Improving Network I/O Virtualization Performance of Xen Hypervisor

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-11 Number-2                          
Year of Publication : 2014
Authors : Shikha R. Thakur , R. M. Goudar


Shikha R. Thakur , R. M. Goudar. "Improving Network I/O Virtualization Performance of Xen Hypervisor", International Journal of Engineering Trends and Technology (IJETT), V11(2),79-83 May 2014. ISSN:2231-5381. published by seventh sense research group


Virtualization technology is the backbone of Cloud Computing. Virtualization provides efficiency, flexibility and scalability in cloud computing. Virtualization in cloud computing can be done through different virtualization platform such as VMware, Kvm, UMLinux, VirtualBox, Xen. Xen is an open source hypervisor; a virtualization tool for cloud computing that is widely used among cloud providers. Since, Xen yields poor throughput for network I/O virtualization. To overcome this problem; number of hardware and software enhancement solutions are proposed. Packet aggregation mechanism is one of the solutions that can improve the performance of driver domain based model of Xen. Packet aggregation mechanism results in increased throughput at a cost of maximized packet delay and jitter. Here is the proposed self-adaptive buffering jitter control mechanism that dynamically tunes the aggregation to achieve best trade-off between throughput and delay. It finds the mean release time of a container according to dynamic traffic load. Thus, an aggregated model of Xen would improve performance resulting in strong foundation of virtualization for cloud providers.


[1] GManel Bourguiba, Kamel Haddadou, Ines El Korbi, Guy Pujolle, "Improving Network I/O Virtualization for Cloud Computing," IEEE Transactions on Parallel and Distributed Systems, 25 Feb. 2013.
[2] M. Bourguiba, K. Haddadou, and G. Pujolle, ”Packet Aggregation Based Network I/O Virtualization for Cloud Computing”,Elsevier Computer Communications, Vol. 35, no. 3, pp 309-319,2012.
[3] David Hay , Gabriel Scalosub,” Jitter regulation for multiple streams”, 13th Annual European Symposium on Algorithms,2005.
[4] S. Gamage, A. Kangarlou, R. Kompella, and D. Xu, ”Opportunistic Flooding to Improve TCP Transmit Performance in Virtualized Clouds”, Proc. ACM Symp. Cloud Computing (SOCC’ 11), 2011.
[5] K.K Ram, J.R. Santos, Y. Turner, A.L Cox, and S. Rixner, ”Achieving 10Gb/s using safe and transparent Network Interface Virtualization”, Proc. ACM SIGPLAN/SIGOPS Conf. Virtual Execution Environments (VEE’ 09), 2009.
[6] V. Ramaswami, ”From the matrix-geometric to the matrix exponential”, Queueing Systems Theory Appl., vol. 6, pp. 229- 260, June 1990.
[7] M. Dobrescu, N. Egi, K. Argyraki, B.G. Chun, K. Fall, G. Iannaccone, A. Knies, M. Manesh, and S. Ratnasamy, Routebricks : exploiting parallelism to scale software routers, Proc. ACM SIGOPS Symp. Operating systems principles (SOSP 09), 2009.
[8] P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho, R.Neugebauer, I.Pratt, and A. Warfield, ”Xen and the art of virtualization”, Proc. ACM Symp. Operating Systems Principles (SOSP’ 03), Oct. 2003.
[9] Xing Pu , Ling Liu , Yiduo Mei , Sankaran Sivathanu , Younggyun Koh , Calton Pu, Understanding Performance Interference of I/O Workload in Virtualized Cloud Environments, Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing, p.51-58, July 05-10, 2010.
[10] Mukil Kesavan , Ada Gavrilovska , Karsten Schwan, Differential virtual time (DVT): rethinking I/O service differentiation for virtual machines, Proceedings of the 1st ACM symposium on Cloud computing, June 10-11, 2010.
[11] K. Fraser, S. Hand, R. Neugebauer, I. Pratt, A. Warfield, M. Williams, Safe hardware Access with the Xen virtual machine monitor, in: Proceedings of the First Workshop on Operating System and Architectural Support for the on Demand IT Infrastructure, OASIS 2004.
[12] Jeremy Sugerman , Ganesh Venkitachalam , Beng-Hong Lim, Virtualizing I/O Devices on VMware Workstation`s Hosted Virtual Machine Monitor, Proceedings of the General Track: 2002 USENIX Annual Technical Conference, p.1-14, June 25-30, 2001.
[13] X. Zhang, and Y. Dong, ”Optimizing Xen VMM based on Intel Virtualization technology”, Proc. International Conference on Computer Science and Software Engineering, 2008.
[14] Scot Rixner, Network Virtualization: Breaking the Performance Barrier, Queue, v.6 n.1, January/February 2008.
[15] Paul Barham , Boris Dragovic , Keir Fraser , Steven Hand , Tim Harris , Alex Ho , Rolf Neugebauer , Ian Pratt , Andrew Warfield, Xen and the art of virtualization, Proceedings of the nineteenth ACM symposium on Operating systems principles, October 19-22, 2003.
[16] Yiduo Mei , Ling Liu , Xing Pu , Sankaran Sivathanu, Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud, Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing, p.59-66, July 05-10, 2010.
[17] Scot Rixner, Network Virtualization: Breaking the Performance Barrier, Queue, v.6 n.1, January/February 2008.
[18] A. Menon, and W. Zwaenepoel, ”Optimizing TCP Receive Performance”, Proc. USENIX Annual Technical Conference (USENIX’ 08), 2008.
[19] J. Wang, K. Wright, and K. Gopalan, ”XenLoop: A Transparent High Performance Inter-vm Network LoopBack”, Proc. ACM Symp. High Performnce Parrallel and Distributed Computing (HPDC’08), 2008.
[20] Yaozu Dong, Dongxiao Xu, Yang Zhang, Guangdeng Liao, ”Optimizing Network I/O Virtualization with Efficient Interrupt Coalescing and Virtual Receive Side Scaling ”, Proc. IEEE International conference on cluster Computing, p.26-34, Sept. 26-30, 2011.
[21] Ramjee, R. Dept. of Comput. Sci., Massachusetts Univ., MA, USA Kurose, J. Towsley, D. Schulzrinne, Henning “Adaptive playout mechanisms for packetized audio applications in wide-area networks”, INFOCOM `94. Networking for Global Communications., 13th Proceedings IEEE, Page(s): 680 - 688 vol.2, 1994.

Xen, Network I/O virtualization, Cloud Computing, Packet aggregation, Delay and jitter, Adaptive buffering.