Survivable virtual infrastructure mapping in virtualized data centers

Jielong Xu, Jian Tang, Kevin Kwiat, Weiyi Zhang, Guoliang Xue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

51 Citations (Scopus)

Abstract

In a virtualized data center, survivability can be enhanced by creating redundant Virtual Machines (VMs) as backup for VMs such that after VM or server failures, affected services can be quickly switched over to backup VMs. To enable flexible and efficient resource management, we propose to use a service-aware approach in which multiple correlated VMs and their backups are grouped together to form a Survivable Virtual Infrastructure (SVI) for a service or a tenant. A fundamental problem in such a system is to determine how to map each SVI to a physical data center network such that operational costs are minimized subject to the constraints that each VM's resource requirements are met and bandwidth demands between VMs can be guaranteed before and after failures. This problem can be naturally divided into two sub-problems: VM Placement(VMP) and Virtual Link Mapping (VLM). We present a general optimization framework for this mapping problem. Then we present an efficient algorithm for the VMP sub problem as well as a polynomial-time algorithm that optimally solves the VLM sub problem, which can be used as subroutines in the framework. We also present an effective heuristic algorithm that jointly solves the two sub problems. It has been shown by extensive simulation results based on the real VM data traces collected from the green data center at Syracuse University that compared with the First Fit Descending (FFD) and single shortest path based baseline algorithm, both our VMP+VLM algorithm and joint algorithm significantly reduce the reserved bandwidth, and yield comparable results in terms of the number of active servers.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
Pages196-203
Number of pages8
DOIs
StatePublished - 2012
Event2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012 - Honolulu, HI, United States
Duration: Jun 24 2012Jun 29 2012

Other

Other2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
CountryUnited States
CityHonolulu, HI
Period6/24/126/29/12

Fingerprint

Servers
Bandwidth
Virtual machine
Subroutines
Heuristic algorithms
Polynomials
Costs

Keywords

  • Cloud computing
  • data center
  • service-aware
  • survivability
  • virtual machine management

ASJC Scopus subject areas

  • Software

Cite this

Xu, J., Tang, J., Kwiat, K., Zhang, W., & Xue, G. (2012). Survivable virtual infrastructure mapping in virtualized data centers. In Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012 (pp. 196-203). [6253506] https://doi.org/10.1109/CLOUD.2012.100

Survivable virtual infrastructure mapping in virtualized data centers. / Xu, Jielong; Tang, Jian; Kwiat, Kevin; Zhang, Weiyi; Xue, Guoliang.

Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012. 2012. p. 196-203 6253506.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Xu, J, Tang, J, Kwiat, K, Zhang, W & Xue, G 2012, Survivable virtual infrastructure mapping in virtualized data centers. in Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012., 6253506, pp. 196-203, 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012, Honolulu, HI, United States, 6/24/12. https://doi.org/10.1109/CLOUD.2012.100
Xu J, Tang J, Kwiat K, Zhang W, Xue G. Survivable virtual infrastructure mapping in virtualized data centers. In Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012. 2012. p. 196-203. 6253506 https://doi.org/10.1109/CLOUD.2012.100
Xu, Jielong ; Tang, Jian ; Kwiat, Kevin ; Zhang, Weiyi ; Xue, Guoliang. / Survivable virtual infrastructure mapping in virtualized data centers. Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012. 2012. pp. 196-203
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