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Abstract—WDM-based passive optical network upgrades

from traditional single wavelength TDM-PON to satisfy the growing traffic demands in the access network. Various Dynamic Wavelength and Bandwidth Allocation algorithms (DWBA) for WDM-PON have been studied. These DWBA algorithms always separate the bandwidth allocation from wavelength assignment. In our previous work , we introduced a SLA (service level agreement) based dynamic resource allocation scheme where ONUs are formed into different groups, and the limited inter-wavelength multiplexing is used. In this article, we present a new algorithm, which relaxes the restriction to further increase the statistical multiplexing opportunities among different ONUs. We also improve early allocation scheme to support the network under heavy load, further improving network utilization. In addition, we enhance excess bandwidth allocation scheme to further improve network performance. We use extensive simulations to compare the proposed algorithm with the algorithms from previous works. The results have shown that the newly-proposed algorithm outperforms the existing algorithms.

Index Terms—Dynamic Wavelength and Bandwidth Allocation (DWBA), WDM-PON. Quality of Services.

I. INTRODUCTION Wavelength division multiplexing (WDM) based Ethernet

passive optical networks (EPONs) have been considered as one of promising technologies for next generation access network to provide sufficient bandwidth to the increasing end-users application such as IP telephony (VoIP), Video-on-demand, High Definition TV (HDTV) and high-quality audio transmission due to their low operational costs and huge bandwidth [1]. How to provide effective and fair resource allocation to Optical Network Units (ONUs) has become one of key factors to ensure the success of WDM-PON deployment. The most challenging task for resource allocation comes from upstream transmission, where ONUs share multiple wavelengths to transmit packets to Optical Line Terminal (OLT). Similar to its predecessors, for upstream transmission allocation, WDM-PON uses the basic MPCP protocol to collect resource requests from ONUs via REPORT messages, and disseminate the resource

Xin Ye and M.A.Ali are with the Electrical Engineering Department,

Graduate School of The City University of New York, New York, NY 10016 USA (e-mail: xinye@ ee.ccny.cuny.edu; ali@ccny.cuny.edu).

Chadi M Assi is with Concordia Institute, Information Systems Engineering Department, Concordia University, Montreal, QC H3G 1M8, Canada (e-mail: assi@ciise.concordia.ca).

assignment results to ONUs through GATE message . How to support effective resource allocation in

WDM-PON has been extensively studied lately[1-5]. In [1], we proposed Enhanced Dynamic Bandwidth Allocation (EDBA) scheme, where, the ONUs are divided into K groups based on their service level agreement (SLA), and K is the number of wavelengths in PON, further one wavelength is selected as the default wavelength for each group, and the lightly loaded ONUs always use the default wavelength for upstream transmission to avoid frequent wavelength switching and simplify management. However, the potential drawback of EDBA is that it doesn’t handle the bursty traffic very well. The authors of [2] proposed a WDM extension to IPACT [3] to use strict priority based scheduling for bandwidth allocation and first fit based wavelength selection. In [5], the authors extended EPON based DBA algorithms in [4] and came up with three variants of the WDM DBA schemes; among three variants, two phase based DWBA has the best performance. This scheme offers heavily loaded ONUs two sub-timeslots within the one transmission cycle, hence adding extra complexity into network resource allocation process, furthermore the more guard time is introduced for each heavy loaded ONUs. To address this problem, [6] proposed so called Just-In-Time (JIT) online scheduling framework which schedules ONUs as soon as their REPORTs are received at OLT. However, due to the fact that JIT excludes the cycle based DBA concept, lightly loaded ONUs get more chances to transmit than heavy loaded ONUs, leading to unfair bandwidth allocation, in addition, imminent bandwidth allocation prevents the heavily loaded ONUs from using excess bandwidth saving from lightly loaded ONUs, the performance for heavily loaded ONUs is expected to be degraded.

In this paper, we will introduce a new Integrate Dynamic

Wavelength and Bandwidth (IDWBA) to further increase the statistical multiplexing opportunities among different ONUs and our contributions come from the following aspects: 1) extending early bandwidth allocation to make sure no bandwidth waste caused by Round Trip Time (RTT) from GATE message within any cycle, and each ONU only gets one timeslot per cycle, thus the overhead introduced by [5] can be drastically reduced. Meanwhile, keeping every ONU get one timeslot per cycle avoids unfair resource access in [6]; 2) enhancing excess bandwidth allocation in [5] to improve excess bandwidth utilization. This paper is organized as follows: in section II, describes

Integrated Bandwidth Allocation and Wavelength Assignment in WDM-PON Networks

Xin Ye, Chadi M. Assi, and Mohamed A. Ali.

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MAN/WAN

OLT

Rx ONU

Rx ONU

1: N splitter

Rx

Tx

Tx

Rx

WDM-PON architecture and its corresponding media access control protocol. In section III, the new IDWBA algorithm will be presented. Section IV presents our simulation study; finally section V concludes this paper.

II WDM PON ARCHITECTURE & MAC PROTOCOL The development of protocols and algorithms for

WDM-PON is currently at their initial stage due to the fact that there is no suitable standard network protocol [9-11]. A comprehensive review of WDM-PONs has been presented in [11].

1. WDM-PON Architecture We assume WDM-PON variation I in [11] as our studied

architecture. In this architecture, each ONU has either tunable transceiver or an array of multiple fixed transceivers (each has its own wavelength) to transmit traffic to OLT in the upstream direction. In the case of the fixed transceivers, at any time, only one wavelength is used, the automatic switch circuit is used to control the on/off status of transceivers. In the OLT side, an array of fixed transceivers are deployed, here the number of transceivers is equal to the number of wavelengths supported in network. The bandwidth allocation and wavelength assignment algorithm is implemented at OLT, and the OLT can simultaneously receive data from the various ONUs on different wavelengths and transmit data and control messages to the ONUs. An example of WDM-PON architecture is shown in Figure 1.

Figure 1 WDM-PON architecture

2. Multipoint Control Protocol (MPCP) extension MPCP developed by the IEEE802.3ah Task Force [13]

has been used to arbitrate time-slots among OLT and ONUs in EPON. To support the upgrade from EPON to WDM-PON, the MPCP has to be extended to enable multiple wavelength support. In WDM extension to MPCP, the ONUs send REPORT messages to OLT to request the bandwidth and the supported wavelength information, OLT then executes the dynamic bandwidth allocation and wavelength assignment algorithm to calculate the upstream transmission time slot and corresponding wavelength for all ONUs. Once the transmission slot and wavelength for a

specific ONU is determined, the OLT sends GATE message to this ONU with the transmission schedule of the ONU (i.e., transmission start time, transmission length, and corresponding wavelength channel identifier).

III INTEGRATED DYNAMIC WAVELENGTH AND BANDWIDTH ALLOCATION (IDWBA)

Unlike EDBA proposed in [1], where the early allocated ONUs have to use the default wavelength, our new algorithm relaxes this restriction and makes fully dynamic wavelength and bandwidth integrated. In this way, we expect that IDWBA further increases statistical multiplexing opportunities. The IDWBA consists of two steps: 1) Initialization: based on SLA and transmission overhead, IDWBA calculates the minimal guaranteed bandwidth that OLT needs to provide for each ONU; 2) Real time wavelength selection and bandwidth allocation: IDWBA computes bandwidth assignment and wavelength selection for each ONU based on the bandwidth requests carried by REPORT message(s) and the minimal guaranteed bandwidth.

A. Minimal guaranteed bandwidth calculation

The minimum guaranteed bandwidth iMinB for ONUi

defined in [4], is dependant on the weight assigned to each ONU based on the SLA between the service provider (SP) and users. We consider a PON with N ONUs, and the OLT supports K wavelengths, here, we assume K<N, and the transmission speed per wavelength is R (Mbps). The tunable transmitter at ONUs can be tuned into any wavelength supported by OLT. The tuning time of the tunable laser is in the order of us1 . We denote CycleT as the

grant cycle. Within a grant cycle, every ONU is granted a timeslot to transmit packets to OLT. Further, we also denote Tg as the guard time that separates the transmission window between ONUi and ONUi+1, uT as the tuning time for a

transmitter tuning into different wavelength, and iw as the weight assigned to each ONU based on its SLA such that

∑=

N

iiw

1 = 1. Therefore, the minimum guaranteed bandwidth

per cycle the OLT can allocate for an ONUi is computed as follows:

8)( iugcyclei

Min

wRKTKTNTB

××××−×−= (1)

In case of no SLA classification per ONU,

,,1 iN

wwi ∀== and 11

=∑=

N

iiw ,

NRKTKTNT

B ugcycleiMin 8

)( ×××−×−= (2)

B. Real time wavelength & bandwidth allocation The IDWBA gives transmission opportunity for each

ONU within one cycle, generally the maximal length of a cycle is 2ms according to [5]. Within a cycle, the ONUs sends REPORT messages to request transmission window

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for next cycle. Upon receiving REPORT(s), the OLT runs real time wavelength and bandwidth allocation to determine the time slot and the selected wavelength for ONU(s). We define i

assignB as the assigned bandwidth to ONUi, and i

qBRe as the requested bandwidth by ONUi.

The real time wavelength selection and bandwidth

allocation has two components: early allocation and regular WDM based DBA. Different from [5], there is always early allocated ONUs within a cycle. There are two early allocation scenarios: 1) there are lightly loaded ONUs within a grant cycle, for lightly loaded ONUs, i.e., i

Mini

q BB ≤Re ,

the OLT conducts allocation for them right after receiving their REPORTs, i.e, i

qiassign BB Re= and the wavelength

with the least load will be selected. 2) there is no lightly loaded ONU in a cycle, then the schemes in [5] assign resources for all ONUs only after receiving all REPORTs, the resources between the time that OLT sends first GATE message and the time the first ONU sends out data get wasted. This wasted time is equivalent to single trip delay (STD) from OLT to ONU and processing delay at ONU. In order to reduce this kind of bandwidth waste without missing the opportunity of accessing excess bandwidth, we propose Just-Enough-Time (JET) allocation scheme to schedule the least loaded ONUs at time:

gprocesSTDavailresourcestart tttt sin_ −−= ,

Here, availresourcet _ is time when the wavelength is

available for next cycle transmission, and we allocate iMin

iassign BB = for the selected ONUi. Since the least

loaded ONUs are used for JET, this makes sure the unfairness is very limited.

The regular WDM based DBA component deals with those unallocated ONUs having heavy load (i.e., i

Mini

q BB >Re ) after all REPORTs are received.

Resource allocation for heavy load ONUs will leverage the extra saving bandwidth from lightly load ONUs. Assume there are M lightly loaded ONUs, the extra saving bandwidth from these lightly loaded ONUs

is ∑−

=−=

1

0Re )(

M

i

iq

iMin

Totalextra BBB , where i

qiMin BB Re> . The

heavily loaded ONUs will get extra bandwidth from TotalextraB

in addition to its guaranteed bandwidth, i.e., ii

extraiassign BBB min+= . To compute i

extraB , we assume

each heavily loaded ONU gets the same share of excess

bandwidth (MN

BB

Totalextra

extra −= ), and we sort the

unallocated ONUs according to their requested bandwidth, and the ONUs having the lower requested bandwidth are

always scheduled first, and TotalextraB is always updated after

one heavily loaded ONU gets assigned. Then for a given heavily loaded ONUi

:

+>+<−

=extra

iMin

iqextra

extraiMin

iq

iMin

iqi

extra BBBifBBBBifBB

BRe

ReRe (3)

And

LBBBBB

Totalextra

extraiextra

Totalextra

Totalextra =−= , (4)

Here L is the number of remaining unallocated ONUs. The pseudo code of the IDWBA algorithm is shown in

Figure 2. It consists of three functions: the main IDWBA function, Grant_on_fly function for early allocation, and Run_wdm_dba function for the resource allocation for heavily loaded ONUs.

IV PERFORMANCE EVALUATION To validate our algorithm, we develop a WDM-PON

event driven simulator in C++. This simulator consists of two modules: a module simulating ONUs and a module simulating OLT. To simplify the simulator, we will ignore the downstream traffic transmission.

The following are some parameters used in our simulation:

The number of ONUs N=32; the number of Wavelengths channels K=2; maximum cycle time = 2 ms; PON Channel speed R = 1 Gbps; distance between OLT and ONU is 20Km; the guard time=1 sµ ; the tuning time =1 sµ ; End-users/ONU link speed is 100Mbps; the distance between ONU and the passive splitter is 5 Km; buffering queue size is 1Mbytes. An extensive study shows that most network traffic (i.e., http, ftp, variable bit rate (VBR) video applications, etc.) can be characterized by self-similarity and long-range dependence (LRD) [7]. To model the bursty nature of Internet traffic, we generated self-similar traffic based on Pareto distribution with a Hurst H=0.8; the source code was provided by [5], where packet sizes are uniformly distributed by 64 and 1518 bytes.

In the simulation, we conduct performance analysis of our

algorithm against previous EDBA in [1] and DWBA–3 control excess algorithm in [5]. The performance parameters we compare are: average packet delay, maximum packet delay, and network throughput.

Figure 3 presents the network average delay for IDWBA, EDBA and DWBA respectively. Here, the traffic load of

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IDWBA() { Early__allocation_flag=0; Num_HeavyLoad=0; While (receive_Report( ONUi )) {

if ( i

qBRe <=iMinB )

{ TotalextraB += MinB -

iqBRe

Grant_on_fly(i

qBRe , i,);

Early_allocation_flag=1; } Else {

if ( startcurrent tt ≥ )

{ if (Early_allocation_flag==0)

Grand_on_fly(iMinB , i)

} Else Num_HeavyLoad++; } if (i==N)

{

Run_wdm_dba(TotalextraB ,Num_HeavyLoad);

i=0; Break; } i++

} }

Grant_on_fly( qBRe , i)

{ iassignB =

iqBRe ;

Max_Capacity=0; for (j=0; j<K; j++) if (max_cap<channel_capacity[j]) { Max_Capacity = channel_capacity[j]; lambda=j; } } Update (channel_capacity);

Send the GATE(R

Biassign , lambda)

to ONUi; }

Run_wdm_dba(TotalextraB , Num_HeavyLoad)

{

Sort( qBRe ); // sort the remaining unassigned bandwidth)

for (j=0; j<Num)HeavyLoad; j++) {

extraB =TotalextraB /(Num_HeavyLoad –j);

Find the corresponding ONU i;

if (i

qBRe <iMinB + extraB )

;iexcessB = i

qBRe -iMinB ;

else iexcessB = extraB ;

iassignB =

iMinB +

iexcessB ;

max_cap=0, lambda=0; for (k=0; k<=K; k++) if (max_cap<channel_capacity[k]) { max_cap=channel_capacity[k]; lambda=k; } Update(channel_capacity);

Send GATE (R

Biassign , lambda) to ONUi;

TotalextraB =

TotalextraB -

iexcessB ;

} }

Figure 2: Psuedo code for the proposed IDWBA.ONUs varies from 0.1 to 0.9. Under lightly load (load<=0.3), these three algorithms archive similar performance. Under medium load (where 0.3<load <0.6), IDWBA and EDBA outperform DWBA. Since in EDBA and IDWBA, the heavy loaded ONUs have opportunities to exploit the resources from all wavelengths. When network load becomes heavy, EDBA’s performance will be similar to the performance of DWBA because the network is overloaded, and there is no ONU that is qualified for early allocation. Due to the fact that IDWBA employs the enhanced early allocation scheme to allow early resource allocation for even heavy loaded ONUs, hence, the performance of IDWBA is better than the previous two algorithms. In Figure 4, we compare the maximum delay under IDWBA, EDBA, and DWBA. When the link load is very light (load <=0.2), there is a small amount of traffic in the network, these three algorithms have the similar results in maximum delay. Since IDWBA always tunes to the maximum capacity wavelength, wavelength-tuning time adds additional delay to the maximum delay of IDWBA. When the link load is medium (0.3< =load < 0.6), DWBA has the worst performance since it always uses the default wavelength while EDBA has the best performance since it always tries to use its default

0

0.0 2

0.0 4

0.0 6

0.0 8

0 .1

0.1 2

0.1 4

0.1 6

0 0.2 0 .4 0.6 0 .8 1

Link Load

Ave

rage

Del

ay(S

econ

d)

EDBA

DWBA

IDWBA

Figure 3. Average Packet Delay V.S. Link Load

wavelength first, if the default wavelength‘s capacity is not enough, then it will turn to other wavelength to transmit. IDWBA’s performance is not as good as EDBA because of the delay introduced by wavelength switching. When the link load becomes heavy, IDWBA achieves the best results while DWBA and EDBA have the similar results. Since IDWBA fully integrate the dynamic bandwidth allocation and wavelength assignment together, and enhanced early allocation scheme can improve network utilization, hence, even though the network is overloaded, IDWBA can still achieve relatively

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ideal results.

0

0.0 2

0.0 4

0.0 6

0.0 8

0 .1

0.1 2

0.1 4

0.1 6

0 0.2 0 .4 0 .6 0 .8 1

Link Load

Max

imal

Del

ay( S

econ

d)

EDBA

DWBA

IDWBA

Figure 4. Maximum Packet Delay V.S. Link Load

Figure 5 shows the throughput of these three algorithms.

As we expected, IDWBA always achieves better performance than EDBA and DWBA. With the increasing network link load, the throughput also increases. IDWBA picks up to around 92% at a network link load of 0.5 and keeps this throughput while the network link load increases to 0.9. However, the throughput improvement of IDWBA over EDBA is not significant, since EDBA utilizes traffic grooming to evenly distribute traffic into different wavelengths and it also allows limited wavelength.

0

0.2

0.4

0.6

0.8

1

1.2

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Link Load

Thro

ughp

ut EDBA

DWBA

IDWBA

Figure 5. Throughput V.S. Link Load

As we can see from Figure 3 to Figure 5, when the traffic

load is light, there is no big difference among these three algorithms, since the OLT has enough resources to accommodate the incoming packets. When the network traffic becomes heavy, IDWBA always outperform EDBA and DWBA in average delay, maximum delay, network throughput and packet loss due to fully flexible integrated dynamic wavelength assignment and bandwidth allocation scheme.

V CONCLUSION In this paper, we present an improved integrated dynamic

wavelength assignment and bandwidth allocation (IDWBA) algorithm for WDM-PON. IDWBA fully exploits the statistical multiplexing opportunities among different ONUs. Simulation results have showed that IDWBA increases the network

efficiency and improve the network performance which comparing with EDBA in [1] and DWBA in [6]. Since the tunable transceiver is expensive, in the future study, we will investigate a hybrid WDM-PON architecture where only a limited number of ONUs employ tunable lasers. We will look for the tradeoff between cost and network performance.

REFERENCES [1] Xin Ye, A. Sana, C.Assi, M.Ali,” Enhanced Dynamic Bandwidth

Allocation in WDM-PON”, SPIE Optics East 2007.. [2] K.H.Kwong, D. Haarle, and I. Andonovic, “Dynamic Bandwidth

Allocation Algorithm for Differentiated Services over WDM_PONs” IEEE International Conference on Communications Systems (ICCS) pp116-120,September 2004, Singapore.

[3] G. Kramer, G. Pesavento “Ethernet Passive Optical Network (EPON): Building a Next-Generation Optical Access Network”, IEEE Communication Magazine. Vol 40, pp.66-73, 2002.

[4] Chadi M. Assi, Yinghua Ye, Sudhir Dixit, and Mohamed A. Ali, “Dynamic bandwidth allocation for Quality-of-Service over Ethernet PONs”, IEEE JSAC, Vol 21, pp. 1467-1477, 2003.

[5] A. R. Dhaini, C. M. Assi, M. Maier, and A. Shami, “Dynamic Wavelength and Bandwidth Allocation in Hybrid TDM/WDM EPON Networks”, Journal of Lightwave Technology.

[6] Michael P. McGarry etc., “Just-in-Time Online Scheduling for WDM EPONs”, ICC2007, June 2007.

[7] Glen Kramer, “Synthetic traffic generation”, C++ source code version, http://wwwcsif.cs.ucdavis.edu/ kramer/research.html.

[8] W. Leland, M. Taqqu, W.Willingler, and D.Wilson. “On the Self –Similar Nature of Ethernet Traffic (Extended Version)”, IEEE/ACM Transactions on Networking, pp.1-15 Feb 1994.

[9] F.An, K.S.Kim, D.Gutierrez, S. Yam, E. Hu, K.Shrikhandle and L.G.Kazovsky, “SUCCESS: A Next-Generation Hybrid WDM/TDM Optical Access Network Architecture.” Journal of Lightwave Technology, Vol 22, pp. 2557-2569, 2004.

[10] K.S.Kim, D.Gutierrez, F.An, L.G.Kazavsky, “Design and performance Analysis of Scheduling Algorithms for WDM-PON under SUCCESS_HPON Architecture”, Journal of Lightwave Technology, Vol 23, pp.3716-3731, 2005.

[11] Amitabha Banerjee,,etc., “Wavelength-division-multiplexed passive optical network (WDM-PON) technologies for broadband access: a review [Invited]”, J. of Optical Networking, Vol 4, pp.737-758, 2005.

[12] M .McGarry, M. Maier, and M. Reisslein,” Ethernet PONs: A Survey of Dynamic Bandwidth Allocation (DBA) algorithms”, IEEE Optical Communications, August 2004.

[13] IEEE 802.3ah, Ethernet in the First Mile Task Force, http://www.ieee802.org/3/efm/index.html