The Community for Technology Leaders
RSS Icon
Issue No.06 - June (2013 vol.24)
pp: 1097-1106
Sheng Di , The University of Hong Kong, Hong Kong
Cho-Li Wang , The University of Hong Kong, Hong Kong
With virtual machine (VM) technology being increasingly mature, compute resources in cloud systems can be partitioned in fine granularity and allocated on demand. We make three contributions in this paper: 1) We formulate a deadline-driven resource allocation problem based on the cloud environment facilitated with VM resource isolation technology, and also propose a novel solution with polynomial time, which could minimize users' payment in terms of their expected deadlines. 2) By analyzing the upper bound of task execution length based on the possibly inaccurate workload prediction, we further propose an error-tolerant method to guarantee task's completion within its deadline. 3) We validate its effectiveness over a real VM-facilitated cluster environment under different levels of competition. In our experiment, by tuning algorithmic input deadline based on our derived bound, task execution length can always be limited within its deadline in the sufficient-supply situation; the mean execution length still keeps 70 percent as high as user-specified deadline under the severe competition. Under the original-deadline-based solution, about 52.5 percent of tasks are completed within 0.95-1.0 as high as their deadlines, which still conforms to the deadline-guaranteed requirement. Only 20 percent of tasks violate deadlines, yet most (17.5 percent) are still finished within 1.05 times of deadlines.
Resource management, Vectors, Equations, Mathematical model, Prediction algorithms, Virtual machining, Upper bound, payment minimization, VM multiplexing, resource allocation, convex optimization, prediction error tolerance
Sheng Di, Cho-Li Wang, "Error-Tolerant Resource Allocation and Payment Minimization for Cloud System", IEEE Transactions on Parallel & Distributed Systems, vol.24, no. 6, pp. 1097-1106, June 2013, doi:10.1109/TPDS.2012.309
[1] M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R.H. Katz, A. Konwinski, G. Lee, D.A. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, "Above the Clouds: A Berkeley View of Cloud Computing," Technical Report UCB/EECS-2009-28, EECS Dept., Univ. California, Berkeley, Feb. 2009.
[2] L.M. Vaquero, L. Rodero-Merino, J. Caceres, and M. Lindner, "A Break in the Clouds: Towards a Cloud Definition," SIGCOMM Computer Comm. Rev., vol. 39, no. 1, pp. 50-55, 2009.
[3] I. Foster and C. Kesselman, The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, Nov. 2003.
[4] J.E. Smith and R. Nair, Virtual Machines: Versatile Platforms For Systems and Processes. Morgan Kaufmann, 2005.
[5] D. Gupta, L. Cherkasova, R. Gardner, and A. Vahdat, "Enforcing Performance Isolation across Virtual Machines in Xen," Proc. ACM/IFIP/USENIX Int'l Conf. Middleware (Middleware '06), pp. 342-362, 2006.
[6] J.N. Matthews, W. Hu, M. Hapuarachchi, T. Deshane, D. Dimatos, G. Hamilton, M. McCabe, and J. Owens, "Quantifying the Performance Isolation Properties of Virtualization Systems," Proc. Workshop Experimental Computer Science (ExpCS '07), 2007.
[7] Amazon Elastic Compute Cloud,, 2012.
[8] D. Milojicic, I.M. Llorente, and R.S. Montero, "Opennebula: A Cloud Management Tool," IEEE Internet Computing, vol. 15, no. 2, pp. 11-14, Mar./Apr. 2011.
[9] S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge Univ. Press, 2009.
[10] E. Imamagic, B. Radic, and D. Dobrenic, "An Approach to Grid Scheduling by Using Condor-G Matchmaking Mechanism," Proc. 28th Int'l Conf. Information Technology Interfaces, pp. 625-632, 2006.
[11] B. Sharma, V. Chudnovsky, J.L. Hellerstein, R. Rifaat, and C.R. Das, "Modeling and Synthesizing Task Placement Constraints in Google Compute Clusters," Proc. Second ACM Symp. Cloud Computing (SOCC '11), pp. 3:1-3:14, 2011.
[12] H. Khazaei, J.V. Misic, and V.B. Misic, "Modelling of Cloud Computing Centers Using m/g/m Queues," Proc. Int'l Conf. Distributed Computing Systems Workshops (ICDCS), pp. 87-92, 2011.
[13] Y. Wu, K. Hwang, Y. Yuan, and W. Zheng, "Adaptive Workload Prediction of Grid Performance in Confidence Windows," IEEE Trans. Parallel and Distributed Systems, vol. 21, no. 7, pp. 925-938, July 2010.
[14] S. Di, D. Kondo, and W. Cirne, "Characterization and Comparison of Cloud versus Grid Workloads," Proc. 14th Int'l Conf. Cluster Computing, pp. 230-238, 2012.
[15] Q. Zhang, J.L. Hellerstein, and R. Boutaba, "Characterizing Task Usage Shapes in Google's Compute Clusters," Proc. Large-Scale Distributed Systems and Middleware Workshop (LADIS '11), 2011.
[16] L. Huang, J. Jia, B. Yu, B.G. Chun, P. Maniatis, and M. Naik, "Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression," Proc. 24th Conf. Neural Information Processing Systems (NIPS '10), pp. 1-9, 2010.
[17] 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. 19th ACM Symp. Operating Systems Principles (SOSP '03), pp. 164-177, 2003.
[18] P. Wendykier and J.G. Nagy, "Parallel Colt: A High-Performance Java Library for Scientific Computing and Image Processing," ACM Trans. Math. Software, vol. 37, pp. 31:1-31:22, Sept. 2010.
[19] R.K. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modelling. John Wiley & Sons, Apr. 1991.
[20] C. Jiang, C. Wang, X. Liu, and Y. Zhao, "A Survey of Job Scheduling in Grids," Proc. Joint Ninth Asia-Pacific Web and Eighth Int'l Conf. Web-Age Information Management Conf. Advances in Data and Web Management (APWeb/WAIM '07), pp. 419-427, 2007.
[21] P. Crescenzi and V. Kann, A Compendium of NP Optimization Problems, compendium.pdf , 2012.
[22] O. Sinnen, Task Scheduling for Parallel Systems. Wiley-Interscience, May 2007.
[23] K. Ramamritham, J.A. Stankovic, and W. Zhao, "Distributed Scheduling of Tasks with Deadlines and Resource Requirements," IEEE Trans. Computers, vol. 38, no. 8, pp. 1110-1123, Aug. 1989.
[24] M.C. McElvany and P.D. Stotts, "Guaranteed Task Deadlines for Fault-Tolerant Workloads with Conditional Branches," Real-Time Systems, vol. 3, no. 3, pp. 275-305, 1991.
[25] L. Zhao, Y. Ren, and K. Sakurai, "A Resource Minimizing Scheduling Algorithm with Ensuring the Deadline and Reliability in Heterogeneous Systems," Proc. 25th IEEE Int'l Conf. Advanced Information Networking and Applications (AINA '11), pp. 275-282, 2011.
[26] W. Chen, A. Fekete, and Y.C. Lee, "Exploiting Deadline Flexibility in Grid Workflow Rescheduling," Proc. 11th IEEE/ACM Int'l Conf. Grid Computing (Grid '10), pp. 105-112, 2010.
[27] X. Meng, C. Isci, J. Kephart, L. Zhang, E. Bouillet, and D. Pendarakis, "Efficient Resource Provisioning in Compute Clouds via VM Multiplexing," Proc. Seventh Int'l Conf. Autonomic Computing (ICAC '10), pp. 11-20, 2010.
[28] R. Nathuji, A. Kansal, and A. Ghaffarkhah, "Q-Clouds : Managing Performance Interference Effects for Qos-Aware Clouds," Proc. European Conf. Computer Systems (EuroSys '10), pp. 237-250, 2010.
[29] L. Wu, S.K. Garg, and R. Buyya, "SLA-Based Resource Allocation for Software as a Service Provider (SAAS) in Cloud Computing Environments," Proc. 11th IEEE/ACM Int'l Symp. Cluster, Cloud and Grid Computing (CCGRID '11), pp. 195-204, 2011.
[30] S. Chaisiri, R. Kaewpuang, B.-S. Lee, and D. Niyato, "Cost Minimization for Provisioning Virtual Servers in Amazon Elastic Compute Cloud," Proc. 19th Ann. IEEE/ACM Int'l Symp. Modeling, Analysis and Simulation of Computer and Telecomm. Systems (MASCOTS '11), pp. 85-95, 2011.
[31] M. Mao, J. Li, and M. Humphrey, "Cloud Auto-Scaling with Deadline and Budget Constraints," Proc. 11th IEEE/ACM Int'l Conf. Grid Computing (Grid '10), pp. 41-48, 2010.
[32] M. Mao and M. Humphrey, "Auto-Scaling to Minimize Cost and Meet Application Deadlines in Cloud Workflows," Proc. Int'l Conf. High Performance Computing, Networking, Storage & Analysis (SC '11), pp. 49:1-49:12, 2011.
[33] J. Weinman, "Smooth Operator: The Value of Demand Aggregation," Smooth_Operator _Demand_Aggregation.pdf , 2011.
[34] V. Petrucci, O. Loques, and D. Mossé, "A Dynamic Optimization Model for Power and Performance Management of Virtualized Clusters," Proc. First Int'l Conf. Energy-Efficient Computing and Networking (e-Energy '10), pp. 225-233, 2010.
[35] F. Chang, J. Ren, and R. Viswanathan, "Optimal Resource Allocation in Clouds," Proc. IEEE Int'l Conf. Cloud Computing, pp. 418-425, 2010.
7 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool