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A Novel Heuristic Scheme for Modeling and Managing Time Bound Constraints in Data-Intensive Grid and Cloud Infrastructures

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2014 Workshops (OTM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8842))

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Abstract

Inspired by the emerging Cloud Computing challenge, in this paper we provide a comprehensive framework for modeling and managing time bound constraints in data-intensive Grid and Cloud infrastructures, along with its experimental assessment and analysis. We provide both conceptual and theoretical contributions of the proposed framework, along with a heuristic scheme, called RGDTExec, that solves all possible instances of the problem underlying the proposed framework by exploiting a suitable greedy algorithm, called RGDTExecRun. As we demonstrate throughout the paper, the framework keeps several aspects of research innovations that are beneficial in a wide range of application scenarios.

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References

  1. Agrawal, D., Das, D., El Abbadi, A.: A Big Data and Cloud Computing: Current State and Future Opportunities. In: Proceedings of EDBT 2011, pp. 530–533 (2011)

    Google Scholar 

  2. Barbará, D., DuMouchel, W., Faloutsos, C., Haas, P., Hellerstein, J.M., Ioannidis, Y.E., Jagadish, H.V., Johnson, T., Poosala, V., Ross, K.A., Sevcik, K.C.: The new jersey data reduction report. IEEE Data Engineering Bullettin 20(4), 3–45 (1997)

    Google Scholar 

  3. Bowers, S., Ludäscher, B.: An Ontology-Driven Framework for Data Transformation in Scientific Workflows. In: Rahm, E. (ed.) DILS 2004. LNCS (LNBI), vol. 2994, pp. 1–16. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  4. Cao, Y., Chen, C., Guo, F., Jiang, D., Lin, Y., Ooi, B.C., Vo, H.T., Wu, S., Xu, Q.: ES2: A cloud data storage system for supporting both OLTP and OLAP. In: Proceedings of IEEE ICDE 2011, pp. 291–302 (2011)

    Google Scholar 

  5. de Carvalho Costa, R.L., Furtado, P.: An SLA-enabled grid data warehouse. In: Proceedings of IEEE IDEAS, pp. 285–289 (2007)

    Google Scholar 

  6. Cohen, J., Dolan, B., Dunlap, M., Hellerstein, J.M., Welton, C.: MAD Skills: New Analysis Practices for Big Data. PVLDB 2(2), 1481–1492 (2009)

    Google Scholar 

  7. Costan, A., Tudoran, R., Antoniu, G., Brasche, G.: TomusBlobs: Scalable Data-intensive Processing on Azure Clouds. Concurrency and Computation: Practice and Experience (2013) (in press)

    Google Scholar 

  8. Cuzzocrea, A.: Data transformation services over grids with real-time bound constraints. In: Meersman, R., Tari, Z. (eds.) OTM 2008, Part I. LNCS, vol. 5331, pp. 852–869. Springer, Heidelberg (2008)

    Google Scholar 

  9. Cuzzocrea, A.: Analytics over Big Data: Exploring the Convergence of Data Warehousing, OLAP and Data-Intensive Cloud Infrastructures. In: Proceedings of IEEE COMPSAC 2013, pp. 481–483 (2013)

    Google Scholar 

  10. Cuzzocrea, A., Darmont, J., Mahboubi, H.: Fragmenting very large XML data warehouses via K-means clustering algorithm. International Journal of Business Intelligence and Data Mining 4(3-4), 301–328 (2009)

    Article  Google Scholar 

  11. Cuzzocrea, A., Furfaro, F., Greco, S., Mazzeo, G.M., Masciari, E., Saccà, D.: A distributed system for answering range queries on sensor network data. In: Proceedings of IEEE PerSeNS 2005, pp. 369–373 (2005)

    Google Scholar 

  12. Cuzzocrea, A., Furfaro, F., Masciari, E., Saccà, D., Sirangelo, C.: Approximate query answering on sensor network data streams. In: Stefanidis, A., Nittel, S. (eds.) GeoSensor Networks, pp. 53–72. CRC Press (2004)

    Google Scholar 

  13. Cuzzocrea, A., Furfaro, F., Mazzeo, G.M., Saccá, D.: A grid framework for approximate aggregate query answering on summarized sensor network readings. In: Meersman, R., Tari, Z., Corsaro, A. (eds.) OTM-WS 2004. LNCS, vol. 3292, pp. 144–153. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  14. Cuzzocrea, A., Kumar, A., Russo, V.: Experimenting the query performance of a grid-based sensor network data warehouse. In: Hameurlain, A. (ed.) Globe 2008. LNCS, vol. 5187, pp. 105–119. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  15. Cuzzocrea, A., Song, I.-Y., Davis, K.C.: Analytics over Large-Scale Multidimensional Data: The Big Data Revolution. In: Proceedings of ACM DOLAP, pp. 101–104 (2011)

    Google Scholar 

  16. Dean, J., Ghemawat, S.: MapReduce: Simplified Data Processing on Large Clusters. Communications of the ACM 51(1) (2008)

    Google Scholar 

  17. Foster, I., Kesselman, C., Nick, J.M., Tuecke, S.: Grid services for distributed system integration. IEEE Computer 35(6), 37–46 (2002)

    Article  Google Scholar 

  18. Foster, I., Kesselman, C., Tuecke, S.: The anatomy of the grid: enabling scalable virtual organizations. International Journal of High Performance Computing Applications 15(3), 200–222 (2001)

    Article  Google Scholar 

  19. Fox, G.: Data Intensive Applications on Clouds. In: Proceedings of ACM DataCloud 2011 (2011), http://grids.ucs.indiana.edu/ptliupages/publications/data311gf-fox.pdf

  20. Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., et al.: Data cube: a relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data Mining and Knowledge Discovery 1(1), 29–53 (1997)

    Article  Google Scholar 

  21. Ho, C.-T., Agrawal, R., Megiddo, N., Srikant, R.: Range queries in OLAP data cubes. In: Proceedings of ACM SIGMOD 1997, pp. 73–88 (1997)

    Google Scholar 

  22. Iqbal, S., Bunn, J.J., Newman, H.B.: Distributed heterogeneous relational data warehouse in a grid environment. In: Proceedings of CHEP 2003 (2003), http://www.slac.stanford.edu/econf/C0303241/proc/papers/THAT007.pdf

  23. Kiran, M., Hashim, A.-H.A., Kuan, L.M., Jiun, Y.Y.: Execution time prediction of imperative paradigm tasks for grid scheduling optimization. International Journal of Computer Science and Network Security 9(2), 155–163 (2009)

    Google Scholar 

  24. Lawrence, M., Dehne, F.A., Rau-Chaplin, A.: Implementing OLAP query fragment aggregation and recombination for the OLAP enabled grid. In: Proceedings of IEEE IPDPS 2007, pp. 1–8 (2007)

    Google Scholar 

  25. Lawrence, M., Rau-Chaplin, A.: The OLAP-Enabled Grid: Model and Query Processing Algorithms. In: Proceedings of IEEE HPCS 2006, vol. 4 (2006)

    Google Scholar 

  26. Nguyen, M., Tjoa, A.M., Weippl, E., Brezany, P.: Toward a grid-based zero-latency data warehousing implementation for continuous data streams processing. International Journal of Data Warehousing and Mining 1(4), 22–55 (2005)

    Article  Google Scholar 

  27. Papazoglou, M.P., Georgakapoulos, G.: Service-oriented computing. Communications of the ACM 46(10), 24–28 (2003)

    Article  Google Scholar 

  28. Papazoglou, M.P., van den Heuvel, W.-J.: Service-oriented architectures: approaches, technologies and research issues. VLDB Journal 16(3), 389–415 (2007)

    Article  Google Scholar 

  29. Tsai, W.-T., Shao, Q., Sun, X., Elston, J.: Real-Time Service-Oriented Cloud Computing. In: Proceedings of IEEE SERVICES 2010, vol. 1, pp. 473–478 (2010)

    Google Scholar 

  30. Wehrle, P., Miquel, M., Tchounikine, A.: A grid services-oriented architecture for efficient operation of distributed data warehouses on globus. In: Proceedings of IEEE AINA 2007, pp. 994–999 (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. ICAR-CNR and University of Calabria, Italy

    Alfredo Cuzzocrea

  2. University of Technology, Australia

    Guandong Xu

Authors
  1. Alfredo Cuzzocrea
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  2. Guandong Xu
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Editor information

Editors and Affiliations

  1. TU Graz, Rechbauerstraße 12, 8010, Graz, Austria

    Robert Meersman

  2. CRAN, University of Lorraine, Campus Sciences, BP 70239, 54506, Vandoevre-les-Nancy, France

    Hervé Panetto

  3. Department of Software Engineering, Atilim Univeristy, Kızılcaşar Mh Mh, 06830, Ankara, Turkey

    Alok Mishra

  4. Facultad de Informática, Universidad de Murcia, Campus de Espinardo, 30100, Murcia, Spain

    Rafael Valencia-García

  5. Dep. of Informatics Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    António Lucas Soares

  6. SIGMA / LIG, Joseph Fourier University, 220 Rue de la Chimie, BP 53, 38041, Grenoble Cedex 9, France

    Ioana Ciuciu

  7. Institute for Research on Population and Social, National Research Council, Policies, Via Palestro 32, 00185, Rome, Italy

    Fernando Ferri

  8. Dep. Business Informatics, Communications Engineering, Johannes Kepler University, Freistaedterstrasse 315, 4040, Linz, Austria

    Georg Weichhart

  9. STINA Business Solutions GmbH, Schottenfeldgasse 63/2, 1070, Wien, Austria

    Thomas Moser

  10. SAP Research, 805 avenue du Dr Donat, 06259, Sophia-Antipolis, Mougins, France

    Michele Bezzi

  11. Department of Computing, Hong Kong Polytechnic University, PQ806, Mong Man Wai Building, Hong Kong,, China

    Henry Chan

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Cuzzocrea, A., Xu, G. (2014). A Novel Heuristic Scheme for Modeling and Managing Time Bound Constraints in Data-Intensive Grid and Cloud Infrastructures. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2014 Workshops. OTM 2014. Lecture Notes in Computer Science, vol 8842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45550-0_19

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  • DOI: https://doi.org/10.1007/978-3-662-45550-0_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45549-4

  • Online ISBN: 978-3-662-45550-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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