Minimizing the cost of hierarchical optical transport network traffic grooming boards in metro networks

Aryanaz Attarpour; Memedhe Ibrahimi; Nicola Di Cicco; Francesco Musumeci; Andrea Castoldi; Mario Ragni; Massimo Tornatore

doi:10.1364/JOCN.489421

Journal of Optical Communications and Networking
Vol. 15,
Issue 10,
pp. E18-E28
(2023)
•https://doi.org/10.1364/JOCN.489421

Minimizing the cost of hierarchical optical transport network traffic grooming boards in metro networks

Aryanaz Attarpour, Memedhe Ibrahimi, Nicola Di Cicco, Francesco Musumeci, Andrea Castoldi, Mario Ragni, and Massimo Tornatore

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Aryanaz Attarpour, Memedhe Ibrahimi, Nicola Di Cicco, Francesco Musumeci, Andrea Castoldi, Mario Ragni, and Massimo Tornatore, "Minimizing the cost of hierarchical optical transport network traffic grooming boards in metro networks," J. Opt. Commun. Netw. 15, E18-E28 (2023)

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About this Article
History
- Original Manuscript: March 9, 2023
- Revised Manuscript: May 31, 2023
- Manuscript Accepted: June 9, 2023
- Published: September 7, 2023
Virtual Issues
Journal of Optical Communications and Networking Optical Networks and Systems (ONS) Symposium at GLOBECOM 2022 (2023)

Abstract

Metro network operators aim to design scalable and cost-effective network architectures to address the capacity expansion due to ongoing traffic growth. While coherent transmission (e.g., at 100 Gbps and 200 Gbps) can address capacity growth, operators must also support legacy non-coherent transmission technology (e.g., at 10 Gbps). Therefore, operators must devise new practical solutions to jointly support new and legacy transmission technologies, while minimizing the network cost. This study investigated the optimization problem arising when deploying a metro network with a hierarchical architecture of grooming nodes. More precisely, we optimized the deployment cost of hierarchical traffic-grooming stacked optical transport network (OTN) boards with a mix of coherent and non-coherent transmission technologies in metro/regional networks composed of interconnected rings, while considering a filterless node architecture. We formulated the optimization problem using integer linear programming. Then, to deal with problem scalability, we proposed a comprehensive set of novel heuristic approaches based on genetic algorithms, simulated annealing, and a knowledge-domain heuristic (local search). We also compared the proposed approaches with baseline strategies used by network operators and showed that we can reach up to 50% cost savings compared to these baselines.

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$N_{1 A P}$ , $N_{2 A P}$	Subset of logical nodes representing client interfaces of OTU2-ADM and OTU4-ADM boards
$N$	Set of logical nodes representing OTN boards and interfaces
$N_{1}$ , $N_{2}$ , $N_{3}$ , $N_{4}$	Subset of logical nodes representing OTU2-ADM, OTU4-ADM, and OTU-TPD boards and ROADMs
$E$	Set of links representing optical links and connections between the interfaces of OTN boards
$E_{0}$	Subset of logical links representing connections of a client to the interfaces of OTU2-ADM and OTU4-ADM
$E_{1}, E_{2}$	Subset of logical links representing connections to client interfaces to OTU2-ADM and OTU4-ADM
$E_{3}$	Subset of logical links representing connections of a client to the interfaces of OTU-TPD
$E_{4}$	Subset of links representing the line interfaces between OTU2-ADM and OTU4-ADM
$E_{5}$	Subset of links representing the line interfaces between OTU4-ADM and OTU-TPD
$E_{6}$	Subset of links representing coherent colored interfaces between OTU-TPD and a ROADM
$E_{7}$	Subset of links representing non-coherent colored interfaces between OTU2-ADM and a ROADM
$E_{R}$	Subset of links representing links between ROADMs
$W$	Set of wavelengths
$D$	Set of connection requests (demands)
$M$	Assumed number

$y_{i, j}$	Binary value equal to 1 if link ( $i, j$ ) is activated/used
$τ_{i, w}$	Binary variable equal to 1 if transponder $i$ is activated and uses wavelength $w$
$f_{i, j, w}$	Binary variable equal to 1 if wavelength $w$ is used in active link ( $i, j$ )
$λ_{w}$	Binary variable equal to 1 if wavelength $w$ is used in the network (in any link $f_{i, j, w}$ )
$b_{i, j, w}$	Binary variable equal to 1 if wavelength $w$ is being broadcasted on link ( $i, j$ )
$μ_{j}$	Cost of logical node $i$ , i.e., OTN board/interface
$ρ_{i}$	Cost of transponder $i$

Approach	Best Cost (cu)	Avg Cost (cu)	Avg Time
ILP	1741	–	$< 2 d a y s$
GA	1741	1741	$< 1 m i n$
GA, $m = 2$	1741	1741	$< 1 m i n$
GA, $m = 1$	1741	1741	$< 1 m i n$
SA	2394	2522	1 min
SA, $m = 2$	1859	1955	$< 1 m i n$
SA, $m = 1$	1741	1741	$< 1 m i n$
LS	1741	—	1 s
Baseline	3591	—	—

Approach	Best Cost (cu)	Avg Cost (cu)	Avg Time
ILP	1614	—	$< 1 d a y$
GA	1614	1614	$< 1 m i n$
GA, $m = 2$	1614	1614	$< 1 m i n$
GA, $m = 1$	1614	1614	1 min
SA	2227	2829	$< 3 m i n$
SA, $m = 2$	1636	1650	$< 1 m i n$
SA, $m = 1$	1614	1614	1 min
LS	1622	—	1s
Baseline	3094	—	—

Approach	Best Cost (cu)	Avg Cost (cu)	Avg Time
ILP	N.A.	—	—
GA	N.A.	—	—
GA, $m = 2$	5996	6002	$< 1 m i n$
GA, $m = 1$	5996	5996	1 min
SA	N.A.	—	—
SA, $m = 2$	10600	11026	6 min
SA, $m = 1$	6374	6570	4 min
SA-In., $m = 2$	6503	6503	5 min
SA-In., $m = 1$	6028	6028	3.7 min
LS	6028	—	1 s
Baseline	13003	—	—

ILP	Integer linear programming
GA	Genetic algorithm
SA	Simulated annealing
LS	Local search
SA-In.	Simulated annealing with heuristic initialization
ROADM	Reconfigureable optical add drop multiplexer
OTN	Optical transport network
OTU2-ADM	Optical transport unit2-add drop mulitplexer
OTU4-ADM	Optical transport unit4-add drop mulitplexer
OTU-TPD	Optical transport unit-transponder
DCM	Dispersion compensation module
WSS	Wavelength selective switch
ADM	Add drop multiplexer
N.A.	Not applicable

Memedhe Ibrahimi	https://orcid.org/0000-0002-9823-8206
Francesco Musumeci	https://orcid.org/0000-0002-3617-5916
Massimo Tornatore	https://orcid.org/0000-0003-0740-1061

Abstract

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Journal of Optical Communications and Networking