Dynamic memory balancing for virtual machines

Abstract

Virtualization essentially enables multiple operating systems and applications to run on one physical computer by multiplexing hardware resources. A key motivation for applying virtualization is to improve hardware resource utilization while maintaining reasonable quality of service. However, such a goal cannot be achieved without efficient resource management. Though most physical resources, such as processor cores and I/O devices, are shared among virtual machines using time slicing and can be scheduled flexibly based on priority, allocating an appropriate amount of main memory to virtual machines is more challenging. Different applications have different memory requirements. Even a single application shows varied working set sizes during its execution. An optimal memory management strategy under a virtualized environment thus needs to dynamically adjust memory allocation for each virtual machine, which further requires a prediction model that forecasts its host physical memory needs on the fly. This paper introduces MEmory Balancer (MEB) which dynamically monitors the memory usage of each virtual machine, accurately predicts its memory needs, and periodically reallocates host memory. MEB uses two effective memory predictors which, respectively, estimate the amount of memory available for reclaiming without a notable performance drop, and additional memory required for reducing the virtual machine paging penalty. Our experimental results show that our prediction schemes yield high accuracy and low overhead. Furthermore, the overall system throughput can be significantly improved with MEB.

References

1. Jikes RVM. URL http://www.jikesrvm.org/.
2. SPEC CPU2000, a. URL http://www.spec.org/cpu2000.
3. SPECweb2005, b. URL http://www.spec.org/web2005.
4. Bowen Alpern et al. The Jalapeño virtual machine. IBM Systems Journal, 39(1):211--238, February 2000.
5. Bowen Alpern et al. Implementing Jalapeño in Java. In OOPSLA '99: Proceedings of the 14th annual ACM SIGPLAN conference on Object-Oriented Programing, Systems, Languages, and Applications, pages 314--324, Denver, CO, November 1999.
6. V. Application. Intel 64 and IA-32 architecture software developer's manual, 2006. URL citeseer.ist.psu.edu/484264.html
7. M. Arnold, S.J. Fink, D. Grove, M. Hind, and P. Sweeney. Adaptive optimization in the Jalape¿no JVM. In OOPSLA '00: Proceedings of the 15th annual ACM SIGPLAN conference on Object-Oriented Programing, Systems, Languages, and Applications, pages 47--65, Minneapolis, MN, October 2000.
8. Paul Barham, Boris Dragovic, Keir Fraser, Steven Hand, Tim Harris, Alex Ho, Rolf Neugebauer, Ian Pratt, and Andrew Warfield. Xen and the art of virtualization. SIGOPS Oper. Syst. Rev., 37(5):164--177, 2003. ISSN 0163-5980. doi: http://doi.acm.org/10.1145/1165389.945462.
9. S.M. Blackburn, R. Garner, C. Hoffman, A.M. Khan, K.S. McKinley, R. Bentzur, A. Diwan, D. Feinberg, D. Frampton, S.Z. Guyer, M. Hirzel, A. Hosking, M. Jump, H. Lee, J.E.B. Moss, A. Phansalkar, D. Stefanović, T. VanDrunen, D. von Dincklage, and B. Wiedermann. The DaCapo benchmarks: Java benchmarking development and analysis. In OOPSLA '06: Proceedings of the 21st annual ACM SIGPLAN conference on Object-Oriented Programing, Systems, Languages, and Applications, pages 169--190, New York, NY, USA, October 2006. ACM Press. doi: http://doi.acm.org/10.1145/1167473.1167488
10. Dhruba Chandra, Fei Guo, Seongbeom Kim, and Yan Solihin. Predicting inter-thread cache contention on a chip multi-processor architecture. In HPCA '05: Proceedings of the 11th International Symposium on High-Performance Computer Architecture, pages 340--351,Washington, DC, USA, 2005. IEEE Computer Society. ISBN 0-7695-2275-0. doi: http://dx.doi.org/10.1109/HPCA.2005.27.
11. Stephen T. Jones, Andrea C. Arpaci-Dusseau, and Remzi H. Arpaci-Dusseau. Geiger: monitoring the buffer cache in a virtual machine environment. SIGOPS Oper. Syst. Rev., 40(5):14--24, 2006. ISSN 0163-5980. doi: http://doi.acm.org/10.1145/1168917.1168861.
12. Pin Lu and Kai Shen. Virtual machine memory access tracing with hypervisor exclusive cache. In ATC'07: 2007 USENIX Annual Technical Conference on Proceedings of the USENIX Annual Technical Conference, pages 1--15, Berkeley, CA, USA, 2007. USENIX Association. ISBN 999-8888-77-6.
13. Chi-Keung Luk, Robert Cohn, Robert Muth, Harish Patil, Artur Klauser, Geoff Lowney, Steven Wallace, Vijay Janapa Reddi, and Kim Hazelwood. Pin: building customized program analysis tools with dynamic instrumentation. In PLDI '05: Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation, pages 190--200, New York, NY, USA, 2005. ACM Press. ISBN 1-59593-056-6. doi: http://doi.acm.org/10.1145/1065010.1065034. Dan Magenheimer. Memory overcommit. . . without the commitment, 2008
14. R.L. Mattson, J. Gecsei, D. Slutz, and I.L. Traiger. Evaluation techniques for storage hierarchies. IBM System Journal, 9(2):78--117, 1970.
15. R.A. Sugumar and S.G. Abraham. Efficient simulation of caches under optimal replacement with applications to miss characterization. In SIGMETRICS '93: Proceedings of the 1993 ACM SIGMETRICS Conference on Measurement&Modeling Computer Systems, pages 24--35, May 1993.
16. Carl A.Waldspurger. Memory resource management in vmware esx server. SIGOPS Oper. Syst. Rev., 36(SI):181--194, 2002. ISSN 0163-5980. doi: http://doi.acm.org/10.1145/844128.844146.
17. Timothy Wood, Prashant Shenoy, and Arun. Black-box and gray-box strategies for virtual machine migration. pages 229--242. URL http://www.usenix.org/events/nsdi07/tech/wood.html.
18. T. Yang, E. Berger, M. Hertz, S. Kaplan, and J. Moss. Automatic heap sizing: Taking real memory into account, 2004. URL citeseer.ist.psu.edu/article/yang04automatic.html.
19. Ting Yang, Emery D. Berger, Scott F. Kaplan, and J. Eliot B. Moss. CRAMM: virtual memory support for garbage-collected applications. In OSDI '06: Proceedings of the 7th symposium on Operating systems design and implementation, pages 103--116, Berkeley, CA, USA, 2006. USENIX Association. ISBN 1-931971-47-1.
20. Pin Zhou, Vivek Pandey, Jagadeesan Sundaresan, Anand Raghuraman, Yuanyuan Zhou, and Sanjeev Kumar. Dynamic tracking of page miss ratio curve for memory management. In ASPLOS-XI: Proceedings of the 11th international conference on Architectural support for programming languages and operating systems, pages 177--188, New York, NY, USA, 2004. ACM. ISBN 1-58113-804-0. doi: http://doi.acm.org/10.1145/1024393.1024415.

Index Terms

• General and reference

  • Cross-computing tools and techniques

    • Performance

• Software and its engineering

  • Software organization and properties

    • Extra-functional properties

      • Software performance