Abstract
The promotion of distributed Cloud Computing infrastructures as the next platform to deliver the Utility Computing paradigm, leads to new virtual machines (VMs) scheduling algorithms leveraging peer-to-peer approaches. Although these proposals considerably improve the scalability, leading to the management of hundreds of thousands of VMs over thousands of physical machines (PMs), they do not consider the network overhead introduced by multi-site infrastructures. This overhead can have a dramatic impact on the performance if there is no mechanism favoring intra-site v.s. inter-site manipulations.
This paper introduces a new building block designed on top of a network with Vivaldi coordinates maximizing the locality criterion (i.e., efficient collaborations between PMs). We combined such a mechanism with DVMS, a large-scale virtual machine scheduler and showed its benefit by discussing several experiments performed on four distinct sites of the Grid’5000 testbed. With our proposal and without changing the scheduling decision algorithm, the number of inter-site operations has been reduced by 72%. This result provides a glimpse of the promising future of using locality properties to improve the performance of massive distributed Cloud platforms.
Chapter PDF
Similar content being viewed by others
References
Barbagallo, D., Di Nitto, E., Dubois, D.J., Mirandola, R.: A Bio-inspired Algorithm for Energy Optimization in a Self-Organizing Data Center. In: Weyns, D., Malek, S., de Lemos, R., Andersson, J. (eds.) SOAR 2009. LNCS, vol. 6090, pp. 127–151. Springer, Heidelberg (2010)
Dabek, F., Cox, R., Kaashoek, M.F., Morris, R.: Vivaldi: A Decentralized Network Coordinate System. In: 2004 Conf. on Applications, Technologies, Architectures, and Protocols for Computer Comm. SIGCOMM 2004, pp. 15–26 (2004)
Feller, E., Morin, C., Esnault, A.: A Case for Fully Decentralized Dynamic VM Consolidation in Clouds. In: CloudCom 2012: 4th IEEE International Conference on Cloud Computing Technology and Science (December 2012)
Feller, E., Rilling, L., Morin, C.: Snooze: A Scalable and Autonomic Virtual Machine Management Framework for Private Clouds. In: CCGRID 2012: 12th Int. Symp. on Cluster, Cloud and Grid Comp, pp. 482–489 (May 2012)
Garcés-Erice, L., Biersack, E.W., Ross, K.W., Felber, P., Urvoy-Keller, G.: Hierarchical Peer-To-Peer Systems. Parallel Processing Letters 13(4), 643–657 (2003)
Greenberg, A., Hamilton, J., Maltz, D.A., Patel, P.: The Cost of a Cloud: Research Problems in Data Center Networks. SIGCOMM Comput. Commun. Rev. 39(1), 68–73 (2008)
Hermenier, F., Demassey, S., Lorca, X.: Bin Repacking Scheduling in Virtualized Datacenters. In: Lee, J. (ed.) CP 2011. LNCS, vol. 6876, pp. 27–41. Springer, Heidelberg (2011)
Hermenier, F., Lawall, J., Muller, G.: BtrPlace: A Flexible Consolidation Manager for Highly Available Applications. IEEE Transactions on Dependable and Secure Computing 99 (2013) (PrePrints)
Jelasity, M., Babaoglu, O.: T-Man: Gossip-based Overlay Topology Management. In: Brueckner, S.A., Di Marzo Serugendo, G., Hales, D., Zambonelli, F. (eds.) ESOA 2005. LNCS (LNAI), vol. 3910, pp. 1–15. Springer, Heidelberg (2006)
Marzolla, M., Babaoglu, O., Panzieri, F.: Server consolidation in Clouds through gossiping. In: WoWMoM 2011: Proceedings of the 12th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, pp. 1–6. IEEE Computer Society, Washington, DC (2011)
Mastroianni, C., Meo, M., Papuzzo, G.: Self-economy in cloud data centers: Statistical assignment and migration of virtual machines. In: Jeannot, E., Namyst, R., Roman, J. (eds.) Euro-Par 2011, Part I. LNCS, vol. 6852, pp. 407–418. Springer, Heidelberg (2011)
Quesnel, F., Lebre, A., Pastor, J., Sudholt, M., Balouek, D.: Advanced Validation of the DVMS Approach to Fully Distributed VM Scheduling. In: ISPA 2013: 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, pp. 1249–1256 (July 2013)
Quesnel, F., Lèbre, A., Südholt, M.: Cooperative and Reactive Scheduling in Large-Scale Virtualized Platforms with DVMS. Concurrency and Computation: Practice and Experience 25(12), 1643–1655 (2013)
Rouzaud-Cornabas, J.: A Distributed and Collaborative Dynamic Load Balancer for Virtual Machine. In: Guarracino, M.R., et al. (eds.) Euro-Par-Workshop 2010. LNCS, vol. 6586, pp. 641–648. Springer, Heidelberg (2011)
Rowstron, A., Druschel, P.: Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems. In: Guerraoui, R. (ed.) Middleware 2001. LNCS, vol. 2218, p. 329. Springer, Heidelberg (2001)
Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., Balakrishnan, H.: Chord: A Scalable Peer-to-Peer Lookup Service for Internet Applications. In: ACM SIGCOMM Computer Communication Review, vol. 31, pp. 149–160. ACM (2001)
Xu, Z., Mahalingam, M., Karlsson, M.: Turning Heterogeneity into an Advantage in Overlay Routing. In: INFOCOM (2003)
Xu, Z., Zhang, Z.: Building Low-Maintenance Expressways for P2P Systems. Tech. Rep. HPL-2002-41, Hewlett-Packard Labs (2002)
Yazir, Y.O., Matthews, C., Farahbod, R.: Neville, S., Guitouni, A., Ganti, S., Coady, Y.: Dynamic Resource Allocation in Computing Clouds Using Distributed Multiple Criteria Decision Analysis. In: Cloud 2010: IEEE 3rd Int. Conf. on Cloud Computing, Los Alamitos, CA, USA, pp. 91–98 (July 2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Pastor, J., Bertier, M., Desprez, F., Lebre, A., Quesnel, F., Tedeschi, C. (2014). Locality-Aware Cooperation for VM Scheduling in Distributed Clouds. In: Silva, F., Dutra, I., Santos Costa, V. (eds) Euro-Par 2014 Parallel Processing. Euro-Par 2014. Lecture Notes in Computer Science, vol 8632. Springer, Cham. https://doi.org/10.1007/978-3-319-09873-9_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-09873-9_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09872-2
Online ISBN: 978-3-319-09873-9
eBook Packages: Computer ScienceComputer Science (R0)