Efficient Top-k Subscription Matching for Location-Aware Publish/Subscribe

  • Jiafeng HuEmail author
  • Reynold Cheng
  • Dingming Wu
  • Beihong Jin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9239)


The dissemination of messages to a vast number of mobile users has raised a lot of attention. This issue is inherent in emerging applications, such as location-based targeted advertising, selective information disseminating, and ride sharing. In this paper, we examine how to support location-based message dissemination in an effective and efficient manner. Our main idea is to develop a location-aware version of the Pub/Sub model, which was designed for message dissemination. While a lot of studies have successfully used this model to match the interest of subscriptions (e.g., the properties of potential customers) and events (e.g., information of casual users), the issues of incorporating the location information of subscribers and publishers have not been well addressed. We propose to model subscriptions and events by boolean expressions and location data. This allows complex information to be specified. However, since the number of publishers and subscribers can be enormous, the time cost for matching subscriptions and events can be prohibitive. To address this problem, we have developed the \(R^I\)-tree. This data structure is an integration of the R-tree and the dynamic interval-tree. Together with our novel pruning strategy on \(R^I\)-tree, our solution can effectively and efficiently return the top-k subscriptions with respect to an event. We have performed extensive evaluations to verify our approach.


Leaf Node Index Structure Priority Queue Conjunctive Normal Form Boolean Expression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Jiafeng Hu and Reynold Cheng were supported by the Research Grants Council of Hong Kong (RGC Project (HKU 711110)). Dingming Wu was supported by HKU 714712E. Beihong Jin was supported by the National Natural Science Foundation of China under Grant No. 61472408 and the Opening Foundation of Beijing Key Lab of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications.


  1. 1.
    Chen, L., Cong, G., Jensen, C.S., Wu, D.: Spatial keyword query processing: an experimental evaluation. In: PVLDB’2013, pp. 217–228. VLDB Endowment (2013)Google Scholar
  2. 2.
    Chen, L., Cong, G., Cao, X., Tan, K.-L.: Temporal spatial-keyword top-k publish/subscribe. In: ICDE 2015, pp. 255–266 (2015)Google Scholar
  3. 3.
    Cheng, Z., Caverlee, J., Lee, K., Sui, D.Z.: Exploring millions of footprints in location sharing services. In: ICWSM 2011, pp. 81–88 (2011)Google Scholar
  4. 4.
    Cong, G., Jensen, C.S., Wu, D.: Efficient retrieval of the top-k most relevant spatial web objects. In: VLDB 2009, vol. 2, pp. 337–348 (2009)Google Scholar
  5. 5.
    de Berg, M., van Kreveld, M., Overmars, M., Schwarzkopf, O.: Computational Geometry: Algorithms and Applications. Springer-Verlag, Heidelberg (2000)CrossRefGoogle Scholar
  6. 6.
    Eugster, P.T., Felber, P.A., Guerraoui, R., Kermarrec, A.-M.: The many faces of publish/subscribe. ACM Comput. Surv. 35(2), 114–131 (2003)CrossRefGoogle Scholar
  7. 7.
    Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. In: PODS 2001, pp. 102–113. ACM, NY, USA (2001)Google Scholar
  8. 8.
    Fontoura, M., et al.: Efficiently evaluating complex boolean expressions. In: SIGMOD 2010, pp. 3–14. ACM, NY, USA (2010)Google Scholar
  9. 9.
    Guo, L., Zhang, D., Li, G., Tan, K.-L., Bao, Z.: Location-aware pub/sub system: When continuous moving queries meet dynamic event streams. In: SIGMOD 2015, pp. 843-857. ACM (2015)Google Scholar
  10. 10.
    Guttman. A.: R-trees: a dynamic index structure for spatial searching. In SIGMOD 1984, pp. 47–57. ACM, NY, USA (1984)Google Scholar
  11. 11.
    Hu, H., Liu, Y., Li, G., Feng, J., Tan, K.-L.: A location-aware publish/subscribe framework for parameterized spatio-textual subscriptions. In: ICDE 2015, pp. 711–722 (2015)Google Scholar
  12. 12.
    Kaplan, H., Molad, E., Tarjan, R.E.: Dynamic rectangular intersection with priorities. In: STOC 2003, p. 639. ACM Press, New York, June 2003Google Scholar
  13. 13.
    Li, G., Wang, Y., Wang, T., Feng, J.: Location-aware publish/subscribe. In: KDD 2013, pp. 802–810. ACM Press, New York (2013)Google Scholar
  14. 14.
    Machanavajjhala, A., Vee, E., Garofalakis, M., Shanmugasundaram, J.: Scalable ranked publish/subscribe. In: VLDB 2008, vol. 1, issue no. 1, pp. 451–462, August 2008Google Scholar
  15. 15.
    Mehlhorn, K.: Data structures and algorithms 3: Multi-dimensional Searching and Computational Geometry. Monographs in Theoretical Computer Science. An EATCS Series. Springer, Heidelberg (1984)zbMATHCrossRefGoogle Scholar
  16. 16.
    Sadoghi, M., Jacobsen, H.-A.: Be-tree: an index structure to efficiently match boolean expressions over high-dimensional discrete space. In: SIGMOD 2011, pp. 637-648. ACM (2011)Google Scholar
  17. 17.
    Sadoghi, M., Jacobsen, H.-A.: Relevance matters: Capitalizing on less (top-k matching in publish/subscribe). In: ICDE 2012, pp. 786–797 (2012)Google Scholar
  18. 18.
    Whang, S.E., Garcia-Molina, H., Brower, C. J. Shanmugasundaram, S. Vassilvitskii, E. Vee, and R. Yerneni. Indexing boolean expressions. In: VLDB 2009, vol. 2, issue no. 1, pp. 37–48 (2009)Google Scholar
  19. 19.
    Yu, M., Li, G., Wang, T., Feng, J., Gong, Z.: Efficient filtering algorithms for location-aware publish/subscribe. IEEE TKDE 27(4), 950–963 (2015)Google Scholar
  20. 20.
    Zhang, D., Chan, C.-Y., Tan, K.-L.: An efficient publish/subscribe index for e-commerce databases. In: Proceedings VLDB Endow, vol. 7, issue no. 8, pp. 613–624 (2014)Google Scholar
  21. 21.
    Zhang, D., Tan, K.-L., Tung, A.K.H.: Scalable top-k spatial keyword search. In: EDBT 2013, pp. 359–370. ACM Press, New York, USA (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jiafeng Hu
    • 1
    Email author
  • Reynold Cheng
    • 1
  • Dingming Wu
    • 1
  • Beihong Jin
    • 2
  1. 1.Department of Computer ScienceThe University of Hong KongHong KongChina
  2. 2.State Key Laboratory of Computer ScienceInstitute of Software, Chinese Academy of SciencesBeijingChina

Personalised recommendations