Abstract

Dynamic grooming deals with requests for wavelength allocation based on a dynamic pattern of arrivals in contrast to the situation of static grooming in which the pattern of arrivals must be previously known. Solutions for dynamic grooming typically involve the construction of an auxiliary graph for deciding on the routing and wavelength assignment. An auxiliary graph can represent the network partially leading to scalable solutions; however, a previous proposal employing a reduced auxiliary graph produces blocking that is not fairly distributed among calls. A novel algorithm is thus proposed in this paper for achieving fairness in relation to the blocking of calls. This algorithm uses alternative routing rather than shortest-path routing as well as auxiliary graphs based on the virtual topology. Results reveal a higher degree of fairness obtained by the use of the novel algorithm than by previously proposed algorithms.

© 2010 Optical Society of America

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References

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  1. K. Zhu, B. Mukherjee, “A review of traffic grooming in WDM optical networks: architectures and challenges,” Opt. Networks Mag., vol. 4, no. 2, pp. 55–64, Feb. 2003.
  2. S. Huang, R. Dutta, “Dynamic traffic grooming: the changing role of traffic grooming,” IEEE Commun. Surv. & Tutorials, vol. 8, no. 4, pp. 32–50, 2006.
  3. R. Dutta, A. E. Kamal, G. N. Rouskas, Traffic Grooming for Optical Networks: Foundations, Techniques and Frontiers. Springer, 2008.
    [CrossRef]
  4. R. Dutta, G. N. Rouskas, “Traffic grooming in WDM networks: past and future,” IEEE Network, vol. 16, no. 6, pp. 46–56, Nov./Dec. 2002.
    [CrossRef]
  5. O. Gerstel, R. Ramaswami, G. Sasaki, “Cost-effective traffic grooming in WDM rings,” IEEE/ACM Trans. Netw., vol. 8, no. 5, pp. 618–630, 2000.
    [CrossRef]
  6. A. Chiu, E. Modiano, “Traffic grooming algorithms for reducing electronic multiplexing costs in WDM ring networks,” J. Lightwave Technol., vol. 18, no. 1, pp. 2–12, 2000.
    [CrossRef]
  7. H. Liu, F. Tobagi, “Traffic grooming in WDM SONET UPSR rings with multiple line speeds,” in Proc. of IEEE INFOCOM, 2005, pp. 718–729.
  8. S. Huang, R. Dutta, G. N. Rouskas, “Traffic grooming in path, star, and tree networks: complexity, bounds, and algorithms,” IEEE J. Sel. Areas Commun., vol. 24, no. 4, pp. 66–82, 2006.
    [CrossRef]
  9. J. Hu, B. Leida, “Traffic grooming, routing, and wavelength assignment in optical WDM mesh networks,” in Proc. of IEEE INFOCOM, 2004, pp. 1340–1351.
  10. W. Yao, B. Ramamurthy, “A link bundled auxiliary graph model for constrained dynamic traffic grooming in WDM mesh networks,” IEEE J. Sel. Areas Commun., vol. 23, no. 8, pp. 1542–1555, 2005.
    [CrossRef]
  11. C. Xin, “Blocking analysis of dynamic traffic grooming in mesh WDM optical networks,” IEEE/ACM Trans. Netw., vol. 15, no. 3, pp. 721–733, 2007.
    [CrossRef]
  12. F. Palmieri, U. Fiore, S. Ricciardi, “SPARK: a smart parametric online RWA algorithm,” J. Commun. Networks, vol. 9, no. 4, pp. 368–376, 2007.
    [CrossRef]
  13. C. Xin, C. Qiao, “Performance analysis of multi-hop traffic grooming in mesh WDM optical networks,” in Proc. of the Int. Conf. on Computer Communications and Networks, 2003, pp. 237–242.
  14. E. A. Doumith, M. Gagnaire, “Impact of traffic predictability on WDM EXC/OXC network performance,” IEEE J. Sel. Areas Commun., vol. 25, no. 5, pp. 895–904, 2007.
    [CrossRef]
  15. M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
    [CrossRef]
  16. Q.-D. Ho, M.-S. Lee, “Time-efficient near-optimal wavelength assignment in dynamically-reconfigurable WDM networks,” in Proc. of the IEEE Workshop on High Performance Switching and Routing, 2005, pp. 453–456.
  17. T.-T. N. Thi, T. T. Minh, Q.-D. Hos, M.-S. Lee, “A time and cost efficient dynamic traffic grooming algorithm for optical mesh networks,” in Proc. of the 2nd Int. IEEE/Create-Net Workshop on Traffic Grooming, 2005, pp. 315–320.
  18. C. Xin, “Dynamic traffic grooming in optical networks with wavelength conversion,” IEEE J. Sel. Areas Commun., vol. 25, no. 9, pp. 50–57, 2007.
    [CrossRef]
  19. A. Jaekel, A. Bari, Y. Chen, S. Bandyopadhyay, “New techniques for efficient traffic grooming in WDM mesh networks,” in Proc. of IEEE Int. Conf. on Computer Communications and Networks, 2007, pp. 303–308.
  20. Q.-D. Ho, M.-S. Lee, “A zone-based approach for scalable dynamic traffic grooming in large WDM mesh networks,” IEEE J. Lightwave Technol., vol. 25, no. 1, pp. 261–270, 2007.
    [CrossRef]
  21. K. Zhu, B. Mukherjee, “On-line approaches for provisioning connections of different bandwidth granuralities in WDM mesh networks,” in Optical Fiber Communication Conf., 2002, pp. 549–551.
  22. H. Zhu, H. Zang, K. Zhu, B. Mukherjee, “Dynamic traffic grooming in WDM mesh networks using a novel graph model,” Opt. Networks Mag., vol. 4, no. 3, pp. 65–75, Mar. 2003.
  23. R. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling. Wiley, 1991.
  24. A. C. Drummond, N. L. S. da Fonseca, “On-line dynamic traffic grooming algorithms for WDM mesh networks,” in IEEE Int. Conf. on Communications, 2009, pp. 1–5.

2008 (1)

M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
[CrossRef]

2007 (5)

C. Xin, “Dynamic traffic grooming in optical networks with wavelength conversion,” IEEE J. Sel. Areas Commun., vol. 25, no. 9, pp. 50–57, 2007.
[CrossRef]

Q.-D. Ho, M.-S. Lee, “A zone-based approach for scalable dynamic traffic grooming in large WDM mesh networks,” IEEE J. Lightwave Technol., vol. 25, no. 1, pp. 261–270, 2007.
[CrossRef]

C. Xin, “Blocking analysis of dynamic traffic grooming in mesh WDM optical networks,” IEEE/ACM Trans. Netw., vol. 15, no. 3, pp. 721–733, 2007.
[CrossRef]

F. Palmieri, U. Fiore, S. Ricciardi, “SPARK: a smart parametric online RWA algorithm,” J. Commun. Networks, vol. 9, no. 4, pp. 368–376, 2007.
[CrossRef]

E. A. Doumith, M. Gagnaire, “Impact of traffic predictability on WDM EXC/OXC network performance,” IEEE J. Sel. Areas Commun., vol. 25, no. 5, pp. 895–904, 2007.
[CrossRef]

2006 (2)

S. Huang, R. Dutta, G. N. Rouskas, “Traffic grooming in path, star, and tree networks: complexity, bounds, and algorithms,” IEEE J. Sel. Areas Commun., vol. 24, no. 4, pp. 66–82, 2006.
[CrossRef]

S. Huang, R. Dutta, “Dynamic traffic grooming: the changing role of traffic grooming,” IEEE Commun. Surv. & Tutorials, vol. 8, no. 4, pp. 32–50, 2006.

2005 (1)

W. Yao, B. Ramamurthy, “A link bundled auxiliary graph model for constrained dynamic traffic grooming in WDM mesh networks,” IEEE J. Sel. Areas Commun., vol. 23, no. 8, pp. 1542–1555, 2005.
[CrossRef]

2003 (2)

H. Zhu, H. Zang, K. Zhu, B. Mukherjee, “Dynamic traffic grooming in WDM mesh networks using a novel graph model,” Opt. Networks Mag., vol. 4, no. 3, pp. 65–75, Mar. 2003.

K. Zhu, B. Mukherjee, “A review of traffic grooming in WDM optical networks: architectures and challenges,” Opt. Networks Mag., vol. 4, no. 2, pp. 55–64, Feb. 2003.

2002 (1)

R. Dutta, G. N. Rouskas, “Traffic grooming in WDM networks: past and future,” IEEE Network, vol. 16, no. 6, pp. 46–56, Nov./Dec. 2002.
[CrossRef]

2000 (2)

O. Gerstel, R. Ramaswami, G. Sasaki, “Cost-effective traffic grooming in WDM rings,” IEEE/ACM Trans. Netw., vol. 8, no. 5, pp. 618–630, 2000.
[CrossRef]

A. Chiu, E. Modiano, “Traffic grooming algorithms for reducing electronic multiplexing costs in WDM ring networks,” J. Lightwave Technol., vol. 18, no. 1, pp. 2–12, 2000.
[CrossRef]

Bandyopadhyay, S.

A. Jaekel, A. Bari, Y. Chen, S. Bandyopadhyay, “New techniques for efficient traffic grooming in WDM mesh networks,” in Proc. of IEEE Int. Conf. on Computer Communications and Networks, 2007, pp. 303–308.

Bari, A.

A. Jaekel, A. Bari, Y. Chen, S. Bandyopadhyay, “New techniques for efficient traffic grooming in WDM mesh networks,” in Proc. of IEEE Int. Conf. on Computer Communications and Networks, 2007, pp. 303–308.

Baruffaldi, A.

M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
[CrossRef]

Chen, Y.

A. Jaekel, A. Bari, Y. Chen, S. Bandyopadhyay, “New techniques for efficient traffic grooming in WDM mesh networks,” in Proc. of IEEE Int. Conf. on Computer Communications and Networks, 2007, pp. 303–308.

Chiu, A.

da Fonseca, N. L. S.

A. C. Drummond, N. L. S. da Fonseca, “On-line dynamic traffic grooming algorithms for WDM mesh networks,” in IEEE Int. Conf. on Communications, 2009, pp. 1–5.

Doumith, E. A.

E. A. Doumith, M. Gagnaire, “Impact of traffic predictability on WDM EXC/OXC network performance,” IEEE J. Sel. Areas Commun., vol. 25, no. 5, pp. 895–904, 2007.
[CrossRef]

Drummond, A. C.

A. C. Drummond, N. L. S. da Fonseca, “On-line dynamic traffic grooming algorithms for WDM mesh networks,” in IEEE Int. Conf. on Communications, 2009, pp. 1–5.

Dutta, R.

S. Huang, R. Dutta, G. N. Rouskas, “Traffic grooming in path, star, and tree networks: complexity, bounds, and algorithms,” IEEE J. Sel. Areas Commun., vol. 24, no. 4, pp. 66–82, 2006.
[CrossRef]

S. Huang, R. Dutta, “Dynamic traffic grooming: the changing role of traffic grooming,” IEEE Commun. Surv. & Tutorials, vol. 8, no. 4, pp. 32–50, 2006.

R. Dutta, G. N. Rouskas, “Traffic grooming in WDM networks: past and future,” IEEE Network, vol. 16, no. 6, pp. 46–56, Nov./Dec. 2002.
[CrossRef]

R. Dutta, A. E. Kamal, G. N. Rouskas, Traffic Grooming for Optical Networks: Foundations, Techniques and Frontiers. Springer, 2008.
[CrossRef]

Fiore, U.

F. Palmieri, U. Fiore, S. Ricciardi, “SPARK: a smart parametric online RWA algorithm,” J. Commun. Networks, vol. 9, no. 4, pp. 368–376, 2007.
[CrossRef]

Gagnaire, M.

E. A. Doumith, M. Gagnaire, “Impact of traffic predictability on WDM EXC/OXC network performance,” IEEE J. Sel. Areas Commun., vol. 25, no. 5, pp. 895–904, 2007.
[CrossRef]

Gerstel, O.

O. Gerstel, R. Ramaswami, G. Sasaki, “Cost-effective traffic grooming in WDM rings,” IEEE/ACM Trans. Netw., vol. 8, no. 5, pp. 618–630, 2000.
[CrossRef]

Ho, Q.-D.

Q.-D. Ho, M.-S. Lee, “A zone-based approach for scalable dynamic traffic grooming in large WDM mesh networks,” IEEE J. Lightwave Technol., vol. 25, no. 1, pp. 261–270, 2007.
[CrossRef]

Q.-D. Ho, M.-S. Lee, “Time-efficient near-optimal wavelength assignment in dynamically-reconfigurable WDM networks,” in Proc. of the IEEE Workshop on High Performance Switching and Routing, 2005, pp. 453–456.

Hos, Q.-D.

T.-T. N. Thi, T. T. Minh, Q.-D. Hos, M.-S. Lee, “A time and cost efficient dynamic traffic grooming algorithm for optical mesh networks,” in Proc. of the 2nd Int. IEEE/Create-Net Workshop on Traffic Grooming, 2005, pp. 315–320.

Hu, J.

J. Hu, B. Leida, “Traffic grooming, routing, and wavelength assignment in optical WDM mesh networks,” in Proc. of IEEE INFOCOM, 2004, pp. 1340–1351.

Huang, S.

S. Huang, R. Dutta, “Dynamic traffic grooming: the changing role of traffic grooming,” IEEE Commun. Surv. & Tutorials, vol. 8, no. 4, pp. 32–50, 2006.

S. Huang, R. Dutta, G. N. Rouskas, “Traffic grooming in path, star, and tree networks: complexity, bounds, and algorithms,” IEEE J. Sel. Areas Commun., vol. 24, no. 4, pp. 66–82, 2006.
[CrossRef]

Jaekel, A.

A. Jaekel, A. Bari, Y. Chen, S. Bandyopadhyay, “New techniques for efficient traffic grooming in WDM mesh networks,” in Proc. of IEEE Int. Conf. on Computer Communications and Networks, 2007, pp. 303–308.

Jain, R.

R. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling. Wiley, 1991.

Kamal, A. E.

R. Dutta, A. E. Kamal, G. N. Rouskas, Traffic Grooming for Optical Networks: Foundations, Techniques and Frontiers. Springer, 2008.
[CrossRef]

Lee, M.-S.

Q.-D. Ho, M.-S. Lee, “A zone-based approach for scalable dynamic traffic grooming in large WDM mesh networks,” IEEE J. Lightwave Technol., vol. 25, no. 1, pp. 261–270, 2007.
[CrossRef]

T.-T. N. Thi, T. T. Minh, Q.-D. Hos, M.-S. Lee, “A time and cost efficient dynamic traffic grooming algorithm for optical mesh networks,” in Proc. of the 2nd Int. IEEE/Create-Net Workshop on Traffic Grooming, 2005, pp. 315–320.

Q.-D. Ho, M.-S. Lee, “Time-efficient near-optimal wavelength assignment in dynamically-reconfigurable WDM networks,” in Proc. of the IEEE Workshop on High Performance Switching and Routing, 2005, pp. 453–456.

Leida, B.

J. Hu, B. Leida, “Traffic grooming, routing, and wavelength assignment in optical WDM mesh networks,” in Proc. of IEEE INFOCOM, 2004, pp. 1340–1351.

Liu, H.

H. Liu, F. Tobagi, “Traffic grooming in WDM SONET UPSR rings with multiple line speeds,” in Proc. of IEEE INFOCOM, 2005, pp. 718–729.

Minh, T. T.

T.-T. N. Thi, T. T. Minh, Q.-D. Hos, M.-S. Lee, “A time and cost efficient dynamic traffic grooming algorithm for optical mesh networks,” in Proc. of the 2nd Int. IEEE/Create-Net Workshop on Traffic Grooming, 2005, pp. 315–320.

Modiano, E.

Mukherjee, B.

M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
[CrossRef]

K. Zhu, B. Mukherjee, “A review of traffic grooming in WDM optical networks: architectures and challenges,” Opt. Networks Mag., vol. 4, no. 2, pp. 55–64, Feb. 2003.

H. Zhu, H. Zang, K. Zhu, B. Mukherjee, “Dynamic traffic grooming in WDM mesh networks using a novel graph model,” Opt. Networks Mag., vol. 4, no. 3, pp. 65–75, Mar. 2003.

K. Zhu, B. Mukherjee, “On-line approaches for provisioning connections of different bandwidth granuralities in WDM mesh networks,” in Optical Fiber Communication Conf., 2002, pp. 549–551.

Palmieri, F.

F. Palmieri, U. Fiore, S. Ricciardi, “SPARK: a smart parametric online RWA algorithm,” J. Commun. Networks, vol. 9, no. 4, pp. 368–376, 2007.
[CrossRef]

Pattavina, A.

M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
[CrossRef]

Qiao, C.

C. Xin, C. Qiao, “Performance analysis of multi-hop traffic grooming in mesh WDM optical networks,” in Proc. of the Int. Conf. on Computer Communications and Networks, 2003, pp. 237–242.

Ramamurthy, B.

W. Yao, B. Ramamurthy, “A link bundled auxiliary graph model for constrained dynamic traffic grooming in WDM mesh networks,” IEEE J. Sel. Areas Commun., vol. 23, no. 8, pp. 1542–1555, 2005.
[CrossRef]

Ramaswami, R.

O. Gerstel, R. Ramaswami, G. Sasaki, “Cost-effective traffic grooming in WDM rings,” IEEE/ACM Trans. Netw., vol. 8, no. 5, pp. 618–630, 2000.
[CrossRef]

Ricciardi, S.

F. Palmieri, U. Fiore, S. Ricciardi, “SPARK: a smart parametric online RWA algorithm,” J. Commun. Networks, vol. 9, no. 4, pp. 368–376, 2007.
[CrossRef]

Rouskas, G. N.

S. Huang, R. Dutta, G. N. Rouskas, “Traffic grooming in path, star, and tree networks: complexity, bounds, and algorithms,” IEEE J. Sel. Areas Commun., vol. 24, no. 4, pp. 66–82, 2006.
[CrossRef]

R. Dutta, G. N. Rouskas, “Traffic grooming in WDM networks: past and future,” IEEE Network, vol. 16, no. 6, pp. 46–56, Nov./Dec. 2002.
[CrossRef]

R. Dutta, A. E. Kamal, G. N. Rouskas, Traffic Grooming for Optical Networks: Foundations, Techniques and Frontiers. Springer, 2008.
[CrossRef]

Sasaki, G.

O. Gerstel, R. Ramaswami, G. Sasaki, “Cost-effective traffic grooming in WDM rings,” IEEE/ACM Trans. Netw., vol. 8, no. 5, pp. 618–630, 2000.
[CrossRef]

Thi, T.-T. N.

T.-T. N. Thi, T. T. Minh, Q.-D. Hos, M.-S. Lee, “A time and cost efficient dynamic traffic grooming algorithm for optical mesh networks,” in Proc. of the 2nd Int. IEEE/Create-Net Workshop on Traffic Grooming, 2005, pp. 315–320.

Tobagi, F.

H. Liu, F. Tobagi, “Traffic grooming in WDM SONET UPSR rings with multiple line speeds,” in Proc. of IEEE INFOCOM, 2005, pp. 718–729.

Tornatore, M.

M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
[CrossRef]

Xin, C.

C. Xin, “Blocking analysis of dynamic traffic grooming in mesh WDM optical networks,” IEEE/ACM Trans. Netw., vol. 15, no. 3, pp. 721–733, 2007.
[CrossRef]

C. Xin, “Dynamic traffic grooming in optical networks with wavelength conversion,” IEEE J. Sel. Areas Commun., vol. 25, no. 9, pp. 50–57, 2007.
[CrossRef]

C. Xin, C. Qiao, “Performance analysis of multi-hop traffic grooming in mesh WDM optical networks,” in Proc. of the Int. Conf. on Computer Communications and Networks, 2003, pp. 237–242.

Yao, W.

W. Yao, B. Ramamurthy, “A link bundled auxiliary graph model for constrained dynamic traffic grooming in WDM mesh networks,” IEEE J. Sel. Areas Commun., vol. 23, no. 8, pp. 1542–1555, 2005.
[CrossRef]

Zang, H.

H. Zhu, H. Zang, K. Zhu, B. Mukherjee, “Dynamic traffic grooming in WDM mesh networks using a novel graph model,” Opt. Networks Mag., vol. 4, no. 3, pp. 65–75, Mar. 2003.

Zhu, H.

M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
[CrossRef]

H. Zhu, H. Zang, K. Zhu, B. Mukherjee, “Dynamic traffic grooming in WDM mesh networks using a novel graph model,” Opt. Networks Mag., vol. 4, no. 3, pp. 65–75, Mar. 2003.

Zhu, K.

H. Zhu, H. Zang, K. Zhu, B. Mukherjee, “Dynamic traffic grooming in WDM mesh networks using a novel graph model,” Opt. Networks Mag., vol. 4, no. 3, pp. 65–75, Mar. 2003.

K. Zhu, B. Mukherjee, “A review of traffic grooming in WDM optical networks: architectures and challenges,” Opt. Networks Mag., vol. 4, no. 2, pp. 55–64, Feb. 2003.

K. Zhu, B. Mukherjee, “On-line approaches for provisioning connections of different bandwidth granuralities in WDM mesh networks,” in Optical Fiber Communication Conf., 2002, pp. 549–551.

IEEE Commun. Surv. & Tutorials (1)

S. Huang, R. Dutta, “Dynamic traffic grooming: the changing role of traffic grooming,” IEEE Commun. Surv. & Tutorials, vol. 8, no. 4, pp. 32–50, 2006.

IEEE J. Lightwave Technol. (1)

Q.-D. Ho, M.-S. Lee, “A zone-based approach for scalable dynamic traffic grooming in large WDM mesh networks,” IEEE J. Lightwave Technol., vol. 25, no. 1, pp. 261–270, 2007.
[CrossRef]

IEEE J. Sel. Areas Commun. (5)

C. Xin, “Dynamic traffic grooming in optical networks with wavelength conversion,” IEEE J. Sel. Areas Commun., vol. 25, no. 9, pp. 50–57, 2007.
[CrossRef]

S. Huang, R. Dutta, G. N. Rouskas, “Traffic grooming in path, star, and tree networks: complexity, bounds, and algorithms,” IEEE J. Sel. Areas Commun., vol. 24, no. 4, pp. 66–82, 2006.
[CrossRef]

W. Yao, B. Ramamurthy, “A link bundled auxiliary graph model for constrained dynamic traffic grooming in WDM mesh networks,” IEEE J. Sel. Areas Commun., vol. 23, no. 8, pp. 1542–1555, 2005.
[CrossRef]

E. A. Doumith, M. Gagnaire, “Impact of traffic predictability on WDM EXC/OXC network performance,” IEEE J. Sel. Areas Commun., vol. 25, no. 5, pp. 895–904, 2007.
[CrossRef]

M. Tornatore, A. Baruffaldi, H. Zhu, B. Mukherjee, A. Pattavina, “Holding-time-aware dynamic traffic grooming,” IEEE J. Sel. Areas Commun., vol. 26, no. 3, pp. 28–35, 2008.
[CrossRef]

IEEE Network (1)

R. Dutta, G. N. Rouskas, “Traffic grooming in WDM networks: past and future,” IEEE Network, vol. 16, no. 6, pp. 46–56, Nov./Dec. 2002.
[CrossRef]

IEEE/ACM Trans. Netw. (2)

O. Gerstel, R. Ramaswami, G. Sasaki, “Cost-effective traffic grooming in WDM rings,” IEEE/ACM Trans. Netw., vol. 8, no. 5, pp. 618–630, 2000.
[CrossRef]

C. Xin, “Blocking analysis of dynamic traffic grooming in mesh WDM optical networks,” IEEE/ACM Trans. Netw., vol. 15, no. 3, pp. 721–733, 2007.
[CrossRef]

J. Commun. Networks (1)

F. Palmieri, U. Fiore, S. Ricciardi, “SPARK: a smart parametric online RWA algorithm,” J. Commun. Networks, vol. 9, no. 4, pp. 368–376, 2007.
[CrossRef]

J. Lightwave Technol. (1)

Opt. Networks Mag. (2)

H. Zhu, H. Zang, K. Zhu, B. Mukherjee, “Dynamic traffic grooming in WDM mesh networks using a novel graph model,” Opt. Networks Mag., vol. 4, no. 3, pp. 65–75, Mar. 2003.

K. Zhu, B. Mukherjee, “A review of traffic grooming in WDM optical networks: architectures and challenges,” Opt. Networks Mag., vol. 4, no. 2, pp. 55–64, Feb. 2003.

Other (10)

R. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling. Wiley, 1991.

A. C. Drummond, N. L. S. da Fonseca, “On-line dynamic traffic grooming algorithms for WDM mesh networks,” in IEEE Int. Conf. on Communications, 2009, pp. 1–5.

A. Jaekel, A. Bari, Y. Chen, S. Bandyopadhyay, “New techniques for efficient traffic grooming in WDM mesh networks,” in Proc. of IEEE Int. Conf. on Computer Communications and Networks, 2007, pp. 303–308.

K. Zhu, B. Mukherjee, “On-line approaches for provisioning connections of different bandwidth granuralities in WDM mesh networks,” in Optical Fiber Communication Conf., 2002, pp. 549–551.

H. Liu, F. Tobagi, “Traffic grooming in WDM SONET UPSR rings with multiple line speeds,” in Proc. of IEEE INFOCOM, 2005, pp. 718–729.

J. Hu, B. Leida, “Traffic grooming, routing, and wavelength assignment in optical WDM mesh networks,” in Proc. of IEEE INFOCOM, 2004, pp. 1340–1351.

R. Dutta, A. E. Kamal, G. N. Rouskas, Traffic Grooming for Optical Networks: Foundations, Techniques and Frontiers. Springer, 2008.
[CrossRef]

C. Xin, C. Qiao, “Performance analysis of multi-hop traffic grooming in mesh WDM optical networks,” in Proc. of the Int. Conf. on Computer Communications and Networks, 2003, pp. 237–242.

Q.-D. Ho, M.-S. Lee, “Time-efficient near-optimal wavelength assignment in dynamically-reconfigurable WDM networks,” in Proc. of the IEEE Workshop on High Performance Switching and Routing, 2005, pp. 453–456.

T.-T. N. Thi, T. T. Minh, Q.-D. Hos, M.-S. Lee, “A time and cost efficient dynamic traffic grooming algorithm for optical mesh networks,” in Proc. of the 2nd Int. IEEE/Create-Net Workshop on Traffic Grooming, 2005, pp. 315–320.

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Figures (32)

Fig. 1
Fig. 1

Shortest-path routing versus alternative-path routing.

Fig. 2
Fig. 2

Example of the virtual topology expansion method.

Fig. 3
Fig. 3

Algorithm for Alternative Routing With Virtual Topology Expansion (ARVTE).

Fig. 4
Fig. 4

Algorithm 1 for alternative path routing.

Fig. 5
Fig. 5

Algorithm 2 for alternative path routing.

Fig. 6
Fig. 6

Algorithm 3 for alternative path routing.

Fig. 7
Fig. 7

ILP for minimum path coloring.

Fig. 8
Fig. 8

NSF topology.

Fig. 9
Fig. 9

USA topology.

Fig. 10
Fig. 10

Pan-European topology.

Fig. 11
Fig. 11

Manhattan Street topology.

Fig. 12
Fig. 12

Architecture of an OXC with partial grooming and partial wavelength conversion capabilities.

Fig. 13
Fig. 13

BBR for the AR1, AR2, AR3, and ZWNE algorithms over the network load for the NSF network.

Fig. 14
Fig. 14

BBR for the ARVTE1, AR1, and VTE algorithms over the network load for the NSF network.

Fig. 15
Fig. 15

Jain’s fairness index values for the results of ARVTE1 and AR1 algorithms over the network load for the NSF network.

Fig. 16
Fig. 16

Jain’s fairness index values for the results of ARVTE1 and AR1 algorithms over the network load for the USA network.

Fig. 17
Fig. 17

Jain’s fairness index values for the results of VTE and ZWNE algorithms over the network load for the NSF network.

Fig. 18
Fig. 18

Jain’s fairness index values for the results of VTE and ZWNE algorithms over the network load for the USA network.

Fig. 19
Fig. 19

BBR for the ARVTE1, ZWNE, and SLRC algorithms over the network load for the NSF network.

Fig. 20
Fig. 20

BBR for eight variants of the APR1 algorithm used by the ARVTE1 over the networks load for the NSF network.

Fig. 21
Fig. 21

Comparison among time complexity of SLRC, ZWNE, and ARVTE versus network loads for the NSF network.

Fig. 22
Fig. 22

BBR for the ARVTE and ZWNE algorithms over the network load for the NSF network.

Fig. 23
Fig. 23

BBR for the ARVTE and ZWNE algorithms over the network load for the USA network.

Fig. 24
Fig. 24

BBR for the ARVTE and ZWNE algorithms over the network load for the Pan-European network.

Fig. 25
Fig. 25

BBR for the ARVTE and ZWNE algorithms over the network load for the Manhattan Street network.

Fig. 26
Fig. 26

Jain’s fairness index values for the results of ARVTE and ZWNE algorithms over the network load for the NSF network (top). BBR of each source–destination pair for a load of 28 Erlangs (bottom).

Fig. 27
Fig. 27

Jain’s fairness index values for the results of ARVTE and ZWNE algorithms over the network load for the USA network (top). BBR of each source–destination pair for a load of 31 Erlangs (bottom).

Fig. 28
Fig. 28

Jain’s fairness index values for the results of ARVTE and ZWNE algorithms over the network load for the Pan-European network (top). BBR of each source–destination pair for a load of 19 Erlangs (bottom).

Fig. 29
Fig. 29

Jain’s fairness index values for the results of ARVTE and ZWNE algorithms over the network load for the Manhattan Street network (top). BBR of each source–destination pair for a load of 34 Erlangs (bottom).

Fig. 30
Fig. 30

Lightpath costs of the different networks evaluated resulting from use of the ARVTE and ZWNE algorithms over the network load.

Fig. 31
Fig. 31

BBR for the ARVTE and ZWNE algorithms over the network load for the USA network.

Fig. 32
Fig. 32

Jain’s fairness index values for the results of ARVTE and ZWNE algorithms over the network load for the USA network.

Equations (3)

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c ( l ) = 1 × hc ( l ) + 0.1 × gp ( l ) + 0.01 × wc ( l ) .
f ( x 1 , x 2 , , x n ) = ( i = 1 n x i ) 2 n i = 1 n x i 2 .
c 2 ( l ) = { c ( l ) if groomable lightpath α × c ( l ) if new lightpath   ( α > 1 ) } .