Multicast Traffic Grooming in Tap-and-Continue WDM Mesh Networks

Rongping Lin; Wen-De Zhong; Sanjay Kumar Bose; Moshe Zukerman

doi:10.1364/JOCN.4.000918

Journal of Optical Communications and Networking
Vol. 4,
Issue 11,
pp. 918-935
(2012)
•https://doi.org/10.1364/JOCN.4.000918

Multicast Traffic Grooming in Tap-and-Continue WDM Mesh Networks

Rongping Lin, Wen-De Zhong, Sanjay Kumar Bose, and Moshe Zukerman

Not Accessible

Your library or personal account may give you access

Get PDF
Email
Share
Get Citation
Copy Citation Text
Rongping Lin, Wen-De Zhong, Sanjay Kumar Bose, and Moshe Zukerman, "Multicast Traffic Grooming in Tap-and-Continue WDM Mesh Networks," J. Opt. Commun. Netw. 4, 918-935 (2012)

Export Citation
- BibTex
- Endnote (RIS)
- HTML
- Plain Text
Citation alert
Save article

Abstract

Multicast applications are expected to be major drivers of Internet traffic growth. As most multicast connections require much lower bandwidth than the capacity offered by a wavelength, multicast traffic grooming is needed to efficiently use network resources. Recent research on multicast grooming has focused on light-trees because of their natural advantage for multicast traffic. However, using light-trees may lead to some serious negative side effects because of light splitting. In this paper, we investigate the multicast traffic grooming problem in tap-and-continue (TaC) networks, where a node can tap a small amount of incoming optical power for the local station while forwarding the remainder to an output. We first propose a simple and efficient node architecture with the TaC mechanism. We use this in an integer linear programming (ILP) formulation with the objective of minimizing the network cost in terms of the number of higher layer electronic ports and the number of wavelengths used. Since the ILP is not scalable, two heuristic algorithms, multicast trail grooming (MTG) and multiple destination trail-based grooming (MDTG), are proposed. Using the ILP, we show that having more costly nodes with multicast capability does not improve the performance significantly. The solutions obtained by MTG and MDTG are close to the ILP optimal solution. MTG and MDTG are shown to work efficiently for typical network topologies such as NSFNET, with MTG showing better performance than MDTG.

Full Article | PDF Article

More Like This

Dynamic Multicast Traffic Grooming in Optical WDM Mesh Networks: Lightpath Versus Light-Tree

Xiaojun Yu, Gaoxi Xiao, and Tee-Hiang Cheng
J. Opt. Commun. Netw. 5(8) 870-880 (2013)

Design of Light-Tree Based Optical Inter-Datacenter Networks

Rongping Lin, Moshe Zukerman, Gangxiang Shen, and Wen-De Zhong
J. Opt. Commun. Netw. 5(12) 1443-1455 (2013)

Multicast Overlay for High-Bandwidth Applications Over Optical WDM Networks

Arush Gadkar, Jeremy Plante, and Vinod M. Vokkarane
J. Opt. Commun. Netw. 4(8) 571-585 (2012)

Previous Article Next Article

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (17)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (8)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (43)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Index	Requests	Traffic routings
1	(4; 1, 6; 2)	( $4 \to 6$ ) ( $6 \to 1$ )
2	(6; 1, 3, 5; 12)	( $6 \to 1$ , 3, 5)
3	(6; 1, 2, 3, 4, 5; 10)	( $6 \to 2$ , 3, 5) ( $2 \to 1$ , 4)
4	(5; 1, 2; 1)	( $5 \to 1$ , 2)
5	(6; 2, 3, 5; 1)	( $6 \to 2$ , 3, 5)
6	(3; 1, 2, 4, 5; 6)	( $3 \to 4$ , 5) ( $5 \to 1$ , 2)
7	(1; 2, 3, 4, 5, 6; 6)	( $1 \to 2$ , 3, 4, 5) ( $4 \to 6$ )
8	(6; 1; 7)	( $6 \to 1$ )
9	(2; 5, 6; 11)	( $2 \to 5$ , 6)
10	(3; 4, 5; 3)	( $3 \to 4$ , 5)

Optimal schemes	Cost	φ	A	B	$A_{i}$ (1 $\leq i \leq$ 6)	$B_{i}$ (1 $\leq i \leq$ 6)
Trail-based	90	3	9	20	1, 2, 1, 1, 1, 3	4, 3, 3, 3, 5, 2
Light-tree-based	89	2	10	19	2, 2, 1, 1, 1, 3	4, 2, 3, 3, 5, 2

Trail	Physical route
( $1 \to 2$ , 3, 4, 5)	$1 \to 2 \to 4 \to 5 \to 6 \to 3 (λ_{3})$
( $2 \to 1$ , 4)	$2 \to 1 \to 4 (λ_{1})$
( $2 \to 5$ , 6)	$2 \to 3 \to 6 \to 3 \to 5 (λ_{1})$
( $3 \to 4$ , 5)	$3 \to 2 \to 4 \to 5 (λ_{1})$
( $4 \to 6$ )	$4 \to 2 \to 3 \to 6 (λ_{2})$
( $5 \to 1$ , 2)	$5 \to 3 \to 2 \to 1 (λ_{3})$
( $6 \to 1$ )	$6 \to 5 \to 4 \to 1 (λ_{1})$
( $6 \to 1$ , 3, 5)	$6 \to 5 \to 3 \to 2 \to 1 (λ_{2})$
( $6 \to 2$ , 3, 5)	$6 \to 3 \to 5 \to 4 \to 1 \to 2 (λ_{2})$

Trail	Physical route
( $1 \to 2$ , 3, 4)	$1 \to 4 \to 2 \to 3 (λ_{2})$
( $2 \to 5$ , 6)	$2 \to 4 \to 5 \to 6 (λ_{4})$
( $3 \to 4$ , 5)	$3 \to 5 \to 4 (λ_{2})$
( $4 \to 5$ )	$4 \to 5 (λ_{2})$
( $5 \to 1$ , 2)	$5 \to 4 \to 2 \to 1 (λ_{1})$
( $5 \to 6$ )	$5 \to 6 (λ_{2})$
( $6 \to 1$ , 2, 3, 4, 5)	$6 \to 3 \to 5 \to 4 \to 1 \to 2 (λ_{3})$
( $6 \to 1$ )	$6 \to 5 \to 4 \to 1 (λ_{4})$
( $6 \to 1$ , 3, 5)	$6 \to 3 \to 5 \to 4 \to 1 (λ_{5})$

	Cost	A	B	Ports	φ	Wavelinks
1–13	3479.84	99.44	459.8	559.24	24.88	720.84
1–9	2918.04	99	369.24	468.24	21.72	621.12
7–13	4921.96	99.32	694.24	793.56	32.12	960.48

	Cost	A	B	Ports	φ	Wavelinks
1–13	3508.24	99.44	459.8	559.24	30.56	832.36
1–9	2942.04	99	369.24	468.24	26.52	690.32
7–13	4963.16	99.32	694.24	793.56	40.36	1169.6

Abstract

Cited By

Figures (17)

Tables (8)

Equations (43)

Journal of Optical Communications and Networking