E\(^2\)STA: An Energy-Efficient Spatio-Temporal Query Algorithm for Wireless Sensor Networks

  • Liang Liu
  • Zhe XuEmail author
  • Yi-Ting Wang
  • Xiao-Lin Qin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11342)


After wireless sensor networks are deployed, spatio-temporal query is frequently submitted by users to obtain all the sensor readings of an area of interest in a period of time. Most of existing spatio-temporal query processing algorithms organized all the nodes in the whole network or the nodes in the query area into a single routing tree guided by which the sensor readings of the nodes in the query area are sent back to the sink. This study attempts to answer the following two questions: first, is it feasible to processing spatio-temporal query by multiple routing trees? Second, for the single tree based algorithms and the multiple trees based algorithms, which one outperforms the other? We pointed out that the path along which the query results are sent back to the sink is fairly long when a single routing tree is adopted, which leads to a large amount of energy consumption. Organizing the nodes in the query area into multiple routing trees can avoid this problem. Based on the above findings, we designed a protocol of constructing multiple routing trees for the nodes in the query area, and proposed an energy-efficient spatio-temporal query processing algorithm called E\(^2\)STA. Theoretical and experimental results show that the proposed algorithm based on multiple routing trees outperforms the existing algorithms based on one single routing tree in terms of energy consumption.


Wireless sensor networks Query processing Spatio-temporal query Energy-efficiency 



This work is supported by the National Natural Science Foundation of China under Grant No. (61402225, 61373015, 41301407), the National Natural Science Foundation of Jiangsu Province under Grant No. BK20140832, the China Postdoctoral Science Foundation under Grant No. 2013M540447, the Jiangsu Postdoctoral Science Foundation under Grant No. 1301020C, State Key Laboratory for smart grid protection and operation control Foundation, Science and Technology Funds from National Electric Net Ltd. (The Research on Key Technologies of Distributed Parallel Database Storage and Processing based on Big Data), the Foundation of Graduate Innovation Center in NUAA under Grant No. kfjj20181608.


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjingChina

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