the access link from the user to each ONU[7].

ρonu = EPON Line rate

USER Line rate· ρnetwork

Nonus(4)

Related to the evaluation of the algorithms, LOHEDAis compared with LIPSA to analyze the improvementsachieved by the former, since LIPSA demonstrated higherefficiency compared to other proposed algorithms in long-reach EPONs [13]. Finally, in order to make a correctstatistical analysis of results, they are represented within95% of confidence level.

3.2. Simulation results

Figure 2 represents the upstream channel throughput versusthe total network load when LOHEDA and LIPSA algo-rithms are compared. As it can be observed in the figure,both algorithms achieve the same throughput for every load,and therefore both of them show the same high efficiency.

Figure 2. Upstream channel throughput versus total networkload of LOHEDA and LIPSA algorithms.

As the upstream channel has a capacity of 1 Gbit/s, fol-lowing Equation (4), for network loads nearby 1 it starts toappear packet losses as the channel is completely full. Thusthe range of network loads from 0 to near 1 is interestingfor operators and providers as there are not losses. In thisway Figure 3 represents the total upstream demanded andoffered bandwidth versus the network load (from 0 to 1) forLIPSA and LOHEDA algorithms.

As it can be observed both algorithms entirely offers thetotal demanded bandwidth (Bdemand) up to network loadsnear 1. However, for loads very close or higher than 1the required bandwidth is higher than the channel capacity(1 Gbit/s). Although LOHEDA achieves the same chan-nel throughput than LIPSA for these loads it has beendesigned to enhance the network performance. In partic-ular, LOHEDA permits to anticipate the transmission ofsome packets in order to reduce the mean packet delay andthe queue size of every SLA.

Thus, Figure 4 represents the mean packet delay versusthe total network load for the three supported SLAs (SLA0,SLA1 and SLA2) when LOHEDA and LIPSA algorithmsare compared. As it can be seen, for low and medium net-work loads, which have a significant interest for service

Figure 3. Total bandwidth demand and total offered bandwidthversus total network load of LIPSA and LOHEDA algorithms.



Figure 4. Mean packet delay versus total network load of LIPSAand LOHEDA algorithms for each subscriber (SLA0, SLA1 and

SLA2).

providers, LOHEDA shows lower delay than LIPSA forthe three SLAs.

In particular, LOHEDA achieves a noticeable improve-ment compared to LIPSA for the lowest network load (0.2)obtaining differences near 1E-3 s for every SLA. Moreover,LOHEDA keeps the mean packet delay under or equal to1E-3 s up to network loads of 0.6 for the two highest priorityprofiles, SLA0 and SLA1, and up to network loads of 0.4for the lowest priority profile (SLA2).

The improvements achieved by LOHEDA are due to thetransmission in advance of some packets. In order to demon-strate it, Figure 5 shows the average queue size just afterthe transmission of packets versus the total network loadfor the three supported SLAs and for both algorithms. Itcan be noticed that for all the represented network loads,the size of the queue is much lower for LOHEDA than forLIPSA. In particular, the former achieves differences up toone magnitude for every SLA at network loads around 0.2.

In addition, Figures 6 and 7 are histograms which showthe percentage of time in which the queue size (in bits) islocated in a different range of values. The histogram gives

Figure 5. Average queue size versus total network load ofLOHEDA and LIPSA algorithm for each subscriber (SLA0, SLA1

and SLA2).

Figure 6. Histogram of the queue size versus time for LOHEDAand LIPSA algorithms for SLA0 subscribers.

a rough approximation of the frequency distribution of thedata as it stores samples of the queue size falling in var-ious ranges along the simulation time. In particular, it isrepresented the performance of the SLA0 and SLA2 pro-files for a load of 0.2. It is assumed that the size of thequeue is measured just after each ONU of one SLA hasended its transmission at every cycle. As the RTT is highlyincreased to 1 ms due to the end to end distance of 100 km,there are several packets which arrive to one ONU that haveto wait at least for the next cycle to be sent out. However,LOHEDA allows ONUs to take advantage of the extra allo-cated bandwidth in every cycle so that ONUs can schedulethe transmission of these packets at the current cycle. Thus,LOHEDA succeeds in keeping lower queue size than LIPSAsince packets do not have to wait to be transmitted in sub-sequent cycles, as it can be seen in Figure 6 for the highestpriority subscribers SLA0.

It is remarkable that the 100% of the time, LOHEDAkeeps the queue under 5000 bytes. In contrast, LIPSA onlykeeps the queue size under this value the 35% of the timeand it can be observed that most of the time the queue storesa higher number of bits.

Figure 7. Histogram of the queue size versus time for LOHEDAand LIPSA algorithms for SLA2 subscribers.



Figure 8. Mean packet delay versus total network load anddistance for SLA0 subscribers when LIPSA and LOHEDA are

compared.

The same performance can be noticed for the lowest pri-ority subscribers SLA2 in Figure 7 However, it can be seenthat LOHEDA maintains a higher queue size for SLA2 sub-scribers when compared to SLA0 subscribers (Figure 4).Hence, the higher the priority of the service level profile is,the better performance LOHEDA is able to achieve whencompared to LIPSA.

Since nowadays there is a great interest in developingextended PONs, the second part of this study is focused onthe evaluation of LOHEDA when increasing the distance.In Figures 8--10, it is represented the mean packet delayversus the total network load for SLA0, SLA1 and SLA2

respectively, for distances between 100 and 150 km (stepsof 10 km) when LOHEDA and LIPSA are compared.

It can be noticed in every figure that as the distanceincreases, LOHEDA performs better than LIPSA, achievinglower values of the mean packet delay for every SLA and


compared.


compared.

distance. In fact, LOHEDA achieves delays under or around1.5E-3 s for all the distances and network loads up to 0.6.It means that LOHEDA keeps the mean packet delay underthe maximum limited delay for real-time applications in theaccess [26], which are the most restricted ones regarding themean packet delay. On the contrary, LIPSA always obtainsdelays above this value for most of the considered loadsand distances. For the highest priority profile SLA0 (Figure8), LOHEDA reduces to half the delay achieved by LIPSAfor every distance and loads up to 0.6. Besides, LOHEDAis able to keep delays under 1.5E-3 s for every representednetwork load (up to 0.8) at distances up to 140 km. Forthe medium priority profile SLA1 (Figure 9), the perfor-mance is similar, since LOHEDA keeps the same delay upto distances of 120 km.

Furthermore, the range of network loads which exper-iments improvements and the differences between theobtained values expand with the distance too.

Figure 11. Mean packet delay versus total network load anddistance for SLA0 when LIPSA and LOHEDA are compared in

distances of 50--100 km.





This improvement is more remarkable for SLA2 sub-scribers, as it can be seen in Figure 10. In fact, LOHEDAobtains significant differences of up to 5E-3 s for loads of0.8 and distances of 150 km. Although it is not representedin Figure 10, this difference in seconds is even kept up toloads of 1.0.

Although it has been shown that LOHEDA increases itsperformance in long-reach distances (Figs 8--10), it also canbe used in low distances with similar results. To demonstrateit, Figures 11--13 represent the mean packet delay versusthe network load for SLA0, SLA1 and SLA2 profiles, fordistances from 50 to 100 km (in steps of 10 km). In the threegraphs it can be observed that LOHEDA reduces the meanpacket delay when compared to LIPSA independently ofdistance. However, it is remarkable that LOHEDA reacheshigher differences with LIPSA as the distance increases. Asa consequence, LOHEDA achieves better results for long-



reach distances in spite of the fact that it can be applied indifferent end-to-end EPONs.

4. CONCLUSIONS

In this paper, a novel polling algorithm called LOHEDAis proposed to provide high efficiency in a subscriber dif-ferentiated long-reach EPON. Although polling algorithmspresent good performance, their efficiency can be improvedfor low and medium network loads. These loads are veryinteresting for operators due to the lack of congestion andlosses.

LOHEDA has been compared with LIPSA, an algorithmfor long-reach EPONs which considers client differenti-ation and shows robustness and better results than otheralgorithms proposed for these architectures. Simulationresults show that not only does LOHEDA achieve the samethroughput efficiency but also regarding mean packet delay,LOHEDA achieves improvements for every SLA for thosenetwork loads at which the network is likely to work. Infact, LOHEDA is able to reduce to half the delay obtainedby LIPSA for every service level profile at certain networkloads. This enhancement in performance is possible sinceLOHEDA manages to keep lower queue size than LIPSAfor every load and service level profile by anticipating thetransmission of some packets before they are granted.

This improvement is also noticed when the distanceis highly expanded. It has been demonstrated that as thedistance increases, LOHEDA achieves lower delays foran extended range of networks loads when comparedto LIPSA. Therefore, for all the service levels profilesand distances considered, LOHEDA can achieve delaysaround 1.5E-3 s for certain network loads. It means thatfor this range of loads LOHEDA obtains similar delaysthan real-time traffic which is the most restrictive one interms of delay. Furthermore, for the lowest priority profileSLA2, LOHEDA is able to achieve differences of 5E-3 swhen compare with LIPSA for certain network loads anddistances.

ACKNOWLEDGEMENTS

This work has been supported by the GR72 ExcelenceGroup funding by the Regional Ministry of Castilla y Leon(Junta de Castilla y Leon).

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Authors’ Biographies

Noemi Merayo received the Telecommunication Engi-neer degree in Engineering from the Valladolid University,Spain, in February of 2004 and the Ph.D. degree in the Opti-cal Communication Group at the University of Valladolid,in July 2009. Since 2005, she has been working as a JuniorLecturer at the University of Valladolid. She has also beena visiting research fellow at the University of Hetforshire(London), working in the Optical Networks Group, Science



and Technology Research Institute (STRI). Her doctoralresearch focused on the design and performance evaluationof optical networks, especially passive optical networks.

Tamara Jimenez received her Telecommunication Engi-neer degree from the University of Valladolid, Spain, in2008. She is currently carrying out studies to obtain thePh.D. degree in the Optical Communications Group at theUniversity of Valladolid. She is also working with this groupand collaborating with CEDETEL. Her current researchfocuses on the design and performance evaluation of opticalnetworks, especially long reach passive optical networks.

Patricia Fernandez obtained the TelecommunicationEngineer degree from Universidad Politecnica de Cataluna,Barcelona, Spain, in 1997 and the Ph.D. degree in 2004 fromUniversity of Valladolid. Since 1999, she has been work-ing as a Junior Lecturer at the University of Valladolid. Herresearch interests are passive optical networks and fiber-optic communications components. Dr Fernandez is theauthor of more than 40 papers in international journals andconferences.

Ramon J. Duran received his Telecommunication Engi-neer degree in 2002 and his Ph.D. degree in 2008, both fromthe University of Valladolid, Spain. Since 2002, he has beenworking as a Junior Lecturer at the University of Valladolidand currently he is also Secretary of the Faculty of Telecom-munication Engineering. He is a member of the OpticalCommunications Group at the University of Valladolid. Hiscurrent research interest focuses on the design and perfor-mance evaluation of wavelength-routed optical networks,especially hybrid architectures for optical networks.

Ruben M. Lorenzo received his Telecommunication Engi-neer and Ph.D. degrees from the University of Valladolid,Spain, in 1996 and 1999, respectively. From 1996 to 2000,

he was a Junior Lecturer at the University of Valladolid,and joined the Optical Communications Group. Since 2000,he has been a Lecturer. His research interests includeintegrated optics, optical communication systems and opti-cal networks. He is currently the Head of the Faculty ofTelecommunication Engineering at University of Valladolidand Research Director of CEDETEL (Center for the Devel-opment of Telecommunications in Castilla y Leon).

Ignacio de Miguel received his Telecommunication Engi-neer degree in 1997, and his Ph.D. degree in 2002, bothfrom the University of Valladolid, Spain. Since 1997, hehas been working as a Junior Lecturer at the University ofValladolid. He has also been a visiting research fellow atUniversity College London (UCL), working in the Opti-cal Networks Group. His research interests are the designand performance evaluation of optical networks, especiallyhybrid optical networks, as well as IP over WDM. Dr deMiguel is the recipient of the Nortel Networks Prize to thebest Ph.D. Thesis on Optical Internet in 2002, awarded bythe Spanish Institute and Association of Telecommunica-tion Engineers (COIT/AEIT). He also received the 1997Innovation and Development Regional Prize for his Grad-uation Project.

Evaristo J. Abril received his Telecommunication Engi-neer and Ph.D. degrees from Universidad Politecnica deMadrid, Spain, in 1985 and 1987, respectively. From 1984to 1986, he was a Research Assistant at UniversidadPolitecnica de Madrid, and he became a Lecturer in 1987.Since 1995, he has been Full Professor at University ofValladolid, Spain, where he founded the Optical Com-munications Group. He is currently the Chancellor of theUniversity of Valladolid. His research interests include inte-grated optics, optical communication systems and opticalnetworks. Professor Abril is the author of more than 100papers in international journals and conferences.


A Bandwith Assigment Polling Algorithm to Enhance the Efficiency in QoS Long-reach EPONs

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