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VRAS: A Lightweight Local Resource Allocation System for Virtual Machine Monitor

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Abstract

Traditional computing resource allocations in virtualization environment devote to provide fairness of resource distribution when the overall workload of host is heavy. That makes those allocations lack of efficiency under light workloads. To target this, we design and implement a lightweight resource allocation system, virtual resource allocation system (VRAS). Considering the fact that workloads can be balanced by migrating virtual machines to other hosts, we propose a request driven mechanism to focus on resource allocation under light workloads. We also present some allocation strategies used in VRAS to explain how it works on processor and memory resources. Our experiment results demonstrate that VRAS can result in throughput improvements of 28 % for RUBiS application, and the network overhead reduction of 81 %, comparing with the traditional allocation methods.

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References

  1. Smith, J. E., & Nair, R. (2005). The architecture of virtual machines. IEEE Computer, 38(5), 32–38.

    Article  Google Scholar 

  2. Rosenblum, M., & Garfinkel, T. (2005). Virtual machine monitors: Current technology and future trends. IEEE Computer, 38(5), 39–47.

    Article  Google Scholar 

  3. Wang, X., Sang, Y., Liu, Y., & Luo, Y. (2011). Considerations on security and trust measurement for virtualized environment. Journal of Convergence (JoC), 2(2), 19–24.

    Google Scholar 

  4. Luo, H., & Shyu, M. L. (2011). Quality of service provision in mobile multimedia—A survey. Human-centric Computing and Information Sciences (HCIS), 1, 5. doi:10.1186/2192-1962-1-5.

    Article  Google Scholar 

  5. Xie, X., Jiang, H., Jin, H., Cao, W., Yuan, P., & Yang, L. T. (2012). Metis: A profiling toolkit based on the virtualization of hardware performance counters. Human-centric Computing and Information Sciences (HCIS), 2, 8. doi:10.1186/2192-1962-2-8.

    Article  Google Scholar 

  6. Nelson, M., Lim, B. H., & Hutchins, G. (2005). Fast transparent migration for virtual achines. Proceedings of the 2005 USENIX annual technical conference (USENIX 2005) (pp. 391–394). Anaheim, USA.

  7. Clark, C., Fraser, K., Hand, S., Hanseny, J. G., July, E., & Limpach, C., et al. (2005). Live migration of virtual machines. Proceedings of the 2nd ACM/USENIX symposium on networked systems design and implementation (NSDI 2005), 2 (pp. 273–286). Boston, USA.

  8. Abdelzaher, T., & Lu, C. (2000). Modeling and performance control of internet servers. Proceedings of the 39th IEEE conference on decision and control (ICDC 2000), 3 (pp. 2234–2239). Sydney, Australia.

  9. Anderson, M., Kihl, M., & Robertsson, A. (2003). Modeling and design of admission control mechanisms for web servers using non-linear control theory. Proceedings of the conference on performance and control of next-generation communication networks (ITCom 2003), 5244 (pp. 53–64). Orlando, USA.

  10. Lu, C., Abdelzaher, T. F., Stankovic, J., & Son, S. (2001). A feedback control approach for guaranteeing relative delays in web servers. Proceedings of the 7th IEEE real-time technology and applications symposium, 51–62, Taipei.

  11. Diao, Y., Gandhi, N., Hellerstein, J. L., Parekh, S., & Tilbury, D. M. (2002). Mimo control of an apache web server: Modeling and controller design. Proceedings of the 2002 American control conference (ACC 2002), 6 (pp. 4922–4927). Minneapolis, USA.

  12. Goel, N., & Shyamasundar, R. K. (2012). An executional framework for BPMN using Orc. Journal of Convergence (JoC), 3(1), 29–36.

    Google Scholar 

  13. Braham, P., Draconic, B., Fraser, K., Hand, S., Harris, T., & Ho, A., et al. (2003). Xen and the art of virtualization. Proceedings of the 19th ACM symposium on operating systems principles (SOSP 2003, 37(5) (pp. 164–177). New York, USA.

  14. Whitaker, A., Shaw, M., & Gribble, S. D. (2002). Scale and performance in the denali isolation kernel. Proceedings of the 5th symposium on operating systems design and implementation (OSDI 2002), 36 (pp. 195–209). Boston, USA.

  15. Liu, X., Zhu, X., Singhal, S., & Arlitt, M. (2005). Adaptive entitlement control of resource partitions on shared servers. Proceedings of the 9th IFIP/IEEE international symposium on integrated network management (IM 2005) (pp. 163–176). Nice, France.

  16. Wang, Z., Zhu, X., & Singhal, S. (2005). Utilization and slo-based control for dynamic sizing of resource partitions. Proceedings of the 16th IFIP/IEEE international workshop on distributed system: Operations and management (DSOM 2005), 3775 (pp. 133–144). Barcelona, Spain.

  17. Zhu, X., Wang, Z., & Singhal, S. (2006). Utility driven workload management using nested control design. Proceedings of the 2002 American control conference (ACC 2006) (pp. 6033–6038). Minneapolis, USA.

  18. Padala, P., Shin, K., Zhu, X., Uysal, M., Wang, Z., Singhal, S., et al. (2007). Adaptive control of virtualized resources in utility computing environments. Proceedings of the 2nd ACM SIGOPS/EuroSys European conference on computer systems 2007(EuroSys 2007, 41(3) (pp. 289–302). Lisbon, Portugal.

  19. Zhang, Y., Bestavros, A., Guirguis, M., Matta, I., & West, R. (2005). Friendly virtual machines: Leveraging a feedback-control model for application adaptation. Proceedings of the 1st ACM/USENIX international conference on virtual execution environments (VEE 2005) (pp. 2–12). Chicago, USA.

  20. Qian, H., Miller, E., Zhang, W., Rabinovich, M., & Wills, C. E. (2007). Agility in virtualized utility computing. Proceedings of the 3rd international workshop on virtualization technology in distributed computing (VTDC 2007) (pp. 1–8). Reno, USA.

  21. Wood, T., Shenoy, P., Venkataramani, A., & Yousif, M. (2007). Black-box and gray-box strategies for virtual machine migration. Proceedings of the 4th USENIX symposium on networked systems design and implementation (NSDI 2007) (pp. 229–242). Cambridge, USA.

  22. Cherkasova, L., Gupta, D., & Vahdat, A. (2007). Comparison of the three CPU schedulers in Xen. ACM SIGMETRICS Performance Evaluation Review, 35(2), 42–51.

    Article  Google Scholar 

  23. Credit Scheduler. http://wiki.xensource.com/xenwiki/CreditScheduler

  24. Waldspurger, C. A. (2002). Memory resource management in VMware ESX Server. Proceedings of the 5th symposium on operating systems design and implementation (OSDI 2002), 36 (pp. 181–194). Boston, USA.

  25. Shi, X., Tan, H., Wu, S., & Jin, H. (2008). VNIX: Managing virtual machines on clusters. Proceedings of Japan-China joint workshop on frontier of computer science and technology (FCST 2008) (pp. 155–162). Nagasahi, Japan.

  26. Super PI. http://www.superpi.net

  27. RUBiS. http://rubis.ow2.org

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Acknowledgments

The research is supported by National Science Foundation of China under Grant No. 61073024 and 61232008. It is also supported by National 863 Hi-Tech Research and Development Program under Grant No. 2013AA01A213, Outstanding Youth Foundation of Hubei Province under Grant No. 2011CDA086S, and Guangzhou Science and Technology Program under Grant 2012Y2-00040.

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Authors and Affiliations

  1. Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Hai Jin, Wei Gao, Song Wu & Xuanhua Shi

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  1. Hai Jin
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  2. Wei Gao
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  3. Song Wu
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  4. Xuanhua Shi
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Correspondence to Hai Jin.

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Jin, H., Gao, W., Wu, S. et al. VRAS: A Lightweight Local Resource Allocation System for Virtual Machine Monitor. Wireless Pers Commun 73, 1513–1528 (2013). https://doi.org/10.1007/s11277-013-1263-0

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  • DOI: https://doi.org/10.1007/s11277-013-1263-0

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