A Filter-Based Dynamic Resource Management Framework for Virtualized Data Centers
Abstract
Data centers adapt their operation to changing run-time conditions using energy-aware and SLA-compliant resource management techniques. In this context, current paper presents a novel filter-based dynamic resource management framework for virtualized data centers. By choosing and combining properly software filters performing the scheduling and resource management operations, the framework may be used in what-if analysis. The framework is evaluated by simulation for deploying batch best-effort jobs with time-varying CPU requirements.
References
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[2] A. Beloglazov, J. Abawajy, R. Buyya, Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing, Future Gener. Comput. Syst., 28 (2012), pp. 755-768.
[3] A. Beloglazov, R. Buyya, Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers, Concurr. Comput.: Pract. Exper., 24 (2012), pp. 1397-1420.
[4] R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. F. De Rose, R. Buyya, CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms, Software: Practice and Experience, 41 (2011), pp. 23-50.
[5] CloudSim. http://www.cloudbus.org/cloudsim/
[6] G. Da Costa, J.-P. Gelas, Y. Georgiou, L. Lefevre, A.-C. Orgerie, J.-M. Pierson, O. Richard, K. Sharma, The GREEN-NET framework: Energy efficiency in large scale distributed systems, in Proceedings of the 2009 IEEE International Symposium on Parallel & Distributed Processing (IPDPS’09), 2009, pp. 1-8.
[7] C. Craciun, I. Salomie, Gaussian-type resource allocation policies for virtualized data centers, Studia Univ. Babes-Bolyai, Informatica, LXI(2) (2016), pp. 94-109.
[8] L. Eyraud-Dubois, G. Mounie, D. Trystram, Analysis of scheduling algorithms with reservations, in Proceedings of the IEEE International Parallel and Distributed Processing Symposium (IPDPS’07), 2007, pp. 1-8.
[9] X. Fan, W.-D. Weber, L. A. Barroso, Power provisioning for a warehouse-sized computer, in Proceedings of the 34th annual International Symposium on Computer architecture (ISCA’07), 2007, pp. 13–23.
[10] M. Gabay, S. Zaourar, Variable size vector bin packing heuristics - Application to the machine reassignment problem, Inria, TechReport hal-00868016 (OSP. 2013). Available online: http://hal.archives-ouvertes.fr/hal-00868016.
[11] S. K. Garg, R. Buyya, NetworkCloudSim: Modelling parallel applications in cloud simulations, in Proceedings of the 2011 4th IEEE International Conference on Utility and Cloud Computing (UCC’11), 2011, pp. 105-113.
[12] M. R. Garey, R. L. Graham, J. D. Ullman, An analysis of some packing algorithms, R. Rustin, ed., Combinatorial Algorithms, Algorithmics Press, New York, 1973, pp. 39-47.
[13] R. L. Graham, Bounds for certain multiprocessing anomalies, Bell System Technical Journal, 45 (1966), pp. 1563-1581.
[14] Green Cloud Scheduler. http://coned.utcluj.ro/GreenCloudScheduler/
[15] Haizea. http://haizea.cs.uchicago.edu/
[16] F. Hermenier, X. Lorca, J.-M. Menaud, G. Muller, J. Lawall, Entropy: a consolidation manager for clusters, in Proceedings of the 2009 ACM SIGPLAN/SIGOPS International Conference on Virtual execution environments (VEE’09), 2009, pp. 41-50.
[17] S. Lee, R. Panigrahy, V. Prabhakaran, V. Ramasubramanian, K. Talwar, L. Uyeda, U. Wieder, Validating heuristics for virtual machines consolidation, Microsoft Research, TechReport MSR-TR-2011-9, Jan 2011. Available online: http://research.microsoft.com/pubs/144571/virtualization.pdf
[18] A. W. Mu’alem, D. G. Feitelson, Utilization, predictability, workloads, and user runtime estimates in scheduling the IBM SP2 with backfilling, IEEE Trans. Parallel Distrib. Syst., 12 (2001), pp. 529-543.
[19] The R Project for Statistical Computing. http://www.r-project.org/
[20] OpenNebula. http://www.opennebula.org/
[21] OpenStack. http://www.openstack.org/
[22] I. Salomie, T. Cioara, I. Anghel, D. Moldovan, G. Copil, P. Plebani, An energy aware context model for green IT service centers, Service-Oriented Computing. Lecture Notes in Computer Science 6568, Springer, Berlin, 2011, pp. 169-180.
[23] B. Sotomayor, K. Keahey, I. Foster, Combining batch execution and leasing using virtual machines, in Proceedings of the 17th International Symposium on High performance distributed computing (HPDC’08), 2008, pp. 87-96.
[24] B. Sotomayor, R. S. Montero, I. M. Llorente, I. Foster, An open source solution for virtual infrastructure management in private and hybrid clouds, IEEE Internet Computing, Special Issue on Cloud Computing, 2009.
[25] B. Sotomayor, R. S. Montero, I. M. Llorente, I. Foster, Resource leasing and the art of suspending virtual machines, in Proceedings of the 11th IEEE International Conference on High Performance Computing and Communications (HPCC-09), 2009, pp. 59-68.
[26] B. Sotomayor Basilio, Provisioning computational resources using virtual machines and leases, PhD Dissertation, Univ. of Chicago, Illinois, USA, 2010.
[27] A. Verma, P. Ahuja, A. Neogi, pMapper: power and migration cost aware application placement in virtualized systems, in Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware (Middleware’08), 2008, pp. 243-264.
[28] T. Wood, P. Shenoy, A. Venkataramani, M. Yousif, Sandpiper: Black-box and gray-box resource management for virtual machines, Comput. Netw., 53 (2009), pp. 2923-2938.
[29] H. Zhang, K. Yoshihira, Y.-Y. Su, G. Jiang, M. Chen, X. Wang, iPOEM: A GPS tool for integrated management in virtualized data centers, in Proceedings of the 8th IEEE/ACM International Conference on Autonomic Computing (ICAC’11), 2011, pp. 41-50.
Published
2017-05-28
How to Cite
CRĂCIUN, Cora; SALOMIE, Ioan.
A Filter-Based Dynamic Resource Management Framework for Virtualized Data Centers.
Studia Universitatis Babeș-Bolyai Informatica, [S.l.], v. 62, n. 1, p. 32-48, may 2017.
ISSN 2065-9601.
Available at: <https://www.cs.ubbcluj.ro/~studia-i/journal/journal/article/view/4>. Date accessed: 20 apr. 2024.
doi: https://doi.org/10.24193/subbi.2017.1.03.
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