Generating Realistic Optical Transport Network Topologies

Claunir Pavan; Rui Manuel Morais; José R. Ferreira da Rocha; Armando Nolasco Pinto

doi:10.1364/JOCN.2.000080

Journal of Optical Communications and Networking
Vol. 2,
Issue 1,
pp. 80-90
(2010)
•https://doi.org/10.1364/JOCN.2.000080

Generating Realistic Optical Transport Network Topologies

Claunir Pavan, Rui Manuel Morais, José R. Ferreira da Rocha, and Armando Nolasco Pinto

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Claunir Pavan, Rui Manuel Morais, José R. Ferreira da Rocha, and Armando Nolasco Pinto, "Generating Realistic Optical Transport Network Topologies," J. Opt. Commun. Netw. 2, 80-90 (2010)

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Abstract

We address the problem of generating physical realistic optical transport network topologies. This type of network has characteristics that differ from scale-free networks, such as the Internet. Based on the analysis of a set of real transport topologies, we identify and assess relevant characteristics. A method to generate realistic topologies is proposed. The proposed method is validated by comparing the characteristics of computer-generated and real-world optical transport networks.

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Number	Network	N	L	$⟨ δ ⟩$
1	VIA Network [13]	9	12	2.67
2	BREN [14]	10	11	2.20
3	RNP [15]	10	12	2.40
4	vBNS [16]	12	17	2.83
5	CESNET [17]	12	19	3.17
6	NSFNET [18]	14	21	3.00
7	Italy [19]	14	29	4.14
8	Austria [20]	15	22	2.93
9	Mzima [21]	15	19	2.53
10	ARNES [22]	17	20	2.35
11	Germany [23]	17	26	3.06
12	Spain [24]	17	28	3.29
13	LambdaRail [25]	19	23	2.42
14	Memorex [26]	19	24	2.53
15	CANARIE [27]	19	26	2.74
16	EON [28]	19	37	3.89
17	ARPANET [29]	20	32	3.20
18	PIONIER [30]	21	25	2.38
19	Cox [31]	24	40	3.33
20	SANET [32]	25	28	2.24
21	NEWNET [33]	26	31	2.38
22	Portugal [34]	26	36	2.77
23	RENATER [35]	27	35	2.59
24	GEANT2 [36]	32	52	3.25
25	LONI [37]	33	37	2.24
26	Metrona [38]	33	41	2.48
27	Omnicom [39]	38	54	2.84
28	Internet 2 [40]	56	61	2.18
29	USA 100 [41]	100	171	3.42

Variable	Description
N	Number of nodes
${⟨ δ ⟩}_{\min}$	Minimum average nodal degree
${⟨ δ ⟩}_{\max}$	Maximum average nodal degree
A	Area of the plane in arbitrary units
R	Number of regions
d	Minimum distance between two nodes
α	Waxman link probability parameter
β	Waxman link probability parameter
φ	number of simulations

Variable	Minimum		${Average}^{*}$		Maximum		Std. Deviation
Variable	Real	CG	Real	CG	Real	CG	Real	CG
δ	2	2	2.80	2.80	10	8	0.4–2.0	0.6–2.6
h	1	1	3.40	3.20	21	20	0.7–4.6	0.7–4.3
ω	2	2	2.25	2.30	7	6	0.0–0.9	0.1–1.0
θ	1	1	2.21	2.26	7	6	0.0–1.0	0.0–1.1
c	0	0	0.19	0.16	1	1	0.0–0.4	0.0–0.4

Number	Network	N	L	$⟨ δ ⟩$
1	VIA Network [13]	9	12	2.67
2	BREN [14]	10	11	2.20
3	RNP [15]	10	12	2.40
4	vBNS [16]	12	17	2.83
5	CESNET [17]	12	19	3.17
6	NSFNET [18]	14	21	3.00
7	Italy [19]	14	29	4.14
8	Austria [20]	15	22	2.93
9	Mzima [21]	15	19	2.53
10	ARNES [22]	17	20	2.35
11	Germany [23]	17	26	3.06
12	Spain [24]	17	28	3.29
13	LambdaRail [25]	19	23	2.42
14	Memorex [26]	19	24	2.53
15	CANARIE [27]	19	26	2.74
16	EON [28]	19	37	3.89
17	ARPANET [29]	20	32	3.20
18	PIONIER [30]	21	25	2.38
19	Cox [31]	24	40	3.33
20	SANET [32]	25	28	2.24
21	NEWNET [33]	26	31	2.38
22	Portugal [34]	26	36	2.77
23	RENATER [35]	27	35	2.59
24	GEANT2 [36]	32	52	3.25
25	LONI [37]	33	37	2.24
26	Metrona [38]	33	41	2.48
27	Omnicom [39]	38	54	2.84
28	Internet 2 [40]	56	61	2.18
29	USA 100 [41]	100	171	3.42

Variable	Description
N	Number of nodes
${⟨ δ ⟩}_{\min}$	Minimum average nodal degree
${⟨ δ ⟩}_{\max}$	Maximum average nodal degree
A	Area of the plane in arbitrary units
R	Number of regions
d	Minimum distance between two nodes
α	Waxman link probability parameter
β	Waxman link probability parameter
φ	number of simulations

Abstract

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Tables (3)

Equations (9)

Journal of Optical Communications and Networking

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