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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 516298, 11 pages
http://dx.doi.org/10.1155/2013/516298
Research Article

Accurate Counting Bloom Filters for Large-Scale Data Processing

1College of Information Science and Engineering, Hunan University, Changsha 410082, China
2Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China

Received 3 May 2013; Accepted 5 July 2013

Academic Editor: Gelan Yang

Copyright © 2013 Wei Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. B. B. Bloom, “Space/time tradeoffs in hash coding with allowable errors,” Communications of the ACM, vol. 13, no. 7, pp. 422–426, 1970. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Broder and M. Mitzenmacher, “Network applications of Bloom filters: a survey,” Internet Mathematics, vol. 1, no. 4, pp. 485–509, 2004. View at Google Scholar
  3. S. Tarkoma, C. E. Rothenberg, and E. Lagerspetz, “Theory and practice of bloom filters for distributed systems,” IEEE Communications Surveys and Tutorials, vol. 14, no. 1, pp. 131–155, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. L. Fan, P. Cao, J. Almeida, and A. Z. Broder, “Summary cache: a scalable wide-area Web cache sharing protocol,” IEEE/ACM Transactions on Networking, vol. 8, no. 3, pp. 281–293, 2000. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Dean and S. Ghemawat, “MapReduce: simplified data processing on large clusters,” in Proceedings of the 6th Symposium on Operating System Design and Implementation (OSDI '04), pp. 137–149, San Francisco, Calif, USA, 2004.
  6. Hadoop [EB/OL], 2012, http://hadoop.apache.org.
  7. C. Lam, Hadoop in Action, Manning Publications Press, Shelter Island, NY, USA, 2010.
  8. T. Lee, K. Kim, and H. Kim, “Join processing using Bloom filter in MapReduce,” in Proceedings of the 2012 ACM Research in Applied Computation Symposium, pp. 100–105, San Antonio, Tex, USA, 2012.
  9. F. Bonomi, M. Mitzenmacher, R. Panigrapy, S. Singh, and G. Varghese, “Beyond Bloom filters: from approximate membership checks to approximate state machines,” in Proceedings of the ACM Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM '06), pp. 315–326, Pisa, Italy, October 2006.
  10. F. Bonomi, M. Mitzenmacher, R. Panigrapy, S. Singh, and G. Varghese, “An improved construction for counting Bloom filters,” in Proceedings of the 14th Annual European Symposium on Algorithms (ESA '06), pp. 684–695, Zurich, Switzerland, September 2006.
  11. N. Hua, H. Zhao, B. Lin, and J. Xu, “Rank-indexed hashing: a compact construction of bloom filters and variants,” in Proceedings of the 16th IEEE International Conference on Network Protocols (ICNP '08), pp. 73–82, Orlando, Fla, USA, October 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. D. Ficara, S. Giordano, G. Procissi, and F. Vitucci, “MultiLayer compressed counting bloom filters,” in Proceedings of the 27th IEEE Communications Society Conference on Computer Communications (INFOCOM '08), pp. 311–315, Phoenix, Ariz, USA, April 2008. View at Scopus
  13. O. Rottenstreich, Y. Kanizo, and I. Keslassy, “The variable-increment counting Bloom filter,” in Proceedings of the 31th IEEE International Conference on Computer Communications (INFOCOM '12), pp. 1880–1888, Orlando, Fla, USA, 2012.
  14. S. Lumetta and M. Mitzenmacher, “Using the power of two choices to improve Bloom filters,” Internet Mathematics, vol. 4, no. 1, pp. 17–33, 2009. View at Google Scholar
  15. F. Hao, M. Kodialm, and T. V. Lakshman, “Building high accuracy Bloom filters using partitioned hashing,” in Proceedings of the ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS '07), pp. 277–287, San Diego, Calif, USA, 2007.
  16. A. Kirsch and M. Mitzenmacher, “Less hashing, same performance: building a better bloom filter,” Random Structures and Algorithms, vol. 33, no. 2, pp. 187–218, 2008. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Qiao, T. Li, and S. Chen, “One memory access bloom filters and their generalization,” in Proceedings of the 30th IEEE International Conference on Computer Communications (INFOCOM '11), pp. 1745–1753, Shanghai, China, April 2011. View at Publisher · View at Google Scholar · View at Scopus
  18. F. N. Afrati and J. D. Ullman, “Optimizing multiway joins in a map-reduce environment,” IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 9, pp. 1282–1298, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. S. Blanas, J. M. Patel, V. Ercegovac, J. Rao, E. J. Shekita, and Y. Tian, “A comparison of join algorithms for log processing in MaPreduce,” in Proceedings of the ACM International Conference on Management of Data (SIGMOD '10), pp. 975–986, Indianapolis, Ind, USA, June 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. NBER U.S. patent citation data file [EB/OL], 2012, http://data.nber.org/patents.