An Efficient Location-Aware Top-k Subscription Matching for Publish/Subscribe with Boolean Expressions

  • Hanhan Jiang
  • Pengpeng Zhao
  • Victor S. Sheng
  • Jiajie Xu
  • An Liu
  • Jian Wu
  • Zhiming Cui
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9643)


Location-aware publish/subscribe (pub/sub) has attracted a lot of attentions with the booming of mobile Internet technologies and the rising popularity of smart-phones. Subscribers subscribe their interests with their locations as subscriptions, and publishers publish geo-information as events. Many state-of-art applications with a massive amount of geo-information, such as location-aware targeted advertising systems, face this situation. Existing related work mainly focuses on unstructured geo-textual information. However, many online-to-offline applications have enormous geo-information with different structured descriptions. To handle such structured information, a new type of location-aware pub/sub approach is needed. In this paper, we handle these subscriptions using boolean expressions. Since the number of publishers and subscribers can be enormous, it is extremely important to improve the matching effectiveness and efficiency of top-k query processing. In this paper, we develop a novel solution named RR\(^t\)-trees. RR\(^t\)-trees integrates \(R^t\)-tree and a predicate index structure together to return top-k best matched subscriptions from a great number of events. Our experimental results on synthetic and real-world datasets show that RR\(^t\)-trees achieve better performance than baseline methods.


Location-aware pub/sub Top-k Boolean expressions 



This work was partially supported by Chinese NSFC project (61472263, 61402312, 61402311), and the US National Science Foundation (IIS-1115417).


  1. 1.
    Chen, L., Cong, G., Cao, X., Tan, K.L.: Temporal spatial-keyword top-k publish/subscribe. In: 2015 IEEE 31st International Conference on Data Engineering (ICDE), pp. 255–266 (2015)Google Scholar
  2. 2.
    Cugola, G., Margara, A.: High-performance location-aware publish-subscribe on GPUs. In: Narasimhan, P., Triantafillou, P. (eds.) Middleware 2012. LNCS, vol. 7662, pp. 312–331. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Eugster, G.: Location-based publish/subscribe. In: 2013 IEEE 12th International Symposium on Network Computing and Applications, pp. 279–282 (2005)Google Scholar
  4. 4.
    Fontoura, M., Sadanandan, S., Shanmugasundaram, J., Vassilvitski, S., Vee, E., Venkatesan, S., Zien, J.: Efficiently evaluating complex Boolean expressions. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, pp. 3–14. ACM (2010)Google Scholar
  5. 5.
    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: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 843–857. ACM (2015)Google Scholar
  6. 6.
    Hu, H., Liu, Y., Li, G., Feng, J., Tan, K.L.: A location-aware publish/subscribe framework for parameterized spatio-textual subscriptions. ICDE 2015, 711–722 (2015)Google Scholar
  7. 7.
    Hu, J., Cheng, R., Wu, D., Jin, B.: Efficient top-k subscription matching for location-aware publish/subscribe. In: Claramunt, C., Schneider, M., Wong, R.C.-W., Xiong, L., Loh, W.-K., Shahabi, C., Li, K.-J. (eds.) SSTD 2015. LNCS, vol. 9239, pp. 333–351. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  8. 8.
    Li, G., Wang, Y., Wang, T., Feng, J.: Location-aware publish/subscribe. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 802–810. ACM (2013)Google Scholar
  9. 9.
    Machanavajjhala, A., Vee, E., Garofalakis, M., Shanmugasundaram, J.: Scalable ranked publish/subscribe. Proc. VLDB Endow. 1(1), 451–462 (2008)CrossRefGoogle Scholar
  10. 10.
    Sadoghi, M., Jacobsen, H-.A.: Relevance matters: Capitalizing on less (top-k matching in publish/subscribe). In: 2012 IEEE 28th International Conference on Data Engineering, pp. 786–797 (2012)Google Scholar
  11. 11.
    Sadoghi, M., Burcea, I., H.a.J: Gpx-matcher: A generic Boolean predicate-based xpath expression matcher. In: EDBT 2011, pp. 45–56 (2011)Google Scholar
  12. 12.
    Sadoghi, M., Jacobsen, H.-A.: Be-tree: an index structure to efficiently match Boolean expressions over high-dimensional discrete space. In: ACM Conference on Management of Data, pp. 637–648 (2011)Google Scholar
  13. 13.
    Sadoghi, M., Jacobsen, H.A.: Location-based matching in publish/subscribe revisited. In: Proceedings of the Posters and Demo Track, p. 9. ACM (2012)Google Scholar
  14. 14.
    Shang, S., Deng, K., Xie, K.: Best point detour query in road networks. pp. 71–80. In: ACM (2010)Google Scholar
  15. 15.
    Shang, S., Ding, R., Yuan, B., Xie, K., Zheng, K., Kalnis, P.: User oriented trajectory search for trip recommendation. In: 15th International Conference on Extending Database Technology, EDBT 2012, pp. 156–167 (2012)Google Scholar
  16. 16.
    Shang, S., Ding, R., Zheng, K., Jensen, C.S., Kalnis, P., Zhou, X.: Personalized trajectory matching in spatial networks. VLDB J. 23(3), 449–468 (2014)CrossRefGoogle Scholar
  17. 17.
    Shang, S., Yuan, B., Deng, K., Xie, K., Zheng, K., Zhou, X.: PNN query processing on compressed trajectories. Geoinformatica 16(3), 467–496 (2012)CrossRefGoogle Scholar
  18. 18.
    Whang, S.E., Garcia-Molina, H., Brower, C., Shanmugasundaram, J., Vassilvitskii, S., Vee, E., Yerneni, R.: Indexing Boolean expressions. Proc. VLDB Endow. 2(1), 37–48 (2009)CrossRefGoogle Scholar
  19. 19.
    Xiang Wang, Y.Z., Xuemin Line, W.W.: Ap-tree: Efficiently support continuous spatial-keyword queries over stream. In: 2015 IEEE 31st International Conference on Data Engineering (ICDE), pp. 1107–1118 (2015)Google Scholar
  20. 20.
    Yu, M., Li, G., Wang, T., Feng, J., Gong, Z.: Efficient filtering algorithms for location-aware publish/subscribe. IEEE Trans. Knowl. Data Eng. 27(4), 950–963 (2015)CrossRefGoogle Scholar
  21. 21.
    Zhang, D., Chan, C.Y., Tan, K.L.: An efficient publish/subscribe index for e-commerce databases. Proc. VLDB Endow. 7(8), 613–624 (2014)CrossRefGoogle Scholar
  22. 22.
    Zheng, B., Yuan, N.J., Zheng, K., Xie, X., Sadiq, S., Zhou, X.: Approximate keyword search in semantic trajectory database. In: 2015 IEEE 31st International Conference on Data Engineering (ICDE), pp. 975–986. IEEE (2015)Google Scholar
  23. 23.
    Zheng, K., Huang, Z., Zhou, X., et al.: Discovering the most influential sites over uncertain data: a rank based approach. IEEE Trans. Knowl. Data Eng. 99, 1 (2011)Google Scholar
  24. 24.
    Zheng, K., Zhou, X., Fung, P.C., Xie, K.: Spatial query processing for fuzzy objects. VLDB J. 21, 729–751 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Hanhan Jiang
    • 1
  • Pengpeng Zhao
    • 1
    • 2
  • Victor S. Sheng
    • 3
  • Jiajie Xu
    • 1
    • 2
  • An Liu
    • 1
    • 2
  • Jian Wu
    • 1
    • 2
  • Zhiming Cui
    • 1
    • 2
  1. 1.School of Computer Science and TechnologySoochow UniversitySuzhouChina
  2. 2.Collaborative Innovation Center of Novel Software Technology and IndustrializationSuzhouChina
  3. 3.Computer Science DepartmentUniversity of Central ArkansasConwayUSA

Personalised recommendations