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Next-generation SONET/SDH, RPR, and OBS: which is the

best choice for the future Metro Area Networks?1

Liu Xin*, Wang Hongxiang, Ji Yuefeng

Key Laboratory of Optical Communication and Lightwave Technologies, Ministry of Education, P. R. China,

Beijing University of Posts and Telecommunications, Beijing, China (100876)

[email protected]

AbstractAs Internet traffic has been explosively grown in Metropolitan Area Network (MAN), traditional

SONET/SDH networks needed to be reengineered to handle data traffic in a more efficient way. Recently,

several new technologies have been proposed as a solution for that problem, such as next-generation

SONET/SDH, RPR and OBS. However, which is the best choice? In this paper, we compare the performance

of these technologies, such as the number of required wavelengths, bandwidth utilization, distribution of

delay variation and packet loss rate, network throughput and so on, in a two-fiber ring network model which

is the most familiar network architecture in MAN. The simulation results show that taking one with another,

OBS is the best solution for the future MAN, though its packet loss rate is a little higher than the other two

technologies.

Keywords:Metro Area Networks, Next-Generation SDH/SONET, RPR, OBS

1. Introduction

In existence for over a decade now, Metropolitan area networks, also referred to as MANs, have

traditionally been designed for voice transmission based on time division multiplexing (TDM) technology.

At that time, voice traffic was significantly more important than data traffic. As a result, synchronous optical

network/synchronous digital hierarchy (SONET/SDH) became the dominant standard on these networks.

Those technologies have been able to meet the initial requirements of MANs quite adequately and today,

most of them are based on SONET/SDH technology.With the explosion in the demand for bandwidth for data transmission, it became quite clear that

SONET/SDH networks needed to be reengineered to handle data traffic in a more efficient way. This led to

the emergence of next-generation SONET/SDH [12] and also the increasing number of networks based on

Dense Wavelength Division Multiplexing (DWDM), such as Resilient Packet Ring (RPR) [3], Optical Burst

Switching (OBS) [4] and so on.

However, as there are so many solutions for MAN, which is the best choice? All the researchers of these

technologies have implied that their solution is the one that the most suitable for the data transmission,

especially for the non-uniform traffic demands. How can we make the choice when there is no comparison

among them?

In this paper, we use a two-fiber ring network model which is the most familiar architecture in MAN to

compare the data transmission ability of these technologies. Both analytical and numerical modeling

techniques were applied to quantify and compare the network performance for all technologies in terms of

achievable throughput, delay and delay variation, and the number of required wavelengths and to investigate

the impact of traffic demands.

1Support by National Science Fund for Distinguished Young Scholars (60325104), by National Natural ScienceFoundation (60572021), by National 863 Project (2006AA01Z238), by PCSIRT Project of MOE (IRT0609), byInternational Cooperation Project of MOST (2006DFA11040), by 111 Project (B07005), and by SRFDP of MOE

(No.20040013001), P. R. China.

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This paper is organized as follows. In section 2, we defined the max background traffic model (which is

calculated by CBR flow) and then according to that, we have presented the detailed design of these three

technologies network, including the transmission direction of the ring, the number of wavelengths it needs,

the processing delay for each node and other parameters for them. Then, the simulation results and the

detailed analyses have been provided in Section 3 and the conclusions have been presented at the end of this

paper.

2. Description of Network Model for Comparison

As the ring is the familiar topology in MAN, we have used a two-fiber ring network as the topology model

in our research, which has been shown in Fig 1.

Fig 1 the network model for simulation

There are four nodes (we call them RN) in the ring and the two fibers between each two adjacent RNs can

make the ring either unidirectional or bidirectional. The number of wavelengths in the fibers is undetermined,

and it will be decided by the requirement of each technology for the same traffic model. The data transfer rate

of each wavelength is defined beforehand which is 2.5 Gbit/s. The distance from each RN to its adjacent node

is same as 50 km. That is to say, according to the transmission speed of the optical signals in fibers which isonly 5 s/km, the transmission delay from one RN to its adjacent node will be 250 s. In addition, there are 3

independent Packet Generator and Receivers (we call them PGR) connected to each RN which can generate

the various background traffics, such as Constant Bit Rate (CBR) flow, Dynamic Bit Rate (DBR) flow and

Self-similar flow to the other three RNs as is illuminated in Fig 1.

Network design is based on the requirement of the background traffic. While, as the self-similar traffic

could not be measured accurately, we design the network according to the max average traffic of CBR flow.

The detailed definition is: the max average bit rate of the traffic generated by each PGR could be 2.5 Gbit/s.

Therefore, the max average input bit rate of one RN is 7.5 Gbit/s. and the one of the whole network is 30

Gbit/s. In summary, all the parameters mentioned above have been displayed in Table 1.

Table 1 Parameters of network modelThe number of RNs in the ring 4

The number of fibers in the ring 2

The transmission speed of wavelengths2.5

Gbit s

The distance between two adjacent RNs and the transmission delay in fibers 50 km / 250us

The number of PGRs for each RN 1

The max average traffic from one PGR to another2.5

Gbit s

The max average input traffic of one RN7.5

Gbit s

The max average input traffic of the whole network30

Gbit s

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In addition, we should combine the detailed design of each network model with these three technologies

respective characteristics, including the requirements and admeasurements of wavelengths, the processing

delay for each technology, the max or min burst length and the max assembly time for OBS network and so

on. All of them have been discussed in detailed respectively at the following part.

2.1 NG-SONET/SDHNext-generation SONET/SDH has made a great progress on data transfer compared with the traditional

SONET/SDH. However, there is still no difference on the schemes of wavelength admeasurements between

them. As there are two protection-switched modes (1+1 protection mode and 1:1 protection mode) for Private

protection in SONET/SDH network, we have designed two network models to simulate these two different

modes. The distribution of wavelengths has been shown in Fig 2.

Fig 2 the distribution of time-slot in NG-SONET/SDH network

As is shown in Fig 2, for the 1+1 protection mode, to meet the requirements of the traffic from the upperlayer, there should be a private wavelength between each two nodes. While, on account of the scheme of

bidirectional transmitting and selective receiving, both ringlets would carry the traffic synchronously.

Therefore, 12 wavelengths must be presented at each ringlet. On the contrary, for the 1:1 protection mode, as

the wavelengths could be shared as is shown in Fig 2, we will only use 6 wavelengths to carry these traffics

on one ringlet.

When the packets arrive at a RN, they would queue up there waiting to be transmitted by SONET/SDH

frames, which are transmitted by the RN periodically every other 125s. Since the frames would go through

O/E and E/O conversions and add and drop the packets, the whole delay must be longer than 125s which is

only caused by E/O conversation. As the reading and writing processing delay is based on the clock of the

equipment, and based on the investigation of the processing ability of the exiting technologies, the extra

125s delay for processing should be appropriate.

2.2 RPRFor RPR network, to match the requirements we defined before, only two wavelengths in each fiber have

already been enough. One possible distribution of bandwidth has been shown in Fig 3.

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Fig 3 one possible distribution of bandwidth in the RPR network

As Fig 3 shows, spatial reuse makes RPR network more efficient, which only use total four wavelengths to

carry the same traffic. As the node feeds the ring with the client traffic and the traffic that it has to forward

from upstream nodes to downstream nodes, two approaches are presented to schedule these different traffic

streams: a store-and-forward approach and a cut-through approach [3]. In our comparison, both

approaches have been considered, and the detailed analyses would be provided at the following section.

In addition, one issue should be illustrated is the processing delay of a RPR node. Since RPR is known as a

Layer 2 protocol, and in our comparison, we build the RPR network on the SONET/SDH ring, that is, the

delay at the RN will include not only the time of O/E/O conversions which will take 125s, but also the timeof the processing by Lay 2. Therefore, the extra 250s for the processing delay should be appropriate.

2.3 OBSFor OBS ring network, some new protocols have already been presented, such as Token Access protocol

[5], Dest-Resv-Free protocol [6], advanced Token Access protocol [7] and so on. For all these protocols, the

one which is based on token seems to be able to get better performances [5]. This is because that it can avoid

not only the problem of channel blocking, but also the one of receiver blocking. Therefore, two mode of OBS

ring based on token have been considered in our comparison, one is Fixed Transmitter and Tunable Receiver

(FTTR) mode based on the ODD (Only Destination Delay) [5] protocol and the other is Tunable Transmitter

and Fixed Receiver (TTFR) mode based on the OSD (Only Source Delay) protocol.

For both FTTR and TTFR models, if we want to transmit the traffic as we defined before, three transmittersand three receivers which have the data transmitting or receiving rate of 2.5 should be designed on each RN.

Therefore, as one of the transmitter and the receiver would be fixed to the local ring node in these two

protocols, at least 13 wavelengths should be designed on the ring, one for control channel which would

transfer tokens and control packets (also refers to the burst headers), the others for the data transfer. Hence, as

the network model that we designed has two fibers and the token ring is unidirectional, we design each fiber

with 7 wavelengths including one control channel and six data channel. Moreover, based on that design, we

can use the control channel in one fiber transfer tokens, and the one in the other fiber transfer the headers of

each burst.

In addition, we have designed another bidirectional OBS ring based on the scheme of wavelength grouping

[8], and we have named it WG-OBS ring. The detailed structure of the WG-OBS node has been shown in Fig

4.

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Fig 4 the structure of WG-OBS ring node

In Fig 4, we can see that the ring totally needs 6 wavelengths, two for control channel of each direction, and

four for data channels. When the packets from PRGs arrive at the RN, it will be queue up there until the max

assembly time up or the max burst length reached. The routing scheme adopts OSPF protocol, which will first

choose the ringlet for transmission. Then, for the wavelength reservation, according to the wavelength

grouping, the RN will try to reserve the corresponding wavelength at first, and reserve the other one if the

first try is failed. Moreover, if neither of the wavelengths is available, it will delay the transmission of the

burst and only use the corresponding wavelength until it is available.

Table 2 the predefined parameters of the OBS network mode

Offset timeMin burst

length (bits)

Max burst

length (bits)

Max assembly

time (s)

Token OBS FTTR 10s 512 U -

Token OBS TTFR 10s 512 U -

WG-OBS n*10s 512 500000 0.0005

For all the modes of OBS ring network, there are several parameters must be discussed beforehand, such as

the offset time, the max and min burst size, the max assembly time and so on. All of them have been shown in

Table 2.

In Table 2, as the network modes of FTTR and TTFR dont need wavelength conversations, the offset time

of them are only used to the tuning delay of the transmitter or receiver. Therefore, 10s would be enough

according to [9]. The definition of the max burst length and the max assembly time for WG-OBS are based on

a great deal of simulation with the traffic we defined before, and this parameters could make the packet loss

rate of this network so low that it is only 0.2% even at the condition of 90% load with the dynamic traffic

(which has been defined at the following section) in the whole network. And the max burst length for token

OBS is according to the discussion in [5].

In summary, all the parameters of these 7 network modes we defined before have been shown in Table 3.

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Table 3 summary of the predefined parameters for each network mode

Network modeNumber of data

wavelengthsDirection Processing delay

Queue

Buffer

size (MB)

1+1 mode 24 bidirectional n*125s 64NG-

SONET/SDH 1:1 mode 12 bidirectional n*125s 64

CT 4 bidirectional n*250s 64RPR

SF 4 bidirectional n*250s 64

FTTR 12 unidirectional 10s 64

TTFR 12 unidirectional 10s 64OBS

WG 4 bidirectional n*10s 64

3. Simulation results and Analyses

In this section, we will use two different traffics to simulate these seven network models we designed

above. The parameters of the simulation we defined have been explained in detailed as following. Distribution of Edge-to-Edge delay: this parameter is including not only the transmission delay

from the source RN to the destination, but also its variation.

Bandwidth utilization: this parameter means that when there is some traffic in the ring, what percent

of the bandwidth have been used.

Distribution of Packet loss rate: this parameter implies the variation of the packet loss rate. And for

the different network models, this parameter is caused by different reasons. We will analyze them in

detailed at the following part.

Network throughput: for the same traffic, the average throughout implies the transmission ability of

each network model.

The two different traffics we defined include the dynamic traffic and the self-similar traffic. The dynamic

traffic is defined as the traffic with a fixed uniform-distributed packet length from 512bits to 12144bits and a

variably exponential-distributed packet inter-arrival time with mean from 2.61s to 25.5s. The simulation

results of the bandwidth utilization and the average Edge-to-Edge delay from RN_A to RN_C of each

network model have been shown in Fig 5 and Fig 6 respectively. The self-similar traffic is characterized as a

data rate with a heavy tailed distribution and long rang dependence. Here we consider the self-similar traffic

with a fixed uniform-distributed packet length from 512bits to 12144bits and a variably pareto-distributed

packet inter-arrival time with different locations and shapes. The variation of the input rate with the

self-similar traffics at each node in our comparison has been shown in Fig 7. And the distributions of the

Edge-to-Edge delay from RN_A to RN_C and the packet loss rate for each network model with the

self-similar traffics have been shown in Fig 8 and Fig 9 respectively. And the other simulation results have

been shown in Table 4.

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Fig 5 the bandwidth utilization for the dynamic traffic through each network model

Fig 6 the average delay for the dynamic traffic through each network models

Fig 7 the distribution of the input rate (self-similar traffic)

Fig 8 the distribution of the ETE delay from RN_A to RN_C with self-similar traffic through each network model

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Fig 9 the distribution of packet loss rate with self-similar traffic through each network model

From Fig 5, we can see that with the same traffic, WG-OBS network can get the max bandwidth utilization

and some technologies like NG-SONET/SDH and token-OBS with FTTR and TTFR could not match 50

percent of bandwidth utilization even when the traffic load is 100 percent. For NG-SONET/SDH, as there aresome wavelengths which would never be used in both 1+1 and 1:1 protection mode, which has been shown in

Fig 2, it makes the NG-SONET/SDH not only need more wavelengths to transfer the same traffics, but also

reduce its own bandwidth efficiency. Another issue should be mentioned is that the large overhead which is

more than 10368bits in each frame of NG-SONET/SDH network makes the bandwidth utilization even lower.

Touching the token OBS, there are two factors that make its bandwidth utilization so low. One is there would

never be any traffic on the one-fourth of a wavelength in the ring, since there is no traffic that a RN sends to

itself. The other is for FTTR mode, as the token could not be released ahead of schedule as the TTFR mode,

when the token is sending from one RN to another, none of RNs on the ring could send any data. Therefore,

with the transmission time of the token increasing, the bandwidth utilization of FTTR mode would decrease.

Table 4 the simulation results of these 7 network models with a self-similar trafficNG-SONET/SDH RPR OBS

Network

mode1+1

mode1:1 mode CT SF FTTR TTFR WG-OBS

Average ETE

delay(s)0.03857 0.03857 0.00187 0.00246 0.00479 0.00465 0.00124

Average

throughput (%)99.04 99.04 100 100 100 100 96.86

Bandwidth

utilization (%)35.87 69.67 79.46 79.49 36.74 36.59 76.19

Average packetloss ratio (%)

2.331 2.331 0 0 0 0 4.07

In Fig 6, we can see that the WG-OBS network model has the minimal ETE delay among all of them

whatever percent of the network load is. For NG-SONET/SDH, as it is designed to meet the initial

requirements of TDM services, the transmission delay is invariable no matter what percent of the network

load is. While, for OBS network model, the transmission delay is changed with the variety of the traffic load

of the network. In detail, as FTTR and TTFR of OBS network model can transfer the data only when they

held the TOKEN, the transmission delay is much larger then the other technologies when there is a high load

in the network. That is because the time of the TOKEN being held by each RN become longer. Referring to

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the WG-OBS, the data would queue up at the source RN until the max assembly time or the max burst length

is reached. Therefore, when the traffic load goes higher, the condition of the max burst size would be easier to

reach, and the queuing delay would become shorter. That is, the transmission delay would go smaller as the

network load goes higher. One issue must be mentioned is that when the burst is created caused by the

assembly time up, the difference of transmission delay is mainly due to the sending time of the burst. That is,

if the burst size is small, the sending and receiving time would be short. Hence, when the burst is created

caused by the assembly time up, the edge-to-edge delay would be shorter while the burst size goes smaller.

As is shown in Fig 6, the average Edge-to-Edge delay when the network load is 20 percents is lower than that

when the network load is 40 percents. For RPR network model, we have defined both cut-through and

store-forward mode based on SONET/SDH technology. Therefore, the average Edge-to-Edge delay of RPR

network is the same as that of NG-SONET/SDH network. The only difference between them is that RPR

need more 125s for processing by Layer 2 at each node.

Fig 8 shows the distribution of the Edge-to-Edge delay from RN_A to RN_C in each network model with

self-similar traffic. From it, we can see that in the NG-SONET/SDH network models, the Edge-to-Edge delayof the most packets is nearly 60ms. That is due to the data congestion at the source RN, which makes each

packet has a long queuing delay. However, although there are some packets that have been delayed more than

10ms in token-OBS network models, and in OBS-FTTR network some packets have been delayed even more

than 20ms, the most packets still can arrival at the destination RN in 10ms. That makes the average

Edge-to-Edge delay of these two network models much shorter than that of NG-SONET/SDH network

models. The better performance could be gotten by the other three network models: RPR-CT, RPR-SF and

WG-OBS network models. From Fig 8, we can see that the average Edge-to-Edge delay of the WG-OBS

network model is the shortest among these three networks because the most packets have been delayed less

than 1ms.

The distributions of packet loss rate in each network have been shown in Fig 9. From it, we can see that

except four networks which are based on RPR and token-OBS, all the other network have some packet loss.

For NG-SONET/SDH networks, the packet loss is mainly caused by the buffer overflowing. While, for

WG-OBS network, all the packet loss is caused by the resource competitions. Although we have taken some

measures to reduce the probability of that problem, the packet loss still has occurred. Furthermore, as the

packet loss is based on a burst which consists of many packets from the PRGs, the average packet loss rate is

much higher than the other networks. That means the channel blocking is more influential compared with the

buffer overflowing. However, as the OBS technology is just under researching, the problem of channel

blocking may be solved in future, as some new schemes have already been provided, such as [10], [11] and so

on.

4. Conclusions

In this paper, we have designed 7 network models which are based on three different technologies:

NG-SONET/SDH, RPR and OBS. With the different traffics, we have simulated these network models and

presented the results about the ETE delay, packet loss rate, bandwidth utilization and the network throughput

and other performance. On all accounts, from the point of view of the data transfer performance, with the

simulation results which have been shown above, we can see that WG-OBS ring network is the best solution

for data traffic in the future MAN, though its has a little higher packet loss rate than the other network models.

It is not only because that it has shorter ETE delay and higher bandwidth utilization, but also because that it

has no electronic bottleneck which the RPR network has.

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