Efficient statistical QoT-aware resource allocation in EONs over the C+L-band: a multi-period and low-margin perspective

Mahdieh Mehrabi; Hamzeh Beyranvand; Mohammad Javad Emadi; Farhad Arpanaei

doi:10.1364/JOCN.515081

Journal of Optical Communications and Networking
Vol. 16,
Issue 5,
pp. 577-592
(2024)
•https://doi.org/10.1364/JOCN.515081

Efficient statistical QoT-aware resource allocation in EONs over the C+L-band: a multi-period and low-margin perspective

Mahdieh Mehrabi, Hamzeh Beyranvand, Mohammad Javad Emadi, and Farhad Arpanaei

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Mahdieh Mehrabi, Hamzeh Beyranvand, Mohammad Javad Emadi, and Farhad Arpanaei, "Efficient statistical QoT-aware resource allocation in EONs over the C+L-band: a multi-period and low-margin perspective," J. Opt. Commun. Netw. 16, 577-592 (2024)

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Abstract

Recently, multi-band elastic optical networks (MB-EONs) have been considered a viable solution to increase the transmission bandwidth in optical networks. To improve spectral efficiency and reduce the blocking ratio, the general signal-to-noise ratio (GSNR) as a quality-of-transmission (QoT) metric must be accurately calculated in the routing, modulation level, and spectrum assignment algorithms used in elastic optical networks (EONs). The interference prediction methods commonly used for single-band EONs are not efficient in the case of MB-EONs because of the inter-channel stimulated Raman scattering impact and their wide spectrum. In this paper, we propose a statistical method to predict the interference noise in C+L-band EONs considering multi-period planning. The proposed algorithm, which utilizes the predicted total number of channels (PTNC) on each link for given requests, is a low-margin, fast, and cost-effective method. Additionally, the proposed PTNC algorithm can also be used for single-period planning. Our simulation results indicate that the proposed PTNC algorithm combines the advantages of both studied benchmark algorithms. It has a low complexity order and execution time that are comparable to those of the fully loaded algorithm, which is currently employed by the network operators. However, this benchmark does not achieve the best spectral efficiency. Furthermore, the PTNC method and the other benchmark that determines margin through an exhaustive search, referred to as margin exhaustive search (MES), achieve remarkable spectral efficiency and residual capacity with fewer transceivers, resulting in lower capital expenditure requirements. Nevertheless, the MES algorithm may not be practical due to the requirement of reconfiguring established lightpaths and its high complexity order, particularly in multi-period planning.

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Refs.	EON	Multi-band	Multi-period	Low-Margin and Highly Accurate	Spectrum-Efficient	Low-Complexity	Cost-Effective
[2]	✓	✓	✗	✓	✓	✗	✓
[4]	✓	✓	✗	✗	✓	✓	✓
[5]	✓	✓	✗	✓	✓	✗	✓
[18]	✗	✗	✗	✗	✗	✓	✗
[19]	✗	✓	✗	✗	✗	✓	✗
[20]	✓	✗	✗	✗	✗	✓	✗
[21]	✓	✓	✓	✗	✗	✓	✓
[23]	✗	✓	✗	✓	✓	✗	✓
[24]	✓	✓	✗	✓	✓	✗	✓
[25]	✓	✗	✗	✓	✓	✗	✓
This paper	✓	✓	✓	✓	✓	✓	✓

Symbols	Definitions
${\hat{N}}_{c h, l}^{j}$	Predicted total number of channels on link $l$ , calculated at the beginning of period $j$
$N_{c h, l}$	Number of channels created on link $l$ until now
${\hat{N}}_{c, r}^{j}$	Predicted number of LPs established for request $r$ , from period $j$ until the end
$c_{r}^{j}$	Each predicted LP for request $r$ , at the beginning of period $j$
${\hat{P}}_{1} (k \| c_{r}^{j})$ , ${\hat{P}}_{2} (k \| c_{r}^{j})$	Two simple initial estimates of the probability of establishing LP $c_{r}^{j}$ on the $k$ th candidate path
$\hat{P} (k \| c_{r}^{j})$	Average value of ${\hat{P}}_{1} (k \| c_{r}^{j})$ and ${\hat{P}}_{2} (k \| c_{r}^{j})$
$\hat{P} (l \| c_{r}^{j}) /$ $P (l \| c_{r}^{j})$	Initial/final estimate of the probability of using link $l$ by predicted LP $c_{r}^{j}$
$P (k \| c_{r}^{j})$	Final estimate of the probability of establishing LP $c_{r}^{j}$ on the $k$ th candidate path
$L_{l}^{j}$	Predicted value for load of link $l$ , calculated at the beginning of period $j$

Scenarios		Link’s Load Formulas
Single-period		$L_{l}^{j} = \sum_{r \in R^{l}} {\hat{N}}_{c, r}^{j} = \| R^{l} \|, j = 1$
Multi-period	PTNC-LP	$L_{l}^{j} = \sum_{r \in R^{l}} {\hat{N}}_{c, r}^{j}, j = 1$
Multi-period	PTNC-EP	$L_{l}^{j} = N_{c h, l} + \sum_{r \in R^{l}} {\hat{N}}_{c, r}^{j}$ , $\forall j \in {1, 2, . . ., N_{p}}$

Network	Link Length [km] Min/Avg/Max	Nodal Degree Min/Avg/Max	$\| R \|$	BER	$\tilde{m}$
DT	36.9/186.26/352.6	2/3.29/6	700	$10^{- 3}$	4
JP	47.4/437.31/1256.4	2/2.83/4	350	$10^{- 3}$	3
US	250/1002.3/2600	2/3.58/5	500	$1.5 \times 10^{- 2}$	2

				Residual	Modulation	Execution	Mean of
Network	$P_{0}$ [dBm]	Algorithm	SE	Capacity [GHz]	Cardinality	Time [s]	GSNR’s PPE (%)
DT	−3.9	Fully loaded	16.88	58.95	10.38	71.9	12.23
		MES	17.16	63.72	11.8	1222.5	2.059
		EIPE	17.11	66.66	11.47	102.9	4.892
		PTNC-LP	17.16	68.4	11.7	72.7	2.876
		PTNC-EP	17.17	68.51	11.74	69.1	2.624
JP	−3.7	Fully loaded	14.75	44.12	8.44	54.3	13.41
		MES	15.15	57.08	10.17	528	3.869
		EIPE	15.11	58.68	9.94	114.1	5.746
		PTNC-LP	15.16	59.55	10.19	76.9	3.705
		PTNC-EP	15.17	59.61	10.22	73.7	3.482
US	−2.9	Fully loaded	11.14	26.55	6.64	73	22.16
		MES	11.69	50.54	9.23	1991.4	8.3649
		EIPE	11.46	47.27	8.33	184.6	13.19
		PTNC-LP	11.66	51.64	9.17	110.2	8.297
		PTNC-EP	11.67	52.9	9.27	100.2	7.432

Abstract

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Journal of Optical Communications and Networking