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Performance evaluation of MapReduce using full virtualisation on a departmental cloud

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International Journal of Applied Mathematics and Computer Science
Efficient Resource Management for Grid-Enabled Applications (special section, pp. 219 - 306), Joanna Kołodziej and Fatos Xhafa (Eds.)

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Anon, E.A. (1998). A measure of transaction processing power, in M. Stonebraker and J.M. Hellerstein (Eds.), Readings in Database Systems, 3rd Edn., Morgan Kaufmann, San Francisco, CA, pp. 609-621.Search in Google Scholar

Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R.H., Konwinski, A., Lee, G., Patterson, D.A., Rabkin, A., Stoica, I. and Zaharia, M. (2010). A view of cloud computing, Communications of the ACM53(4): 50-58.10.1145/1721654.1721672Search in Google Scholar

Bacci, B., Danelutto, M., Pelagatti, S. and Vanneschi, M. (1999). SkIE: A heterogeneous environment for HPC applications, Parallel Computing25(13): 1827-1852.10.1016/S0167-8191(99)00072-1Search in Google Scholar

Beaumont, O., Casanova, H., Legrand, A., Robert, Y. and Yang, Y. (2005). Scheduling divisible loads on star and tree networks: Results and open problems, IEEE Transactions on Parallel and Distributed Systems16(3): 207-218.10.1109/TPDS.2005.35Search in Google Scholar

Buono, D., Danelutto, M. and Lametti, S. (2010). Map, reduce and MapReduce, the skeleton way, Procedia Computer Science1(1): 2089-2097.10.1016/j.procs.2010.04.234Search in Google Scholar

Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J. and Brandic, I. (2009). Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility, Future Generation Computer Systems—The International Journal of Grid Computing: Theory Methods and Applications25(6): 599-616.10.1016/j.future.2008.12.001Search in Google Scholar

Buzen, J.P. and Gagliardi, U.O. (1973). The evolution of virtual machine architecture, Proceedings of the National Computer Conference and Exposition, AFIPS '73, ACM, New York, NY, pp. 291-299.Search in Google Scholar

Cole, M. (1989). Algorithmic Skeletons: Structured Management of Parallel Computation, Pitman/MIT Press, London.Search in Google Scholar

Cole, M. (2004). Bringing skeletons out of the closet: A pragmatic manifesto for skeletal parallel programming, Parallel Computing30(3): 389-406.10.1016/j.parco.2003.12.002Search in Google Scholar

Danelutto, M. (2004). Adaptive task farm implementation strategies, 12th Euromicro Workshop on Parallel, Distributed and Network-Based Processing, PDP 2004, IEEE, La Coruña, pp. 416-423.Search in Google Scholar

Dean, J. and Ghemawat, S. (2004). MapReduce: Simplified data processing on large clusters, Proceedings of the 6th conference on Symposium on Operating Systems Design & Implementation OSDI'04, Vol. 6, USENIX, San Francisco, CA, pp. 137-150.Search in Google Scholar

Dean, J. and Ghemawat, S. (2008). MapReduce: Simplified data processing on large clusters, Communications of the ACM51(1): 107-113.10.1145/1327452.1327492Search in Google Scholar

González-Vélez, H. (2006). Self-adaptive skeletal task farm for computational grids, Parallel Computing32(7-8): 479-490.10.1016/j.parco.2006.07.002Search in Google Scholar

González-Vélez, H. and Cole, M. (2010a). Adaptive statistical scheduling of divisible workloads in heterogeneous systems, Journal of Scheduling13(4): 427-441.10.1007/s10951-009-0138-4Search in Google Scholar

González-Vélez, H. and Cole, M. (2010b). Adaptive structured parallelism for distributed heterogeneous architectures: A methodological approach with pipelines and farms, Concurrency and Computation: Practice and Experience22(15): 2073-2094.10.1002/cpe.1549Search in Google Scholar

González-Vélez, H. and Leyton, M. (2010). A survey of algorithmic skeleton frameworks: High-level structured parallel programming enablers, Software: Practice and Experience40(12): 1135-1160.10.1002/spe.1026Search in Google Scholar

Ibrahim, S., Jin, H., Lu, L., Qi, L., Wu, S. and Shi, X. (2009). Evaluating MapReduce on virtual machines: The Hadoop case, in M. Jaatun, G. Zhao, and C. Rong (Eds.) Cloud-Com 2009, Lecture Notes in Computer Science, Vol. 5931, Springer-Verlag, Berlin/Heidelberg, pp. 519-528.10.1007/978-3-642-10665-1_47Search in Google Scholar

Kontagora, M. and González-Vélez, H. (2010). Benchmarking a MapReduce environment on a full virtualisation platform, in L. Barolli, F. Xhafa, S. Vitabile and H.-H. Hsu (Eds.), CISIS 2010, The Fourth International Conference on Complex, Intelligent and Software Intensive Systems, Krakow, Poland, 15-18 February 2010, IEEE Computer Society, Washington, DC, pp. 433-438.10.1109/CISIS.2010.45Search in Google Scholar

Kuchen, H. and Striegnitz, J. (2005). Features from functional programming for a C++ skeleton library, Concurrency and Computation: Practice and Experience17(7-8): 739-756.10.1002/cpe.844Search in Google Scholar

Mesghouni, K., Hammadi, S. and Borne, P. (2004). Evolutionary algorithms for job-shop scheduling, International Journal of Applied Mathematics and Computer Science14(1): 91-103.Search in Google Scholar

Nagarajan, A.B., Mueller, F., Engelmann, C. and Scott, S.L. (2007). Proactive fault tolerance for HPC with Xen virtualization, in B. J. Smith (Ed.), Proceedings of the 21th Annual International Conference on Supercomputing, ICS 2007, Seattle, Washington, USA, June 17-21, 2007, ACM, New York, NY, pp. 23-32.10.1145/1274971.1274978Search in Google Scholar

Nokia Research Center (2009). Disco, Manual version 0.2.3, Nokia Research Center http://discoproject.orgSearch in Google Scholar

Pisoni, A. (2007). Skynet, Manual version 0.9.3Geni.com,skynet.rubyforge.orgSearch in Google Scholar

Ranger, C., Raghuraman, R., Penmetsa, A., Bradski, G. and Kozyrakis, C. (2007). Evaluating MapReduce for multi-core and multiprocessor systems, 13th International Conference on High-Performance Computer Architecture (HPCA-13 2007), Phoenix, AZ, USA, pp. 13-24.Search in Google Scholar

Robertazzi, T.G. (2003). Ten reasons to use divisible load theory, Computer36(5): 63-68.10.1109/MC.2003.1198238Search in Google Scholar

Sandholm, T. and Lai, K. (2009). MapReduce optimization using regulated dynamic prioritization, in J.R. Douceur, A.G. Greenberg, T. Bonald, J. Nieh (Eds.), Proceedings of the Eleventh International Joint Conference on Measurement and Modeling of Computer Systems, SIGMETRICS/Performance 2009, Seattle, WA, USA, June 15-19, 2009, ACM, New York, NY, pp. 299-310.10.1145/1555349.1555384Search in Google Scholar

The Apache Software Foundation (2008). Hadoop MapReduce tutorial, Manual version 0.15, Hadoop Project http://hadoop.apache.orgSearch in Google Scholar

VMware (2007). Understanding full virtualization, paravirtualization, and hardware assist, White Paper Revision: 20070911, VMware, Inc., Palo Alto, CA.Search in Google Scholar

Whitaker, A., Shaw, M. and Gribble, S.D. (2002). Scale and performance in the Denali isolation kernel, ACM SIGOPS Operating Systems Review36(SI): 195-209.10.1145/844128.844147Search in Google Scholar

Youseff, L., Wolski, R., Gorda, B. and Krintz, C. (2006). Paravirtualization for HPC systems, in G. Min, B. Di Martino, L.T. Yang, M. Guo and Gudula Rünger (Eds.), Frontiers of High Performance Computing and Networking—ISPA 2006 International Workshops, Sorrento, Italy, December 4-7, 2006, Lecture Notes in Computer Science, Vol. 4331, Springer-Verlag, Berlin/Heidelberg, pp. 474-486.10.2172/894791Search in Google Scholar

Zaharia, M., Konwinski, A., Joseph, A., Katz, R. and Stoica, I. (2008). Improving MapReduce performance in heterogeneous environments, in R. Draves and R. van Renesse (Eds.), 8th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2008, December 8-10, 2008, San Diego, California, USA, USENIX Association, Berkeley, CA.Search in Google Scholar

ISSN:
1641-876X
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
4 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Mathematik, Angewandte Mathematik