Abstract

We propose resource orchestration schemes in overlay networks enabled by optical network virtualization. Based on the information from underlying optical networks, our proposed schemes provision the fewest data centers to guarantee K-connect survivability, thus maintaining resource availability for cloud applications under any failure.

© 2013 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. S. C. O. P. E. Alliance, “Telecom grade cloud computing,” www.scope-alliance.org (2011).
  2. J. He, “Software-defined transport network for cloud computing,” in Optical Fiber Communication Conference/National Fiber Optic Engineers Conference 2013, OSA Technical Digest (online) (Optical Society of America, 2013), paper OTh1H.6.
    [CrossRef]
  3. G. Wang, T. S. Eugene Ng, and A. Shaikh, “Programming your network at run-time for big data applications,” in Proceedings of the First Workshop on Hot Topics in Software Defined Networks (HotSDN '12). (ACM, 2012), pp. 103–108.
    [CrossRef]
  4. Y. Zhu, M. Ammar, “Algorithms for assigning substrate network resources to virtual network components,” 25th IEEE International Conference on Computer Communications. Proceedings, April 2006.
    [CrossRef]
  5. C. Develder, J. Buysse, A. Shaikh, B. Jaumard, M. De Leenheer, and B. Dhoedt, “Survivable optical grid dimensioning: anycast routing with server and network failure protection,” 2011 IEEE International Conference on Communications, 5–9 June 2011.
    [CrossRef]
  6. Q. Zhang, W. Xie, Q. She, X. Wang, P. Palacharla, and M. Sekiya, “RWA for network virtualization in optical WDM networks,” in Optical Fiber Communication Conference/National Fiber Optic Engineers Conference 2013, OSA Technical Digest (online) (Optical Society of America, 2013), paper JTh2A.65.
    [CrossRef]
  7. Q. Zhang, Q. She, Y. Zhu, X. Wang, P. Palacharla, and M. Sekiya, “Survivable resource orchestration for optically interconnected data center networks,” in 39th European Conference and Exhibition on Optical Communication (ECOC 2013), 22–26 Sept. 2013.
  8. D. Simeonidou, R. Nejabati, M. P. Channegowda, “Software-defined optical networks technology and infrastructure: enabling software-defined optical network operations [Invited],” J. Opt. Commun. Netw. 5(10), A274–A282 (2013).
    [CrossRef]
  9. A. L. Chiu, G. Choudhury, G. Clapp, R. Doverspike, J. W. Gannett, J. G. Klincewicz, R. A. Guangzhi Li, J. Skoog, A. Strand, Von Lehmen, Dahai Xu, “Network design and architectures for highly dynamic next-generation IP-over-optical long distance networks,” J. Lightwave Technol. 27(12), 1878–1890 (2009).
    [CrossRef]

2013 (1)

2009 (1)

Ammar, M.

Y. Zhu, M. Ammar, “Algorithms for assigning substrate network resources to virtual network components,” 25th IEEE International Conference on Computer Communications. Proceedings, April 2006.
[CrossRef]

Channegowda, M. P.

Chiu, A. L.

Choudhury, G.

Clapp, G.

Dahai Xu,

Doverspike, R.

Gannett, J. W.

Guangzhi Li, R. A.

Klincewicz, J. G.

Nejabati, R.

Simeonidou, D.

Skoog, J.

Strand, A.

Von Lehmen,

Zhu, Y.

Y. Zhu, M. Ammar, “Algorithms for assigning substrate network resources to virtual network components,” 25th IEEE International Conference on Computer Communications. Proceedings, April 2006.
[CrossRef]

J. Lightwave Technol. (1)

J. Opt. Commun. Netw. (1)

Other (7)

S. C. O. P. E. Alliance, “Telecom grade cloud computing,” www.scope-alliance.org (2011).

J. He, “Software-defined transport network for cloud computing,” in Optical Fiber Communication Conference/National Fiber Optic Engineers Conference 2013, OSA Technical Digest (online) (Optical Society of America, 2013), paper OTh1H.6.
[CrossRef]

G. Wang, T. S. Eugene Ng, and A. Shaikh, “Programming your network at run-time for big data applications,” in Proceedings of the First Workshop on Hot Topics in Software Defined Networks (HotSDN '12). (ACM, 2012), pp. 103–108.
[CrossRef]

Y. Zhu, M. Ammar, “Algorithms for assigning substrate network resources to virtual network components,” 25th IEEE International Conference on Computer Communications. Proceedings, April 2006.
[CrossRef]

C. Develder, J. Buysse, A. Shaikh, B. Jaumard, M. De Leenheer, and B. Dhoedt, “Survivable optical grid dimensioning: anycast routing with server and network failure protection,” 2011 IEEE International Conference on Communications, 5–9 June 2011.
[CrossRef]

Q. Zhang, W. Xie, Q. She, X. Wang, P. Palacharla, and M. Sekiya, “RWA for network virtualization in optical WDM networks,” in Optical Fiber Communication Conference/National Fiber Optic Engineers Conference 2013, OSA Technical Digest (online) (Optical Society of America, 2013), paper JTh2A.65.
[CrossRef]

Q. Zhang, Q. She, Y. Zhu, X. Wang, P. Palacharla, and M. Sekiya, “Survivable resource orchestration for optically interconnected data center networks,” in 39th European Conference and Exhibition on Optical Communication (ECOC 2013), 22–26 Sept. 2013.

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (9)

Fig. 1
Fig. 1

Communication patterns among distributed DCs. (a) Aggregation. (b) A sequence of aggregations.

Fig. 2
Fig. 2

An overlay framework for distributed DCs.

Fig. 3
Fig. 3

Cloud requests. (a) Basic request. (b) 2-connect separate protection. (c) 2-connect by joint protection.

Fig. 4
Fig. 4

Overlay network.

Fig. 5
Fig. 5

(a) Request A. (b) Request B. (c) VM allocation for requests on an overlay network.

Fig. 6
Fig. 6

Performance as K increases (N = 10). (a) Average of the least M required vs. K. (b) Average delay per request vs. K. (c) Request blocking ratio vs. K.

Fig. 7
Fig. 7

Performance as N increases (K = 4). (a) Average of the least M required vs. N. (b) Average delay per request vs. N. (c) Request blocking ratio vs. N.

Fig. 8
Fig. 8

VM allocation as K increases (N = 10). (a)Average VMs per request vs. K. (b) % of VM reduction vs. K.

Fig. 9
Fig. 9

VM allocation as N increases (K = 4). (a)Average VMs per request vs. N. (b) % of VM reduction vs. N.

Tables (1)

Tables Icon

Table 1 Matrices for DC1

Metrics