Performance comparison of dynamic elastic optical networks with optical regeneration
Research and Development on Information and Communication Technology
Performance Comparison of Dynamic Elastic
Optical Networks with Optical Regeneration
Le Hai Chau, Dang Hoai Bac
Posts and Telecommunications Institute of Technology, Hanoi, Vietnam
Correspondence: Le Hai Chau, [email protected]
Communication: received 23/04/2019, revised: 25/07/2019, accepted: 26/07/2019
Online early access: 26/07/2019, Digital Object Identifier: 10.32913/mic-ict-research.v2019.n1.853
The Area Editor coordinating the review of this article and deciding to accept it was: Dr. Nguyen Tan Hung
Abstract: We have investigated optical regeneration issues
and application in elastic optical networks that are capable of
providing dynamically optical paths with flexible bandwidths.
We have analyzed the impact of optical regeneration in elastic
optical networks and clarified various usage scenarios. We
have then evaluated and compared the performance, in terms
of the overall blocking probability and the total accommo-
dated traffic volume, of three possible network scenarios with
regeneration capability including (i) no regeneration, (ii) 3R
regeneration, and (iii) 4R regeneration for practical network
topologies. Numerical simulation proved that deployment
of optical regeneration devices can exploit elastic optical
networking to enhance the network performance for provi-
sioning dynamically bandwidth-flexible lightpath services. It
is also demonstrated that using re-modulation function while
regenerating optical signals (4R regeneration) can further
improve the network performance. However, due to the
high cost of optical regeneration devices, especially all-optical
ones, and more functional regenerators, the trade-off between
the performance enhancement and the necessary number of
regenerating devices needs to be carefully considered.
spectral utilization, and high cost [5]. Present researches
on optical transmission and networking technologies are
oriented forward more efficient, flexible, and scalable net-
work solutions. Recently, elastic optical network (EON)
utilizing a flexible frequency grid has been proposed as
a promising candidate for future ultra-high capacity optical
networks [6, 7]. Elastic optical networking technology helps
greatly improve the spectral efficiency and flexibility of the
network by eliminating stranded spectrum between chan-
nels, supporting both sub-channel and super-channel traffic,
and therefore allowing flexible bandwidth connections of
multiple data rates and modulation formats [6–8]. However,
EON is currently facing challenges owing to the lack of
architectures and technologies to efficiently support bursty
traffic on flexible spectrum.
Elastic optical networks are able to allocate spectrum
resources flexibly for handling not only legacy low-bitrate
services but also new super-channel services [6]. Although
elastic optical networks are also capable of provisioning
dynamic bandwidth-flexible and spectrum-efficient end-to-
end optical paths while enable an economical scalability
of networks adapting to the growing trend and the het-
erogeneity of bandwidth requirements for Telcos/Internet
service providers [7, 8], more sophisticated network design
and provision control strategies are required for realizing
efficient and robust network operations [7]. As a result,
routing and wavelength assignment (RWA) problem of
elastic optical networks becomes more complicated and is
known as routing and spectrum assignment problem which
includes three sub-problems that are routing, modulation
format assignment and spectrum allocation [7–9].
Keywords: Optical regenerator, routing, modulation format
and spectrum assignment, network control algorithm, elastic op-
tical network.
I. INTRODUCTION
Internet traffic is growing at incredible rates, driven by
high-performance applications including video on demand,
and cloud and grid computing [1, 2] which demand even
more ubiquity, mobility, and heterogeneous bandwidths [3,
4], in recent decades. This traffic growth places an im-
portance of extremely large data capacity yet flexible and
efficient optical network technologies to support broadband
services up to Terabit/s in the near future. To scale to Ter-
abit/s, optical networks based on current WDM technology
using fixed ITU-T frequency grid will face serious problems
due to the stranded bandwidth provisioning, inefficient
Moreover, optical signals suffer from the physical impair-
ments, such as dispersion and noise, etc. which are being
accumulated along the optical paths and consequently,
cause a limitation on the optical transmission reach [10–12].
Particularly in large optical networks in which optical paths
43
Research and Development on Information and Communication Technology
may travel ultra-long distances, the optical impairment
impact becomes very critical. Hence, optical regenerators
need to be deployed to clear the impairments and improve
the optical transmission reach [12, 13].
II. OPTICAL REGENERATION AND ITS APPLICATION
IN DYNAMIC ELASTIC OPTICAL NETWORKS
1. Performance Limits of Long-Haul Elastic Optical
Transmission Systems
Among the regenerator realization technologies, all-
optical regeneration can potentially offer significant cost
savings thanks to less power and size requirement, espe-
cially at high-data rates. Employing advanced all-optical
regeneration that applies multi-channel packaging can be
a disruptive technology to reduce the power and size
footprint.
Unlike traditional WDM networks, elastic optical net-
works can support one or several modulation formats.
Even more, distance-adaptive EONs are able to dynamically
assign the modulation format to each lightpath according
to its length [9]. Backbone elastic optical networks also
consist of long-haul transmission systems which are set
up by many spans. The performance of systems is mainly
limited by Optical Signal to Noise Ratio (OSNR) parameter.
Besides conventional optical regeneration techniques in-
cluding the signal re-amplifying along with re-shaping
(2R), and even/or re-timing (3R), a new elastic optical re-
generator, which is Virtualized Elastic Regenerator (VER),
has been lately proposed for elastic optical networks [14].
Different from traditional optical regenerators, the devel-
oped VER not only offers 3R regeneration functions (re-
amplifying, re-shaping and re-timing), but also naturally
supports re-modulating function (so called 4R) [15, 16]. In
addition, all 3R/4R optical regenerators can also provide
the spectrum conversion capability and therefore, the use
of optical regenerators can help to avoid spectrum collision
efficiently and significantly enhance spectrum resource uti-
lization in elastic optical networks.
Optical Signal to Noise Ratio is defined so as to include
the nonlinear interference noise as follows [17],
Ptx
PASE + PNLI
OSNR =
,
(1)
where Ptx is the average transmitted power per channel,
PASE is the amplified spontaneous emission (ASE) noise
power and PNLI is the nonlinear interference noise power
which accounts for the nonlinear effects.
In fact, PASE is calculated by [18],
PASE = SASE × B0,
(2)
where SASE is the ASE noise power spectral density (PSD),
B0 is the noise bandwidth. Depending on the amplifiers
applied (i.e. Erbium-Doped Fiber Amplifier (EDFA) or
distributed amplification like Raman), SASE is calculated
differently.
In this paper, we investigate optical regeneration issue
and its impact on dynamic elastic optical networks with
bandwidth flexible optical paths provisioning capability. We
also analyze the performance limits of elastic optical trans-
mission system. The network performance, in term of the
overall blocking probability and the accommodated traffic
volume, has been then evaluated and compared among three
typical optical regeneration deploying scenarios that are
If EDFA is used, SASE can be calculated as the following
formulation:
SASE = Ns hν(G − 1)NF,
(3)
where G is the EDFA gain that is equal to the span loss,
NF is the EDFA noise figure, Ns is the number of EDFAs
that is equal to the number of spans, h is Planck’s constant
and, ν is the optical carrier frequency of the signal being
amplified.
(i) no (without) regeneration,
(ii) 3R regeneration, and
(iii) 4R (3R plus Re-modulation) regeneration in two
practical network topologies.
On the other hand, PNLI is approximated as [19]
ꢂ
ꢃ
log π2|β |N2 R2Leff
ꢀ ꢁ
3
2
s
Numerical simulation is used to verified the efficiency
of using optical regenerators to exploit elastic optical net-
working and enhance the network performance. It is proved
that at least 29.8% (or 45.6%) more traffic volume for NSF
(USNET) network can be obtained. Re-modulation feature
of elastic regenerators can also further improve the network
performance. However, in order to build cost-effective,
bandwidth-abundant and flexible optical networks, the bal-
ance between the network performance and the required
regeneration resource cost should be carefully considered
due to costly optical regeneration devices.
ch
2
3
PNLI
=
Nsγ2Pt3x Leff
B0, (4)
π|β |R3
2
s
where Ptx is the transmitted power, Nch is the number of
channels, γ is the fiber nonlinear parameter, β is the fiber
dispersion parameter, Rs is the baudrate (Rs = Rb/log2(M)
with Rb bitrate and M is the modulation order) and Leff is
the effective length is given by
2
1 − e−αL
Leff
=
,
(5)
α
where L is the span length, α is the fiber loss parameter.
44
Vol. 2019, No. 1, September
TABLE I
SUMMARY OF TRANSMISSION PARAMETERS
Parameter
Baud rate
Value
12.5 Gbaud
12.5 GHz
1550 nm
80
Channel spacing
Centered wavelength
Number of channels
Modulation
M-QAM
0.2 dB/km
-21.7 ps2/km
1.4 W−1/km
5 dB
Fiber loss
GVD coefficient
Nonlinear coefficient
Amplifier noise figure
(a) Capacity vs. signal PSD
For distributed amplification, the SASE and PNLI are
calculated as follows:
SASE = 4αhνKT Ltot,
(6)
(7)
ꢂ
ꢃ
log π2|β |N2 R2Ltot
ꢀ ꢁ
3
2
s
ch
2
3
PNLI
=
γ2Pt3x Ltot
B0,
π|β |R3
2
s
where Ltot is the total fiber length, KT is a constant (KT w
1.13 for Raman amplification).
Furthermore, system capacity at Nyquist limit is given
in the following equation [17, 20]:
C
B
= log2(1 + SNR) (bits/s/Hz/pol),
(8)
(9)
2B0
2B0
SNR =
OSNR =
OSNR .
Rb
Rs log2 M
(b) Capacity vs. signal transmission power
And, the bit error rate (BER) for the systems with QPSK
and M-QAM (Quadrature Amplitude Modulation) can be
estimated respectively as in formulas (10) and (11) [20]:
Fig. 1. Information capacity limits per polarization of 16-QAM for
linear (dashed line) and nonlinear (solid line) transmission at different
transmission distances (L
= 80 km).
span
√
1
2
BER = erfc( SNR),
(10)
ꢀ
ꢁ
On the other hand, the dependence of the system per-
formance, in terms of capacity, BER and the maximum
optical reach at BER of 10−3, on the transmission distance
and the applied modulation format is shown in Figures 3
and 4 correspondingly. Applying higher-order modulation
formats which support higher capacity per spectrum slot
and consequently, require less number of spectrum slots. In
other words, employing higher-order modulation format can
attain higher spectrum efficiency but it suffers from shorter
optical transparent reach and as a result, more frequent re-
generation and/or more regeneration resources are required.
On the other hand, using lower-order modulation formats
may cause less spectrum slot capacity and thus, may
result in an increment in the required number of spectrum
slots. Hence, there exists a trade-off between the system
performance and the transmission length/modulation format
in elastic optical networks.
1
M
s
2 1 −
√
3 log2 M
2(M − 1)
BER =
erfc(
SNR).
(11)
log2 M
In order to estimate the performance limits of an elastic
optical transmission system, we assumed values of key
parameters as given in Table I. Figure 1 demonstrates the
capacity limits per polarization of 16-QAM modulation
format (M=16) with respect to the signal PSD and the
given transmitted power when the transmission distance is
various [20]. Here, the capacity is estimated without and
with optical fiber nonlinear effects (shown as dashed and
solid graphs). The results confirm that the system capacity
is limited due to the nonlinear effects of optical fibers.
Consequently, the system performance, in terms of BER,
is also strongly depended on the fiber distance and the
transmitted power (as shown in Figure 2).
45
Research and Development on Information and Communication Technology
(a) Capacity
Fig. 2. Performance limits of 16-QAM format for linear (dashed line)
and nonlinear (solid line) transmission.
2. Optical Regeneration Issue and Its Application
In general, optical regeneration can be deployed in
optical networks to mitigate the accumulation of noises
to limit signal degradation and extend the transmission
length of optical paths. Optical regenerators are capa-
ble of re-amplifying (1R), re-shaping (2R), and even re-
timing (3R) the signals and so, called 1R, 2R or 3R
regenerators respectively. Among those regenerators, 3R
regenerators are required for high-speed and long reach
optical paths. Optical regenerator technology for WDM
networks is quite mature and it strongly relies on the
provided data rate; semiconductor optical amplifier (SOA)-
based Mach-Zehnder interferometers have been widely
utilized for amplitude modulation to support data rates up
to 40 Gbps while ultrafast mechanisms in optical fibers or
polarization rotation in SOAs are popularly employed to
deal with higher rates such as beyond 40 Gbps [10, 14].
Recently, all-optical 3R (reamplifying, reshaping, and re-
timing) regeneration devices can directly handle the optical
signal degradation caused by fiber loss, dispersion and the
amplified spontaneous emission noise of EDFAs or fiber
nonlinearity, and overcome the bandwidth bottleneck of
optical–electrical–optical (O/E/O) processing systems.
(b) BER
Fig. 3. Performance limits vs transmission distance for linear (dashed
line) and nonlinear (solid line) transmission schemes at different M-ary
(L
= 80 km).
span
of VER, optical signals with various data rates can be
cost-effectively regenerated. Based on the data rate of
each incoming optical signal, a number of necessary SSRs
is allocated to regenerate the optical signal. In order to
provide the spectrum selectivity in VER, optical coherent
detection with a wavelength tunable local oscillator (LO)
is employed. Along with the multiple-channel and various
data rate regeneration capability, a VER is also able to
convert modulation format distance-adaptively (also known
as re-modulation capability) and hence, it enables saving
the spectrum utilization when the transmission distance is
sufficiently short enough to use more spectrum-efficient
(higher-order) modulation formats. In other words, VERs
can provide 4R regeneration function. However, note that
VER cost seems to be expensive and relies strongly on the
SSR pool size, the number of SSRs [15, 16].
In addition to conventional regenerators, a new re-
generation technology, named virtualized elastic regener-
ator (VER), that is able to regenerate flexibly and cost-
effectively multiple-data-rate optical signals, has been pro-
posed to realize emerging elastic optical networks [14].
VERs are constructed based on spectrum-selective sub-
channel regenerators (SSRs) where each SSR is capable of
regenerating a sub-channel, i.e., 100 Gbps. A VER includes
a set of SSRs and all the incoming optical signals, that
need to be regenerated, share the regeneration resource,
says SSR pool. By sharing SSRs in the regeneration pool
From network point of view, elastic optical networks
that are partially with VER-equipped nodes (i.e. recon-
46
Vol. 2019, No. 1, September
appropriate regenerators to enhance the spectrum utilization
efficiency of the networks (the required LMOD is shorter).
Obviously, selection of regeneration nodes and modulation
format and spectrum assignment strategy are the key for
minimizing the network performance.
III. NETWORK PERFORMANCE EVALUATION
In this section, we evaluate the performances of dynamic
elastic optical networks using different optical regeneration
techniques including 3R- and 4R-capable regeneration, in
term of the overall blocking probability and the accom-
modated traffic volume. In order to clarify the impact of
optical regeneration in dynamic elastic optical networks,
the network performances of three regeneration applicable
network scenarios including (i) no regeneration, (ii) only
3R regeneration and (iii) fully-capable elastic regeneration
(4R) will be tested and compared. For fair comparison, we
employ similar RMSA algorithms for those cases. We also
use two different RMSA algorithms which are a simple
shortest path and first fit algorithm (called First Fit) [21]
and the spectrum-least RSA algorithm which has been
developed in [22] (denoted as Least Spectrum).
Fig. 4. Transmission distance limits vs signal PSD per channel at BER
= 10−3 with L
= 80 km for linear (dashed line) and nonlinear (solid
span
line) transmission schemes at different M-ary QAM formats.
figurable optical add-drop multiplexer (ROADMs)/optical
cross-connects (OXCs)) are capable of not only providing
distance-adaptive and multiple modulation format optical
paths, but also offer the optical path regeneration (including
3R and 4R regeneration). Lightpaths can be regenerated
with/without being re-modulated only at the nodes that
consist of VERs. Furthermore, to establish lightpaths dy-
namically and effectively in elastic optical networks, rout-
ing, modulation and spectrum assignment (RMSA) problem
must be solved efficiently. The applied RMSA scheme
must be able to overcome the optical reach limit constraint
while exploiting distance-adaptive modulation capability of
the networks. As discussed in [18], with a given capacity
of traffic demand, higher-order modulation formats may
offer a spectrum reduction while suffer from an increase
in the regeneration utilization frequency and/or necessary
regenerator devices. Contrarily, a lower-order modulation
format can help to extend the optical reach and so, may
reduce the number of necessary regenerator devices but, it
may result in less spectrum utilization efficiency. There-
fore, employing 4R regeneration with an effective RMSA
algorithm enables improving the spectrum usage efficiency
while dealing with the spectrum continuity and spectrum
consecutiveness constraints in elastic optical networks.
Moreover, two typical network topologies, that are (i)
National Science Foundation network (NSF) consisting of
14 nodes and 22 links, and (ii) US backbone network
(USNET) including 24 nodes and 43 links (shown in Fig-
ure 6) are used for numerical experiments. The regeneration
capable node number is assumed to be limited at 4 and 7
for NSF and USNET respectively and each case will be
tested with 20 random scenarios. We also use following
parameters for the numerical simulation. Each fiber link
can carry up to W spectrum slots (W is fixed at 128)
and the slot bandwidth is assumed to be 12.5 GHz. The
networks can flexibly and dynamically set up and release
optical paths (also called lightpaths). Modulation format
of each lightpath is distance-adaptively assigned. Lightpath
requests arrive sequentially and follow Poisson distribution.
Average arrival rate of ligthpaths is λ (requests per time
unit). Distribution of lightpath holding time is assumed to
be a negative exponential one with the mean hold time of
1/µ (time units). Consequently, the given network traffic
load in Erlangs is λ/µ. Here, the capacity, C, of each
requested lightpath between node pairs is also randomly
assigned between 50 and 100 Gbps following a uniform
distribution. The assumed modulation formats are BPSK,
QPSK, 8-QAM and 16-QAM. The slot bandwidth and the
corresponding transparent reach of BPSK, QPSK, 8-QAM,
and 16-QAM optical signals are given in Table II [21, 22].
In fact, elastic optical networks can use various types of
regenerators (3R or 4R) and low-order modulation formats
can be employed to extend the optical reach and avoid
the use of regenerators. Figure 5 illustrates the differences
among three regeneration applicable elastic optical network
scenarios that are a network without using regenerators,
3R and 4R regeneration capable ones. Here, LMOD is the
optical reach required if the modulation format, MOD, is
used while L1 and L2 are the sub-path lengths. The distance
adaptive modulation capability can be exploited by using
As mentioned above, we evaluate the network perfor-
mance in three comparative regeneration scenarios of elastic
optical networks: (i) without regeneration capability (named
47
Research and Development on Information and Communication Technology
(a) No regeneration scenario
(b) 3R regeneration scenario
(c) 4R regeneration scenario
Fig. 5. Regeneration network scenario comparison.
TABLE II
SUMMARY OF KEY PARAMETERS
Parameter
Spectrum slot number per link
Slot bandwidth
Value
128
12.5 GHz
12.5 Gbps
9600 km
25 Gbps
4800 km
37.5 Gbps
2400 km
50 Gbps
1200 km
50-100 Gbps
1000
Slot capacity
BPSK
Transparent reach
Slot capacity
QPSK
Transparent reach
(a) NSF
Slot capacity
8-QAM
Transparent reach
Slot capacity
16-QAM
Transparent reach
Capacity of requested lightpaths
Connection mean hold time
First-fit and Least-spectrum RSA algorithms (denoted by
First fit w/ 4R and Least spectrum w/ 4R respectively).
The performance of the comparative network scenarios, in
terms of the blocking probability, is shown severally in
Figures 7 and 8 for NSF and USNET network topologies
when the traffic load ranges from 100 to 1500 Erlangs.
These figures verify that the network scenarios using optical
regeneration, i.e. 3R or 4R regeneration, can dramatically
decrease the blocking probability in comparison with that
without regeneration. That is because implementing optical
regeneration can help to resolve the spectrum collision,
save the spectrum resources with higher modulation formats
and enhance the optical reach to improve the network
utilization. Moreover, the results also show that applying
(b) USNET
Fig. 6. Experimental network topologies (NSF and USNET).
No regeneration), (ii) 3R regeneration with two different
RSA algorithms including First-fit and Least-spectrum al-
gorithms (so called First fit w/ 3R and Least spectrum w/
3R correspondingly), and (iii) 4R regeneration also with
48
Vol. 2019, No. 1, September
Fig. 7. Blocking probability for NSF network.
Fig. 9. Accommodated traffic volume comparison.
Fig. 10. Average number of regenerating nodes per lightpath for NSF
network.
Fig. 8. Blocking probability for USNET network.
regeneration is used as the benchmark, so its graph is 1.
The figure describes that, with the same network condi-
tions, using optical regeneration provides higher accepted
traffic volume thanks to the signal regeneration. We can
attain at least 29.8% (45.6%) higher traffic volume with
NSF (USNET) network. Implementing more-efficient RSA
algorithm (i.e. spectrum least) even can further improve
the network performance. However, note that it may results
in higher network CAPEX. In fact, we must consider the
cost of regeneration devices carefully to satisfy the tradeoff
between the CAPEX and the network performance.
4R regeneration offers better performance than that of 3R
regeneration. Such performance improvement is obtained
by re-modulating the optical signal into the optimal mod-
ulation format for exploiting the distance-adaptive feature
of elastic optical networks.
Furthermore, as being verified in Figures 7 and 8, the
performance of the networks also strongly depends on the
applied RMSA algorithm due to the effect of selecting the
regeneration nodes and the modulation format. Optimizing
the regenerating node position and assigning suitable modu-
lation formats play an important role to enhance the overall
spectrum utilization efficiency. It is confirmed that the effect
of optical regeneration is enhanced with larger network.
The main reason is that high-order modulation levels can
be assigned to shorter lightpaths and consequently, help
to lessen the number of spectrum slots required. On the
other hand, larger network which contains longer average
length of lightpaths requires more regeneration resources,
especially for the lightpaths with high-order modulation
format due to the transparent reach limitation.
We have also estimated the average number of regenerat-
ing nodes and that of spectrum slots per lightpath in the ex-
perimental network topologies to determine the requirement
of necessary regeneration resources. Figures 10 and 11
illustrate the obtained numerical results for NSF topology
and Figures 12 and 13 show that of USNET respectively.
Because of the use of same regenerating node selection
strategy, both First fist w/ 3R and First fit w/ 4R scenarios
need almost the same average number of regenerating nodes
for each lightpath. However, the number of regenerated
spectrum slots is decreased with the use of 4R regeneration
thanks to modulate the signals distance-adaptively. The
graphs also verify that, with the Least spectrum algorithm,
the improvement of the network performance costs more
regenerating resources.
Moreover, Figure 9 demonstrates the comparison of
relative accepted traffic volumes among the experimented
scenarios, that are No regeneration, First fit w/3R, First
fit w/ 4R, Least spectrum w/ 3R and 4R, with the given
blocking probability of 10−5. The results obtained by No
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Research and Development on Information and Communication Technology
Fig. 11. Average number of regenerated spectrum slots per lightpath
for NSF network.
Fig. 13. Average number of regenerated spectrum slots per lightpath
for USNET network.
Fig. 14. Modulation efficiency of NSF network.
Fig. 12. Average number of regenerating nodes per lightpath for
USNET network.
Numerical simulation results prove that using optical
regenerators, especially 4R regenerators, can help to ex-
ploit elastic optical networking and enhance the dynamic
network performance for provisioning bandwidth-flexible
lightpath services. It was demonstrated that at least 29.8%
(or 45.6%) more traffic volume can be attained for NSF
(USNET) network. However, optical regenerating devices
are expensive and hence, the trade-off between the required
network performance and the necessary regenerating re-
source cost should be considered carefully in order to cre-
ate future cost-effective, spectrum-efficient and bandwidth-
flexible optical networks.
Finally, Figures 14 and 15 illustrate the modulation
efficiency, which is the ratio of the average spectrum slot
number per established lightpath of each compared scenario
to that of No regeneration one, of both NSF and USNET.
The spectrum slot number of No regeneration scenario is
used as a benchmark and consequently, its normalized value
is one. It demonstrates that although First fit strategy offers
better modulation efficiency (less ratio) for established
lightpaths, it does not consider the spectrum collision an
as a result, its performance is poorer than that of Least
spectrum strategy.
ACKNOWLEDGMENT
IV. CONCLUSION
This research is funded by Vietnam National Foundation
for Science and Technology Development (NAFOSTED)
under grant number 102.02-2015.39.
In this paper, we have investigated the impact of various
optical regeneration techniques including 3R and 4R on
the performance of dynamic elastic optical networks. We
firstly discussed and clarified the differences among optical
regenerating usage scenarios without regeneration and with
regeneration (both 3R and 4R regeneration). We have, then,
evaluated and compared the dynamic elastic optical network
performance, in term of the blocking probability and the
total accepted traffic volume, etc. for three comparative
network scenarios including (i) no regeneration, (ii) with
3R regeneration and (iii) with 4R regeneration capabilities.
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no. 5, pp. 1126–1135, 2015.
[9] M. Jinno, B. Kozicki, H. Takara, A. Watanabe, Y. Sone,
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Le Hai Chau received the B.E. degree
in Electronics and Telecommunications En-
gineering from Posts and Telecommuni-
cations Institute of Technology (PTIT) of
Vietnam in 2003, and the M.Eng. and
D.Eng. degrees in Electrical Engineering
and Computer Science from Nagoya Uni-
versity of Japan in 2009 and 2012, respec-
tively. From 2003 to 2006, he worked at PTIT as a lecturer. He
was a researcher in Nagoya University from 2012 to 2014. He
then became a research scientist at University of California, Davis.
Now, he is a lecturer at PTIT. He is an IEEE member.
[12] A. Bocoi, M. Schuster, F. Rambach, M. Kiese, C.-A. Bunge,
and B. Spinnler, “Reach-dependent capacity in optical net-
works enabled by OFDM,” in Conf. Optical Fiber Commu-
nication, 2009, pp. 1–3.
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grooming and regeneration of wavelength paths in creating
hierarchical optical path networks,” Optics express, vol. 19,
no. 26, pp. B882–B894, 2011.
[14] M. Jinno, K. Yonenaga, H. Takara, K. Shibahara, S. Ya-
manaka, T. Ono, T. Kawai, M. Tomizawa, and Y. Miyamoto,
“Demonstration of translucent elastic optical network based
on virtualized elastic regenerator,” in National Fiber Optic
Engineers Conf. Optical Soc. America, 2012, pp. PDP5B–6.
[15] M. Jinno and H. Takara, “Elastic optical transponder and
regenerator: Toward energy and spectrum efficient optical
transport networks,” in 2012 International Conference on
Photonics in Switching (PS), 2012, pp. 1–3.
Dang Hoai Bac received the B.E. de-
gree from the Hanoi University of Tech-
nology ,Hanoi, Vietnam, in 1997, and both
the M.E. degree and the Ph.D. degree in
Electronics and Telecommunications from
the Posts and Telecommunications Institute
of Technology (PTIT), Hanoi, Vietnam in
2004 and 2010, respectively. He is currently
an Associate Professor/Vice Director at PTIT. His current research
interests include the area of communication theory with a partic-
ular emphasis on modeling, design, and performance evaluation.
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