Int. J. Communications, Network and System Sciences, 2009, 7, 652-656
doi:10.4236/ijcns.2009.27074 Published Online October 2009 (http://www.SciRP.org/journal/ijcns/).
Optical Network Traffic Control Algorithm under Variable
Loop Delay: A Simulation Approach
Manoj Kr DUTTA, Vinod Kumar CHAUBEY
Electrical and Electronics Engineering Department, Birla Institute of Technology & Science,
Pilani, Rajasthan, India
Received May 9, 2009; revised July 16, 2009; accepted August 22, 2009
ABSTRACT
In this paper we present a concept of new architectural model consisting of multiple loop delay to increase
the throughput. The simulated behavior of an optical node has been realized by using an n x m optical switch
and recirculating optical delay lines. This investigation infers the scaling behaviors of the proposed architec-
ture to maintain efficient use of the buffer under Poisson traffic loading. The analysis also reports the traffic
handling capacity for the given complexity of the node architectural design.
Keywords: Fiber Delay Line, Recirculation, Traffic, Throughput
1. Introduction
ALL-OPTICAL communication has been proposed as a
promising candidate for providing high-speed network-
ing [1–4] owing to huge bandwidth of optical channels.
Wide bandwidth available in low attenuation window in
the optical fiber can be divided into a number of inde-
pendent wavelength channels as per network standard
and specification leading to SONET, SDH or wavelength
division-multiplexing (WDM) based all optical network
system [5–7]. Evidently to support such all optical con-
trol in these networks several technologies have been
proposed for efficient networking viz., broadcast and
select, wavelength routing, optical packet switching
(OPS), and optical burst switching [8–10]. In an OPS
network, optical interconnect (or optical switch) for-
wards the packets to their destinations involving pro-
grammable switch fabric and control circuitry and
thereby support in packet contention resolution. However
in a WDM interconnect, output contention arises when
more than one packet on the same wavelength are des-
tined to the same output fiber at the same time. To re-
solve this contention one will have to either temporarily
store some of the packets in a buffer, or to convert
wavelengths to some available wavelengths by wave-
length converters [11–13]. Obviously optical buffers,
wavelength converters add the complexity by enhancing
the installation and recurring cost of the system. How-
ever allocating some dedicated buffers for each output
fiber which can share a common optical delay line (ODL)
buffer pool [5–6] will essentially reduce the cost and
complexity as well. In a WDM a packet that cannot be
directly sent to the output fiber is sent back to one of the
delay lines for recirculation and after being delayed by
some specific time, that packet will come out of the de-
lay line to compete for throughput with the newly arriv-
ing packets. In case of unsuccessful throughput it gets
back into the delay line for the next round trip with addi-
tional delays.
In the proposed model a node has been considered
with more input channels than output channels and the
maximum capacity of this node is decided by the avail-
able output channel. It is assumed that arriving packets
are destined to their respective destinations based on
First Come First Serve (FCFS) scheduling policy. In this
way we can avoid the continuous recirculation of some
packet in the delay line. Packets that arrive in the mean-
time are also sent to delay line. The node includes finite
capacity buffer and multiple delay lines arranged in syn-
chronized mode.
2. Node Architecture Design and Modeling
The packet switching has its own (unique) issues in op-
tical networks. In an optical packet-switched network,
contention occurs due to unavailability of free output
wavelength. In electrical packet-switched networks, con-
tention is resolved with the store-and-forward technique,
which requires the packets losing the contention to be
stored in a memory bank and to be sent out at a later time

M. K. DUTTA ET AL. 653
Figure 1. Recirculating delay line optical.
when the desired output port becomes available. This is
possible because of the availability of electronic random-
access memory (RAM). There is no equivalent optical
RAM technology; therefore, the optical packet switches
need to adopt different approaches for contention resolu-
tion. Meanwhile, WDM networks provide one new addi-
tional dimension namely wavelength, for contention
resolution. There have been studies in literature for util-
izing the three dimensions of contention-resolution sche-
mes: wavelength, time, and space.
In this paper we explore the contention resolution,
based on time and propose a new scheduling algorithm
for prioritizing the packets within the node. The optical
buffers basically delay the incoming signal by making it
to travel a small distance, so as to provide some time to
the processor for serving them in case the service is not
available initially. Now this delay can be provided in
fixed quanta’s only. This unique feature of optical buff-
ers (unlike their electronic counterpart which ‘store’ a
packet) makes it necessary to have a minimum fixed de-
lay once the packet has entered into the fiber delay line
(FDL). Traditionally the buffer is implemented such that
once the packet has entered into the FDL it suffers the
delay and comes out after that time. The packet might be
served had necessary arrangements been made or other-
wise dropped. This architecture provides a single chance
to server to serve it thus resulting in high packet loss.
Ideally the packet should be available at all times at out-
put after having entered the FDL (like equivalent elec-
tronic memory) so that it can be served whenever the
resources are available.
Our new buffer architecture attempts to realize this
objective by giving delays in steps of small granularity D
(µSec) which allows the packets to be processed if the
resource at output is available otherwise reflected back to
the FDL for multiple reflections as per the control algo-
rithm.
It is already assumed that the number of output chan-
nels (m) is less than the number of input channels (n) and
therefore the queuing system has a fair chance of packet
contention. The buffer works with a first-come first-
served (FCFS) scheduling policy and is implemented by
means of FDL’s with reflection.
In the proposed buffer architecture, when the packet
arrives, it will be sent to the output node but if all output
nodes are busy then it will be placed back in the first
loop of the FDL having a delay of D1, after completion of
the delay the packet competes for output port, failing this
it will again be reflected back into the second delay of D2
and so on. The maximum delays that can be provided by
using FDL’s are assumed to have different values of de-
lay such as a constant, arithmetic or a geometric progres-
sive delay.
The flow chart for the packet servicing algorithm in-
volving multiple delays in the proposed node architecture
is presented in Figure 2. Obviously as a packet arrives at
the node and the server is idle it is served immediately
but these are queued if the server is busy. Usually the
delays are kept finite by means of the FDL’s, due to the
limited time resolution related to the granularity and the
new packet is going to be delayed at least by an amount
of D for one loop circulation. Also the packet can’t be
made to reflect infinite number of times due to loss of
energy at each reflection and hence is limited by ac-
cepted SNR.
Figure 2. Flow chart for node performance analysis.

M. K. DUTTA ET AL. 654
Thus the packet is dropped after K reflections, which
is modeled in terms of acceptable quality q and reflection
loss α as a function of log (q-α). Considering the evolu-
tion of buffer contents over time, we can identify three
important variables viz. order of bursts arrival, the packet
inter arrival time (IAT) having Poisson distributed (Tk)
and the intermittent time between the kth arrival and the
next one.
This system is modeled for a random input, having an
exponential service with N servers, an infinite number of
prospective customers and a maximum queue length of L.
System probability for jth call is expressed in term of
packet arrival rate λ and packet length tm as:
0
()() ,0
!
j
jA
PAPAforj N
j

(1)
0
()() !
j
jjN
A
PAPAforNjN L
NN
 (2)
where P0 (A) is used to make the sum of P’s to unity as-
suming A as λtm . Further P0(A) can be written as:
1
0
01
() !!
jN j NL
j
jj
AA A
PA jN N












A
A
(3 )
In the proposed algorithm an incoming packet will be
blocked if all the servers are busy & queue is full. How-
ever the packet will be delayed if the servers are busy but
queue is not completely full. The probability that (N+L)
incoming packet is delayed can be written as
1
1()
NL
j
jN
PP


 (4)
Further a packet will be serviced immediately if there
are less than N packets in the system and the probability
of immediate service of packet is expressed as
1
0
()
N
IS j
j
PP


 (5)
The waiting time distribution for the incoming traffic
can be expressed using the standard equation [14] as
1
0
() !
m
j
Ljx
NjNtt
PPA xedx
j




 (6 )
These equations have been used in throughput simula-
tion in the MATLAB environment under the appropriate
node and traffic assumptions.
3. Simulation and Results
Traffic throughput of the offered traffic that gets proc-
essed through the node has been estimated under various
node design parameter constraints. This traffic has been
evaluated using Equations (2-6) for the proposed node
operated under traffic resolution algorithm. Figure 3
presents the carried traffic corresponding to incoming
offered traffic with the variation of number of delay lines
(N) involved. The simulated curve shows a linear de-
pendence of the carried traffic on the offered traffic only
upto a specific input load but beyond that it deteriorates
owing to the rise in the blocking probability. Moreover
increased incoming traffic results a crowded node forc-
ing to reject the excess traffic. This qualitative behavior
is also supported by the simulation curve showing a re-
jection beyond a critical offered traffic viz. for N=6 be-
yond 2 Erlang.
The Figure 3 reveals better throughput is available if
the delay is varied for different passes instead of keeping
it constant for all passes. Basically if the delay is in-
creased in every recirculation by a certain amount then it
requires less number of recirculation comparing the fixed
delay case to achieve a same particular amount of delay.
As we have already discussed that recirculation of opti-
cal signal in the fiber delay line causes attenuation of
signal power, insertion of different noises which ulti-
mately affects the throughput of the network so it is bet-
ter to have less number of recirculation to achieve better
output. It may also be inferred from Figure 3 that the
region of offered traffic for which the throughput is very
high or the length of the high throughput region is
greater in case of fixed delay network comparing to the
variable delay system.
The Figure 4 depicts that, as the holding time increases
the throughput decreases for all types of delay systems.
Holding time corresponds to the processing speed and it
increases for slower processing speed. Delay line will
provide an amount of delay to the signals which are in
the queue of getting served. Fast servicing will provide
lesser processing time which in turn reduces the number
Figure 3. Plot of carried traffic vs offered traffic for differ-
ent values of N.

M. K. DUTTA ET AL. 655
of recirculation in the delay loop. From Figure 4, it is
also seen that the spreading of the linear region is greater
in case of fixed delay loop comparing to the variable
delay loop.
Figure 5 shows the variation of throughput for differ-
ent numbers of recirculation loop. It is observed that as
the number of recirculation loop increases the amount of
carried traffic increases for both types of delay system i.e,
for fixed delay as well as for increasing delay system.
This is because the lesser loop increases the holding
probability of the packet in the delay line. This in turn
reduces the packet dropping probability. Throughput im-
provement is significant increasing in case of increasing
delay system; this is obvious because the amount of de-
lay achieved during recirculation increases gradually. It
may be noted that the amount of region with maximum
throughput is available in case of fixed delay system.
The analysis has been made more general by including
a geometrical progressing delay loop in addition to arith-
metic and constant delay lines. The corresponding th-
roughputs have been presented in Figure 6 The fig re-
veals that the throughput improves as the delay increases
which is expected but the increment of throughput will
sustain up to a certain value of incoming traffic, after
which the output decreases, means the packets which are
coming further are being completely rejected.
From Figure 6 we can also infer that the insertion of
more delay in the loop will increase the cost and com-
plexity of the system as well and it is tolerable up to a
certain limit. Thus this investigation will help the net-
work designer to take a decision on the possible maxi-
mum throughput and the complexity of node architecture
design.
4. Conclusions
The problem of wavelength contention in packet switched
Figure4. Carried traffic vs offered traffic for different val-
ues of holding time.
Figure 5. Plot of carried traffic vs offered traffic for differ-
ent values of k.
Figure 6. Plot of carried traffic vs offered traffic for differ-
ent types of delay.
WDM networks using recirculation optical delay lines
has been developed. The proposal is based on putting
priority to the packets which have suffered maximum
delay on the link in processing by using a proposed con-
tention resolution algorithm. The performance of the
algorithm has been evaluated using MATLAB simula-
tion to establish a better contention resolution using a
varied delay lines at the nodes. The analysis presented
here is useful to predict the traffic throughput range of a
processing node with given number of FDL’s and rele-
vant design parameters.
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M. K. DUTTA ET AL. 656
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