Using Caching for Local Link Discovery on Large Data Sets

  • Mofeed M. Hassan
  • René Speck
  • Axel-Cyrille Ngonga Ngomo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9114)

Abstract

Engineering the Data Web in the Big Data era demands the development of time- and space-efficient solutions for covering the lifecycle of Linked Data. As shown in previous works, using pure in-memory solutions is doomed to failure as the size of datasets grows continuously with time. We present a study of caching solutions for one of the central tasks on the Data Web, i.e., the discovery of links between resources. To this end, we evaluate 6 different caching approaches on real data using different settings. Our results show that while existing caching approaches already allow performing Link Discovery on large datasets from local resources, the achieved cache hits are still poor. Hence, we suggest the need for dedicated solutions to this problem for tackling the upcoming challenges pertaining to the edification of a semantic Web.

Keywords

Caching Link discovery Semantic web Linked data 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Arlitt, M., Cherkasova, L., Dilley, J., Friedrich, R., Jin, T.: Evaluating content management techniques for web proxy caches. SIGMETRICS Performance Evaluation Review 27(4), 3–11 (2000)CrossRefGoogle Scholar
  2. 2.
    Breslau, L., Cao, P., Fan, L., Phillips, G., Shenker, S.: Web caching and zipf-like distributions: evidence and implications. In: INFOCOM, pp. 126–134 (1999)Google Scholar
  3. 3.
    Hou, W.-C., Wang, S.: Size-adjusted sliding window LFU - a new web caching scheme. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 567–576. Springer, Heidelberg (2001) CrossRefGoogle Scholar
  4. 4.
    Jin, S., Bestavros, A.: Greedydual* web caching algorithm - exploiting the two sources of temporal locality in web request streams. In: 5th International Web Caching and Content Delivery Workshop, pp. 174–183 (2000)Google Scholar
  5. 5.
    Karakostas, G., Serpanos, D.N.: Exploitation of different types of locality for web caches. In: Proceedings of the Seventh International Symposium on Computers and Communications, pp. 207–2012 (2002)Google Scholar
  6. 6.
    Karedla, R., Love, J.S., Wherry, B.G.: Caching strategies to improve disk system performance. Computer 27, 38–46 (1994)CrossRefGoogle Scholar
  7. 7.
    Lyko, K., Höffner, K., Speck, R., Ngomo, A.-C., Lehmann, J.: SAIM – one step closer to zero-configuration link discovery. In: Cimiano, P., Fernández, M., Lopez, V., Schlobach, S., Völker, J. (eds.) ESWC 2013. LNCS, vol. 7955, pp. 167–172. Springer, Heidelberg (2013) Google Scholar
  8. 8.
    Ngonga Ngomo, A.-C.: A time-efficient hybrid approach to link discovery. In: Proceedings of OM@ISWC (2011)Google Scholar
  9. 9.
    Ngonga Ngomo, A.-C.: Link discovery with guaranteed reduction ratio in affine spaces with Minkowski measures. In: Cudré-Mauroux, P., et al. (eds.) ISWC 2012, Part I. LNCS, vol. 7649, pp. 378–393. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  10. 10.
    Ngonga Ngomo, A.-C.: ORCHID – reduction-ratio-optimal computation of geo-spatial distances for link discovery. In: Alani, H., et al. (eds.) ISWC 2013, Part I. LNCS, vol. 8218, pp. 395–410. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  11. 11.
    Ngonga Ngomo, A.-C.: HELIOS – execution optimization for link discovery. In: Mika, P., et al. (eds.) ISWC 2014, Part I. LNCS, vol. 8796, pp. 17–32. Springer, Heidelberg (2014) CrossRefGoogle Scholar
  12. 12.
    Ngonga Ngomo, A.-C., Auer, S.: Limes - a time-efficient approach for large-scale link discovery on the web of data. In: Proceedings of IJCAI (2011)Google Scholar
  13. 13.
    Ngomo, A.-C.N., Kolb, L., Heino, N., Hartung, M., Auer, S., Rahm, E.: When to reach for the cloud: using parallel hardware for link discovery. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 275–289. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  14. 14.
    O’Neil, E.J., O’Neil, P.E., Weikum, G.: The lru-k page replacement algorithm for database disk buffering. SIGMOD Rec. 22, 297–306 (1993)CrossRefGoogle Scholar
  15. 15.
    Podlipnig, S., Böszörmenyi, L.: A survey of web cache replacement strategies. ACM Comput. Surv. 35(4), 374–398 (2003)CrossRefGoogle Scholar
  16. 16.
    Tanenbaum, A.S., Woodhull, A.S.: Operating systems - design and implementation, 3rd edn. Pearson Education (2006)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mofeed M. Hassan
    • 1
  • René Speck
    • 1
  • Axel-Cyrille Ngonga Ngomo
    • 1
  1. 1.AKSW, Department of Computer ScienceUniversity of LeipzigLeipzigGermany

Personalised recommendations