On clustering coherent optics point-to-multipoint trees for cost-effective bandwidth assignment in MANs

José Alberto Hernández; Farhad Arpanaei; Antonio Napoli; Carlos Castro; Óscar González de Dios; Juan Pedro Fernández-Palacios

doi:10.1364/JOCN.497459

Journal of Optical Communications and Networking
Vol. 15,
Issue 12,
pp. 999-1007
(2023)
•https://doi.org/10.1364/JOCN.497459

On clustering coherent optics point-to-multipoint trees for cost-effective bandwidth assignment in MANs

José Alberto Hernández, Farhad Arpanaei, Antonio Napoli, Carlos Castro, Óscar González de Dios, and Juan Pedro Fernández-Palacios

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José Alberto Hernández, Farhad Arpanaei, Antonio Napoli, Carlos Castro, Óscar González de Dios, and Juan Pedro Fernández-Palacios, "On clustering coherent optics point-to-multipoint trees for cost-effective bandwidth assignment in MANs," J. Opt. Commun. Netw. 15, 999-1007 (2023)

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Abstract

Point-to-multipoint (P2MP) coherent pluggable transceivers leveraging digital subcarrier multiplexing (DSCM) techniques are gaining momentum among telecommunication operators as a technology that can potentially provide broadband connectivity in metropolitan area networks (MANs) with flexible bandwidth allocation at reduced costs. This technology allows trees to be built where central metro (hub) nodes are interconnected with remote access/aggregation (spoke) nodes with dedicated and flexible bandwidth slices, enabling better resource management, simplified architectures, and reduced costs. This paper proposes a modified version of AI/ML clustering techniques that concentrates on the same P2MP tree as those low-rate leaf nodes with uncorrelated daily traffic patterns in a cost-effective manner, thus allowing 10%–18% tree reductions. This, when compared with fixed P2P transceivers, translates into potential CAPEX savings between 40% and 50% in the different scenarios here considered.

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	h1	h2	h3	h4	h5	h6	h7	h8	h9	h10	h11	h12	h13	h14	h15	h16	h17	h18	h19	h20	h21	h22	h23	h24
Cluster 2 node 1	1	1	1	1	1	1	1	1	2	4	4	3	4	3	3	3	2	2	2	2	1	1	1	2
Cluster 2 node 2	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Cluster 2 node 3	5	3	1	1	1	2	2	1	2	2	3	5	4	4	3	3	2	3	4	4	3	5	6	3
Cluster 2 node 4	1	1	1	1	1	1	1	1	1	2	1	1	1	1	1	2	2	1	1	1	1	1	2	1
Cluster 2 node 5	2	3	1	2	1	1	1	3	2	2	2	4	3	5	5	3	3	2	3	4	1	2	3	3
Cluster 2 node 6	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Cluster 2 node 7	1	1	1	1	1	1	1	2	2	1	1	1	1	1	1	1	1	1	2	1	2	1	1	1
Sum	12	11	7	8	7	8	8	10	11	13	13	16	15	16	15	14	12	11	14	14	10	12	15	12

Peak (Gb/s)	Variability	CA1	Largest-Fit	Savings
$U (10, 100)$	30% of peak	172 trees	183 trees	6.0%
$U (50, 100)$	30% of peak	220 trees	250 trees	12.0%
$U (10, 150)$	30% of peak	257 trees	278 trees	7.6%
$U (10, 100)$	80% of peak	250 trees	278 trees	5.8%
$U (50, 100)$	80% of peak	333 trees	397 trees	16.1%
$U (10, 150)$	80% of peak	440 trees	520 trees	18.2%

Peak (Gb/s)	Variability	$α$	Grid (km $\times$ km)	CA2	Largest-Fit	Savings
$U (10, 100)$	80% of peak	1	$100 \times 100$	162 trees	172 trees	5.8%
$U (10, 100)$	80% of peak	1	$500 \times 500$	162 trees	172 trees	5.8%
$U (10, 100)$	80% of peak	0.75	$100 \times 100$	163 trees	173 trees	5.2%
$U (10, 100)$	80% of peak	0.75	$500 \times 500$	163 trees	173 trees	5.2%
$U (10, 100)$	80% of peak	0.5	$100 \times 100$	164 trees	172 trees	4.6%
$U (10, 100)$	80% of peak	0.5	$500 \times 500$	164 trees	172 trees	4.6%
$U (10, 100)$	80% of peak	0.25	$100 \times 100$	169 trees	172 trees	1.7%
$U (10, 100)$	80% of peak	0.25	$500 \times 500$	169 trees	172 trees	1.7%
$U (10, 100)$	80% of peak	0	$100 \times 100$	172 trees	172 trees	0%
$U (10, 100)$	80% of peak	0	$500 \times 500$	172 trees	172 trees	0%

Peak (Gb/s)	Variability	400G	200G	100G	10G	P2P Cost Units	CA2 ( $α = 1$ )	400G	100G	P2MP CU	CAPEX Savings
$U (0, 100)$	30% of peak	0	234	698	68	10,860 CU	163 trees	234	766	7404 CU	46.7%
$U (10, 100)$	30% of peak	0	264	736	0	11,584 CU	172 trees	264	736	7584 CU	52.7%
$U (50, 100)$	30% of peak	0	482	518	0	12,892 CU	220 trees	482	518	8892 CU	45.0%
$U (0, 100)$	50% of peak	12	369	558	61	11,894 CU	184 trees	381	619	8286 CU	43.5%
$U (10, 100)$	50% of peak	14	411	575	0	12,662 CU	193 trees	425	575	8550 CU	48.0%
$U (50, 100)$	50% of peak	27	711	262	0	14,644 CU	250 trees	738	262	10,644 CU	40.4%

	h1	h2	h3	h4	h5	h6	h7	h8	h9	h10	h11	h12	h13	h14	h15	h16	h17	h18	h19	h20	h21	h22	h23	h24
Cluster 2 node 1	1	1	1	1	1	1	1	1	2	4	4	3	4	3	3	3	2	2	2	2	1	1	1	2
Cluster 2 node 2	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Cluster 2 node 3	5	3	1	1	1	2	2	1	2	2	3	5	4	4	3	3	2	3	4	4	3	5	6	3
Cluster 2 node 4	1	1	1	1	1	1	1	1	1	2	1	1	1	1	1	2	2	1	1	1	1	1	2	1
Cluster 2 node 5	2	3	1	2	1	1	1	3	2	2	2	4	3	5	5	3	3	2	3	4	1	2	3	3
Cluster 2 node 6	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Cluster 2 node 7	1	1	1	1	1	1	1	2	2	1	1	1	1	1	1	1	1	1	2	1	2	1	1	1
Sum	12	11	7	8	7	8	8	10	11	13	13	16	15	16	15	14	12	11	14	14	10	12	15	12

José Alberto Hernández	https://orcid.org/0000-0002-9551-4308
Farhad Arpanaei	https://orcid.org/0000-0003-1061-0614
Óscar González de Dios	https://orcid.org/0000-0002-1898-0807

Abstract

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Figures (6)

Tables (4)

Equations (4)

Journal of Optical Communications and Networking