An Energy-Efficient In-Network Join Query Processing using Synopsis and Encoding in Sensor Network

센서 네트워크에서 시놉시스와 인코딩을 이용한 에너지 효율적인 인-네트워크 조인 질의 처리

  • 여명호 (국방과학연구소) ;
  • 장용진 (충북대학교 정보통신공학과) ;
  • 김현주 (충북대학교 정보통신공학과) ;
  • 유재수 (충북대학교 정보통신공학과)
  • Received : 2010.12.23
  • Accepted : 2011.02.15
  • Published : 2011.02.28


Recently, many researchers are interested in using join queries to correlate sensor readings stored in different regions. In the conventional algorithm, the preliminary join coordinator collects the synopsis from sensor nodes and determines a set of sensor readings that are required for processing the join query. Then, the base station collects only a part of sensor readings instead of whole readings and performs the final join process. However, it has a problem that incurs communication overhead for processing the preliminary join. In this paper, we propose a novel energy-efficient in-network join scheme that solves such a problem. The proposed scheme determines a preliminary join coordinator located to minimize the communication cost for the preliminary join. The coordinator prunes data that do not contribute to the join result and performs the compression of sensor readings in the early stage of the join processing. Therefore, the base station just collects a part of compressed sensor readings with the decompression table and determines the join result from them. In the result, the proposed scheme reduces communication costs for the preliminary join processing and prolongs the network lifetime.


Sensor Networks;Join Query;In-Network;Data Compression;Data Aggregation


Supported by : 충북BIT연구중심대학육성사업단, 한국연구재단


  1. C. Intanagonwiwat, R. Govindan, and D. Estrin, "Directed diffusion: a scalable and robust communication paradigm for sensor networks", In proceedings of the 6th annual international conference on Mobile computing and networking, pp.56-67, 2000(8).
  2. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey", Computer Networks, Vol. 38, No. 4, pp.393-422, 2002(3).
  3. Y. Yao and J. Gehrke, "The cougar approach to innetwork query processing in sensor networks", SIGMOD Record, Vol.31, No.3, pp.9-18, 2002(9).
  4. S. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, "TAG: A tiny aggregation service for ad-hoc sensor networks", In proceedings of the 5th symposium on Operating systems design and implementation, pp.131-145, 2002(12).
  5. S. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, "TinyDB: an acquisitional query processing system for sensor networks”, ACM Transactions on Database Systems, Vol.30, No.1, pp.122-173, 2005(3).
  6. H. Yu, E. P. Lim, and J. Zhang, “On in-network synopsis join processing for sensor networks", In proceedings of the 7th International Conference on Mobile Data Management, pp.32-40, 2006(5).
  7. S. Nath, P. B. Gibbons, S. Seshan, and Z. R. Anderson, "Synopsis diffusion for robust aggregation in sensor networks", ACM Transactions on Sensor Networks, Vol.4, No.2, pp.1-40, 2008(3).
  8. D. J. Abadi, S. R. Madden, and W. Lindner, "REED: Robust, Efficient Filtering and Event Detection in Sensor Networks," In proceedings of the 31st international conference on Very large data bases, pp.769-780, 2005(8).
  9. B. Karp and H. T. Kung, "GPSR: Greedy Perimeter Stateless Routing for Wireless Networks," In Proceedings of the 6th annual international conference on Mobile computing and networking, pp.243-254, 2000(8).