Abstract
The resources’ heterogeneity and unbalanced capability, together with the diversity of resource requirements in cloud computing systems, have produced great contradictions between resources’ tight coupling characteristics and user’s multi-granularities requirements. We propose a resource virtualization model and its on-demand allocation oriented infrastructure mainly providing computing services to solve that problem. A loosely coupled resource environment centered on resource users is created to complete a mapping from physical view of resources to logic view of resources. Heuristic resource combination algorithm (HRCA) is proposed to transform physical resources to logic resources, which meets two requirements: randomness in combination and fluctuation control to the size of resources granularities. On the basis of the appraisal indexes presented for the on-demand allocation, resource matching algorithm (RMA), targeting at resource satisfaction with the highest resource utilization, is designed to reuse resources. RMA can satisfy users’ requirement in limited time and keep resource satisfaction in the highest level in the condition of logic resources granularities being less than their required size. Resource reconfiguration algorithm (RRA) is presented to implement resource matching in the condition that virtual computing resource pool cannot match granularities of resource requirements. RRA assures the lowest resource refusal rate and the greatest resource satisfaction. We verify the effectiveness, performance and accuracy of algorithms in implementing the goal of resource virtualization centered on resource users and on-demand allocation.
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References
Hai J, Xiaofei L (2008) Virtualization technology for computing system (in Chinese). China Basic Sci 10(6): 12–18
Barham P, Dragovic B, Fraser K et al (2003) Xen and the Art of Virtualization. In: Proceedings of 19 ACM symposium operating systems principles. ACM Press, pp 164–177
Fraser Keir A, Hand Steven M, Leslie Ian M et al (2003) The Xen server computing infrastructure. Technical Report UCAM-CL-TR-552. University of Cambridge, pp 31–41
Nelson M, Lim B-H, Hutchins G (2005) Fast transparent migration for virtual machines. In: Proceedings of USENIX’05 (USENIX 2005), pp 67–74
Waldspurger Arl A (2002) Memory resource management in VMware ESX server. In: The symposium on operating systems design and implementation, pp 181–194
Sotomayor B, Keahey K, Foster I (2006) Overhead matters: a model for virtual resource management. In: First international workshop on virtualization technology in distributed computing, pp 5–8
Huang Y-F, Chao B-W (2001) A priority-based resource allocation strategy in distributed computing networks. J Syst Softw 58(3): 221–233
Andrzejak A, Ceyran M (2005) Characterizing and predicting resource demand by periodicity mining. J Netw Syst Manag 13(2): 175–196
Xiaoying W, Zhihui D, Chen Y et al (2008) Virtualization-based autonomic resource management for multi-tier Web applications in shared data center. J Syst Softw 81(9): 1591–1608
Stillwell M, Schanzenbach D, Vivien F et al (2010) Resource allocation algorithms for virtualized service hosting platforms. J Parallel Distrib Comput (Article in Press)
Yuan D, Yang Y, Liu X, Chen J (2010) A data placement strategy in scientific cloud workflows. Future Gener Comput Syst (in Press)
Grit L, Irwin Aydan Y el al (2006) Virtual Machine hosting for networked clusters: building the foundations for autonomic orchestration. In: First international workshop on virtualization technology in distributed computing, pp 55–62
Foster I, Zhao Y, Raicu I, Lu S (2008) Cloud computing and grid computing 360-degree compared. In: Proceedings of grid computing environments workshop, pp 1–10
Cherkasova L, Gardner R (2005) Measuring CPU overhead for I/O processing in the Xen virtual machine monitor. USENIX 2005 annual technical conference. Anaheim, CA, pp 12–24
Menon A, Renato Santos J et al (2005) Diagnosing performance overheads in the xen virtual machine environment, VEE’05, Chicago
Vrable M, Justin M, Chen J et al (2005) Scalability, fidelity, and containment in the potemkin virtual honeyfarm. ACM SIGOPS Oper Syst Rev 39(5): 62–65
Barham P, Dragovic B, Fraser K et al (2003) Xen and the art of virtualization. In: Proceedings of the ACM symposium on operating systems principles, Bolton, pp 164–167
Li Q, Huai J, Li J et al (2008) HyperMIP: hypervisor controlled mobile IP for virtual machine live migration across networks. In: Proceedings of high assurance systems engineering symposium, pp 3–5
Whitaker A, Shaw M et al (2002) Scale and performance in the Denali isolation kernel. In: Proceedings of the 5th symposium on operating systems design and implementation, Boston, MA, pp 195–209
Wiegert J, Regnier G, Jackson (2007) Challenges for scalable networking in a virtualized server. In: Proceedings of 16th international conference on computer communications and networks, pp 13–16
Van HN, Tran FD, Menaud JM (2009) Autonomic virtual resource management for service hosting platforms. In: Proceedings of software engineering challenges of cloud computing, pp 23–33
Edward W (2008) Benchmarking Amazon EC2 for high-performance scientific computing. http://www.usenix.org/publications/login/2008-10/benchmark_results.tgz
Gmach D, Roliaa J, Cherkasova L et al (2009) Resource pool management: reactive versus proactive or let’s be friends. Comput Netw 53(17): 2905–2922
Mukherjeea T, Banerjeea A et al (2009) Spatio-temporal thermal-aware job scheduling to minimize energy consumption in virtualized heterogeneous data centers. Comput Netw 53(17): 2888–2904
Garga Saurabh K, Yeo Chee S et al (2010) Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers. J Parallel Distrib Comput (in press)
Kanta K (2009) Data center evolution-A tutorial on state of the art, issues, and challenges. Comput Netw 53(17): 2939–2965
Begnum K (2010) Simplified cloud-oriented virtual machine management with MLN. J Supercomput 0920-8542 (in press)
Murphy Michael A, Abraham L, Fenn M et al (2010) Autonomic clouds on the grid. J Grid Comput 8(1): 1–18
Zou D, Du S, Zheng W, Jin H (2009) Building automated trust negotiation architecture in virtual computing environment. J Supercomput, 0920-8542
Kumar S, Talwar V, Kumar V et al (2010) Loosely coupled coordinated management in virtualized data centers. Clust Comput, pp 1386–7857
Zhao M, Zhang J, Figueiredo Renato J (2006) Distributed file system virtualization techniques supporting on-demand virtual machine environments for grid computing. Clust Comput 9(1): 45–56
Zhao M, Zhang J, Figueiredo R (2004) Distributed file system support for virtual machines in grid computing. In: Proceedings of the 13th IEEE international symposium on HPDC, pp 202–211
Luis R-M, Vaqueroa Luis M, Gilb V et al (2010) From infrastructure delivery to service management in clouds. Future Gener Comput Syst (Article in Press)
Bicocchi N, Mameia M, Zambonellia F (2010) Handling dynamics in diffusive aggregation schemes: an evaporative approach. Future Gener Comput Syst 26(6): 877–889
Rosenthala A, Mork P, Lia Maya H et al (2010) Cloud computing: a new business paradigm for biomedical information sharing. J Biomed Inform 43(2): 342–353
Buyya R, Shin Yeo C, Venugopal S et al (2009) Cloud computing and emerging IT platforms: vision, hype, and reality fordelivering computing as the 5th utility. Future Gener Comput Syst 25(6): 599–616
Truong H-L, Dustdara S (2010) Composable cost estimation and monitoring for computational applications in cloud computing environments. Procedia Comput Sci 1(1): 2169–2178
Grossman Robert L, Yunhong G, Sabala M (2009) Compute and storage clouds using wide area high performance networks. Future Gener Comput Syst 25(1): 179–183
Song F (2010) Failure-aware resource management for high-availability computing clusters with distributed virtual machines. J Parallel Distrib Comput Arch 70(4): 384–393
Alonso-Calvoa R, Cespoa J, Garc’ia-Remesala M et al (2010) On distributing load in cloud computing: a real application for very-great image datasets. Proc Comput Sci 1(1): 2663–2671
Richarda B, Maillardb N, César AF et al (2005) The I-cluster cloud: distributed management of idle resources for intense computing. Parallel Comput 31(8–9): 813–838
Khargharia B, Hariri S, Yousif MS (2008) Autonomic power and performance management for computing systems. Clust Comput 11(2): 167–181
Miljani Z, Spasojevi P (2008) Resource Virtualization with Programmable Radio Processing Platform. In: Proceedings of the 4th annual international conference on wireless internet. Maui, Hawaii, pp 6–11
Xu J, Zhao M, Fortes J et al (2008) Autonomic resource management in virtualized data centers using fuzzy logic-based approaches. Clust Comput 11(3): 213–227
Lehoczky J, Sha L, Ding Y (1989) The rate monotonic scheduling algorithm: exact characteristics and average case behavior. In: Proceedings of the IEEE real-time systems symposium, pp 166–171
Nieh J, Lam M (1997) The design, implementation, and evaluation of smart: a scheduler for multimedia applications. In: Proceedings of the sixtheenth symposium on operating system principles. St. Malo, pp 184–197
Jones MB, Rosu D, Rosu M-C (1997) CPU reservations and time constraints: efficient, predictable scheduling of independent activities. In: Proceedings of the sixteenth symposium on operating system principles, St. Malo, pp 198–211
Bavier A, Peterson LL, Moseberger D (2008) BERT: a scheduler for best effort and realtime tasks. Technical Report, Department of Computer Science, Princeton University
Shi L, Sun Y, Wei L (2007) Effect of scheduling discipline on CPU-MEM load sharing system. Sixth international conference on grid and cooperative computing, Xinjiang, pp 242–249
Rawat Sandeep S (2009) Experiments with CPU scheduling algorithm on a computational grid, 2009. In: IEEE international advance computing conference (IACC 2009), Patiala, pp 71–75
Duda KJ, Cheriton DR (1999) Borrowed-virtual-time(BVT) scheduling: supporting latency-sensitive threads in a general-purpose scheduler. In: Proceedings of the 17th ACM SOSP, pp 454–459
Song F, Cheng-Zhong X (2006) Stochastic modeling and analysis of hybrid mobility in reconfigurable distributed virtual machines. J Parallel Distrib Comput 66(11): 1442–1454
Gupta D, Cherkasova L, Gardner R et al (2006) Enforcing performance isolation across virtual machines in Xen. In: Proceedings of the 7th international middleware conference, Melbourne, pp 342 –362
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Chen, X., Zhang, J., Li, J. et al. Resource virtualization methodology for on-demand allocation in cloud computing systems. SOCA 7, 77–100 (2013). https://doi.org/10.1007/s11761-011-0092-9
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DOI: https://doi.org/10.1007/s11761-011-0092-9