The Community for Technology Leaders
RSS Icon
Issue No.03 - March (2013 vol.24)
pp: 464-478
Sheng Di , The University of Hong Kong, Hong Kong
Cho-Li Wang , The University of Hong Kong, Hong Kong
By leveraging virtual machine (VM) technology which provides performance and fault isolation, cloud resources can be provisioned on demand in a fine grained, multiplexed manner rather than in monolithic pieces. By integrating volunteer computing into cloud architectures, we envision a gigantic self-organizing cloud (SOC) being formed to reap the huge potential of untapped commodity computing power over the Internet. Toward this new architecture where each participant may autonomously act as both resource consumer and provider, we propose a fully distributed, VM-multiplexing resource allocation scheme to manage decentralized resources. Our approach not only achieves maximized resource utilization using the proportional share model (PSM), but also delivers provably and adaptively optimal execution efficiency. We also design a novel multiattribute range query protocol for locating qualified nodes. Contrary to existing solutions which often generate bulky messages per request, our protocol produces only one lightweight query message per task on the Content Addressable Network (CAN). It works effectively to find for each task its qualified resources under a randomized policy that mitigates the contention among requesters. We show the SOC with our optimized algorithms can make an improvement by 15-60 percent in system throughput than a P2P Grid model. Our solution also exhibits fairly high adaptability in a dynamic node-churning environment.
Vectors, Resource management, Equations, Heuristic algorithms, System-on-a-chip, Convex functions, Protocols, P2P multiattribute range query, Cloud computing, VM-multiplexing resource allocation, convex optimization
Sheng Di, Cho-Li Wang, "Dynamic Optimization of Multiattribute Resource Allocation in Self-Organizing Clouds", IEEE Transactions on Parallel & Distributed Systems, vol.24, no. 3, pp. 464-478, March 2013, doi:10.1109/TPDS.2012.144
[1] J.E. Smith and R. Nair, Virtual Machines: Versatile Platforms for Systems And Processes. Morgan Kaufmann, 2005.
[2] D. Gupta, L. Cherkasova, R. Gardner, and A. Vahdat, "Enforcing Performance Isolation across Virtual Machines in Xen," Proc. Seventh ACM/IFIP/USENIX Int'l Conf. Middleware (Middleware '06), pp. 342-362, 2006.
[3] M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. 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, Feb. 2009.
[4] D.P. Anderson, "Boinc: A System for Public-Resource Computing and Storage," Proc. IEEE/ACM Fifth Int'l Workshop Grid Computing, pp. 4-10, 2004.
[5] P. Crescenzi and V. Kann, A Compendium of NP Optimization Problems. compendium.pdf , 2012.
[6] O. Sinnen, Task Scheduling for Parallel Systems, Wiley Series on Parallel and Distributed Computing. Wiley-Interscience, 2007.
[7] O.H. Ibarra and C.E. Kim, "Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors," J. ACM, vol. 24, pp. 280-289, Apr. 1977.
[8] X. Meng et al., "Efficient Resource Provisioning in Compute Clouds via vm Multiplexing," Proc. IEEE Seventh Int'l Conf. Autonomic Computing (ICAC '10), pp. 11-20, 2010.
[9] J. Sonneck and A. Chandra, "Virtual Putty: Reshaping the Physical Footprint of Virtual Machines," Proc. Int'l HotCloud Workshop in Conjunction with USENIX Ann. Technical Conf., 2009.
[10] D. Gupta et al., "Difference Engine: Harnessing Memory Redundancy in Virtual Machines," Proc. Eighth Int'l USENIX Symp. Operating Systems Design and Implementation, pp. 309-322, 2008.
[11] S. Govindan, J. Choi, B. Urgaonkar, A. Sivasubramaniam, and A. Baldini, "Statistical Profiling-Based Techniques for Effective Power Provisioning in Data Centers," Proc. Fourth ACM Conf. European Conf. Computer Systems (EuroSys '09), pp. 317-330. 2009,
[12] M. Feldman, K. Lai, and L. Zhang, "The Proportional-Share Allocation Market for Computational Resources," IEEE Trans. Parallel and Distributed Systems, vol. 20, no. 8, pp. 1075-1088, Aug. 2009.
[13] S. Soltesz, H. Poetzl, M.E. Fiuczynski, A. Bavier, and L. Peterson, "Container-Based Operating System Virtualization: A Scalable, High-Performance Alternative to Hypervisors," Proc. Second ACM Int'l European Conf. Computer Systems (Euro '07), pp. 275-287. 2007,
[14] L. Cherkasova, D. Gupta, and A. Vahdat, "Comparison of the Three cpu Schedulers in Xen," SIGMETRICS Performance Evaluation Rev., vol. 35, no. 2, pp. 42-51, 2007.
[15] "The Role of Memory in Vmware Esx Server 3: On Line At: ," technical report, 2012.
[16] dm-ioband:, 2012.
[17] S. Ratnasamy, P. Francis, M. Handley, R. Karp, and S. Shenker, "A Scalable Content-Addressable Network," Proc. ACM SIGCOMM '01, pp. 161-172, 2001.
[18] I. Stoica, R. Morris, D. Karger, M.F. Kaashoek, and H. Balakrishnan, "Chord: A Scalable Peer-to-Peer Lookup Service for Internet Applications," Proc. ACM SIGCOMM '01, pp. 149-160, 2001.
[19] J.S. Kim et al., "Using Content-Addressable Networks for Load Balancing in Desktop Grids," Proc. 16th ACM Int'l Symp. High Performance Distributed Computing (HPDC '07), pp. 189-198, 2007.
[20] A. Leite, H. Mendes, L. Weigang, A. de Melo, and A. Boukerche, "An Architecture for P2P Bag-of-Tasks Execution with Multiple Task Allocation Policies in Desktop Grids," Proc. IEEE Int'l Conf. Cluster Computing, pp. 1-11, Feb. 2011.
[21] Y. Drougas and V. Kalogeraki, "A Fair Resource Allocation Algorithm for Peer-to-Peer Overlays," Proc. IEEE INFOCOM '05, pp. 2853-2858, 2005.
[22] D. Gross and C.M. Harris, Fundamentals of Queueing Theory, Wiley Series in Probability and Statistics. Wiley-Interscience, Feb. 1998.
[23] S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge Univ. Press, 2009.
[24] S. Di, C.-L. Wang, W. Zhang, and L. Cheng, "Probabilistic Best-Fit Multi-Dimensional Range Query in Self-Organizing Cloud," Proc. IEEE 40th Int'l Conf. Parallel Processing, pp. 763-772, 2011.
[25] 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.
[26] Peersim Simulator: http:/, 2012.
[27] Google Cluster-Usage Traces: googleclusterdata , 2012.
[28] C.A. Waldspurger, "Memory Resource Management in Vmware Esx Server," waldspurger.html, 2012.
[29] J.P. Walters, V. Chaudhary, M. Cha, S. GuercioJr., and S. Gallo, "A Comparison of Virtualization Technologies for hpc," Proc. IEEE 22nd Int'l Conf. Advanced Information Networking and Applications (AINA '08), pp. 861-868, 2008.
[30] W.K. Mark Jelasity and M. van Steen, "Newscast Computing," technical report, Vrije Universiteit Amsterdam, 2006.
[31] R.K. Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modelling. John Wiley & Sons, Apr. 1991.
[32] J. Cao, F.B. Liu, and C.Z. Xu, "P2pgrid: Integrating P2P Networks Into the Grid Environment: Research Articles," vol. 19, no. 7, pp. 1023-1046, 2007.
[33] H. Abbes, C. Cerin, and M. Jemni, "Bonjourgrid: Orchestration of Multi-Instances of Grid Middlewares on Institutional Desktop Grids," Proc. IEEE 23rd Int'l Symp. Parallel & Distributed Processing (IPDPS '09), pp. 1-8, 2009.
[34] A. Rossi, A. Singh, and M. Sevaux, "A Metaheuristic for the Fixed Job Scheduling Problem under Spread Time Constraints," Computational Operation Research, vol. 37, pp. 1045-1054, June 2010.
[35] P. Switalski and F. Seredynski, "Generalized Extremal Optimization for Solving Multiprocessor Task Scheduling Problem," Proc. Seventh Int'l Conf. Simulated Evolution and Learning, pp. 161-169, 2008.
[36] G. Singh, C. Kesselman, and E. Deelman, "A Provisioning Model and its Comparison with Best-Effort for Performance-Cost Optimization in Grids," Proc. 16th ACM Symp. High Performance Distributed Computing (HPDC '07), 117-126, 2007.
[37] Q. Zheng, H. Yang, and Y. Sun, "How to Avoid Herd: A Novel Stochastic Algorithm in Grid Scheduling," Proc. 15th ACM Int'l Symp. High Performance Distributed Computing (HPDC '06), pp. 267-278, 2006.
[38] C.B. Lee and A.E. Snavely, "Precise and Realistic Utility Functions for User-Centric Performance Analysis of Schedulers," Proc. 16th ACM Int'l Symp. High Performance Distributed Computing (HPDC '07), pp. 107-116, 2007.
[39] A.R. Bharambe, M. Agrawal, and S. Seshan, "Mercury: Supporting Scalable Multi-Attribute Range Queries," Proc. ACM SIGCOMM '04, pp. 353-366, 2004.
[40] D. Li, J. Cao, X. Lu, and K.C.C. Chen, "Efficient Range Query Processing in Peer-to-Peer Systems," IEEE Trans. Knowledge and Data Eng., vol. 21, no. 1, pp. 78-91, Jan. 2009.
[41] A. Gonzalezbeltran, P. Milligan, and P. Sage, "Range Queries Over Skip Tree Graphs," Computer Comm., vol. 31, no. 2, pp. 358-374, Feb. 2008.
[42] S. Wang, Q.H. Vu, B.C. Ooi, A.K. Tung, and L. Xu, "Skyframe: A Framework for Skyline Query Processing in Peer-to-Peer Systems," J. VLDB, vol. 18, pp. 345-362, Jan. 2009.
[43] M.A. Arefin, M.Y.S. Uddin, I. Gupta, and K. Nahrstedt, "Q-Tree: A Multi-Attribute Based Range Query Solution for Tele-Immersive Framework," Proc. IEEE 29th Int'l Conf. Distributed Computing Systems (ICDCS '09), pp. 299-307, 2009.
[44] J. Wang, S. Wu, H. Gao, J. Li, and B.C. Ooi, "Indexing Multi-Dimensional Data in a Cloud System," Proc. ACM Int'l Conf. Management of Data (SIGMOD '10), pp. 591-602, 2010.
31 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool