Abstract
This paper presents OptiSource, a novel approach of source selection that reduces the number of data sources accessed during query evaluation in large scale distributed data contexts. These contexts are typical of large scale Virtual Organizations (VO) where autonomous organizations share data about a group of domain concepts (e.g. patient, gene). The instances of such concepts are constructed from non-disjointed fragments provided by several local data sources. Such sources overlap in a non mastered way making data location uncertain. This fact, in addition to the absence of reliable statistics on source contents and the large number of sources, make current proposals unsuitable in terms of response quality and/or response time. OptiSource optimizes source selection by taking advantage of organizational aspects of VOs to predict the benefit of using a source. It uses an optimization model to distinguish the sets of sources that maximize benefits and minimize the number of sources to contact to while satisfying resource constraints. The precision and recall of source selection is highly improved as demonstrated by the tests performed with the OptiSource prototype.
This research was supported by the project Ecos-Colciencias C06M02.
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References
Foster, I., Kesselman, C., Tuecke, S.: The anatomy of the grid: Enabling scalable virtual organizations. Int. J. High Perform. Comput. Appl. 15, 200–222 (2001)
NEESGrid: Nees consortium (2008), http://neesgrid.ncsa.uiuc.edu/
BIRN: Bioinformatics research network (2008), http://www.loni.ucla.edu/birn/
Levy, A.Y., Rajaraman, A., Ordille, J.J.: Querying heterogeneous information sources using source descriptions. In: VLDB 1996, Bombay, India, pp. 251–262 (1996)
Garcia-Molina, H., Papakonstantinou, Y., Quass, D., Rajaraman, A., Sagiv, Y., Ullman, J.D., Vassalos, V., Widom, J.: The tsimmis approach to mediation: Data models and languages. Journal of Intelligent Information Systems 8, 117–132 (1997)
Tomasic, A., Raschid, L., Valduriez, P.: Scaling access to heterogeneous data sources with DISCO. Knowledge and Data Engineering 10, 808–823 (1998)
Pottinger, R., Halevy, A.Y.: Minicon: A scalable algorithm for answering queries using views. VLDB J. 10, 182–198 (2001)
Doan, A., Halevy, A.Y.: Efficiently ordering query plans for data integration. In: ICDE ’02, Washington, DC, USA, p. 393. IEEE Computer Society, Los Alamitos (2002)
Huebsch, R., Hellerstein, J.M., Lanham, N., Loo, B.T., Shenker, S., Stoica, I.: Querying the internet with pier. In: VLDB 2003, pp. 321–332 (2003)
Tatarinov, I., Ives, Z., Madhavan, J., Halevy, A., Suciu, D., Dalvi, N., Dong, X.L., Kadiyska, Y., Miklau, G., Mork, P.: The piazza peer data management project. SIGMOD Rec. 32, 47–52 (2003)
Nejdl, W., Wolf, B., Qu, C., Decker, S., Sintek, M., Naeve, A., Nilsson, M., Palmér, M., Risch, T.: Edutella: a p2p networking infrastructure based on rdf. In: WWW ’02, pp. 604–615. ACM, New York (2002)
Adjiman, P., Goasdoué, F., Rousset, M.C.: Somerdfs in the semantic web. J. Data Semantics 8, 158–181 (2007)
Bleiholder, J., Khuller, S., Naumann, F., Raschid, L., Wu, Y.: Query planning in the presence of overlapping sources. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 811–828. Springer, Heidelberg (2006)
Venugopal, S., Buyya, R., Ramamohanarao, K.: A taxonomy of data grids for distributed data sharing, management, and processing. ACM Comput. Surv. 38, 3 (2006)
Wolf, G., Khatri, H., Chokshi, B., Fan, J., Chen, Y., Kambhampati, S.: Query processing over incomplete autonomous databases. In: VLDB, pp. 651–662 (2007)
Naumann, F., Freytag, J.C., Leser, U.: Completeness of integrated information sources. Inf. Syst. 29, 583–615 (2004)
Quiané-Ruiz, J.A., Lamarre, P., Valduriez, P.: Sqlb: A query allocation framework for autonomous consumers and providers. In: VLDB, pp. 974–985 (2007)
Horrocks, I.: Owl: A description logic based ontology language. In: CP, pp. 5–8 (2005)
Pomares, A., Roncancio, C., Abasolo, J., del Pilar Villamil, M.: Knowledge based query processing. In: Filipe, J., Cordeiro, J. (eds.) ICEIS. LNBIP, vol. 24, pp. 208–219. Springer, Heidelberg (2009)
Hillier, F.S., Lieberman, G.J.: Introduction to Operations Research, 8th edn. McGraw-Hill, New York (2005)
Makhorin, A.: Gnu project, gnu linear programming kit (2009), http://www.gnu.org/software/glpk/
Eric Prud, A.S.: Sparql query language for rdf (2007), http://www.w3.org/tr/rdf-sparql-query/
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Pomares, A., Roncancio, C., Cung, VD., Abásolo, J., Villamil, MdP. (2010). Source Selection in Large Scale Data Contexts: An Optimization Approach. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15364-8_4
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