Processing continuous join queries in sensor networks: a filtering approach

While join processing in wireless sensor networks has received a lot of attention recently, current solutions do not work well for continuous queries. In those networks however, continuous queries are the rule. To minimize the communication costs of join processing, it is important to not ship non-joining tuples. In order to know which tuples do not join, prior work has proposed a precomputation step. For continuous queries however, repeating the precomputation for each execution is unnecessary and leaves aside that data tends to be temporally correlated. In this paper, we present a filtering approach for the processing of continuous join queries. We propose to keep the filters and to maintain them. The problems are determining the sizes of the filters and deciding which filters to update. Simplistic approaches result in bad performance. We show how to compute solutions that are optimal. Experiments on real-world sensor data indicate that our method performs close to a theoretical optimum and consistently outperforms state-of-the-art join approaches.

[1]  Wei Hong,et al.  Model-Driven Data Acquisition in Sensor Networks , 2004, VLDB.

[2]  Daniel J. Abadi,et al.  REED: Robust, Efficient Filtering and Event Detection in Sensor Networks , 2005, VLDB.

[3]  Klemens Böhm,et al.  Towards Efficient Processing of General-Purpose Joins in Sensor Networks , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[4]  Ee-Peng Lim,et al.  On In-network Synopsis Join Processing for Sensor Networks , 2006, 7th International Conference on Mobile Data Management (MDM'06).

[5]  Bin Tang,et al.  Join of Multiple Data Streams in Sensor Networks , 2009, IEEE Transactions on Knowledge and Data Engineering.

[6]  Jennifer Widom,et al.  Adaptive filters for continuous queries over distributed data streams , 2003, SIGMOD '03.

[7]  Patrick Valduriez,et al.  Principles of distributed database systems (2nd ed.) , 1999 .

[8]  D K Smith,et al.  Numerical Optimization , 2001, J. Oper. Res. Soc..

[9]  Man Lung Yiu,et al.  Retrieval of Spatial Join Pattern Instances from Sensor Networks , 2007, 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007).

[10]  David E. Culler,et al.  Taming the underlying challenges of reliable multihop routing in sensor networks , 2003, SenSys '03.

[11]  Yin Zhang,et al.  STAR: Self-Tuning Aggregation for Scalable Monitoring , 2007, VLDB.

[12]  Himanshu Gupta,et al.  Communication-Efficient Implementation of Range-Joins in Sensor Networks , 2006, DASFAA.

[13]  Charles E. Heckler,et al.  Applied Multivariate Statistical Analysis , 2005, Technometrics.

[14]  Wei Hong,et al.  TinyDB: an acquisitional query processing system for sensor networks , 2005, TODS.

[15]  Jennifer Widom,et al.  Adaptive precision setting for cached approximate values , 2001, SIGMOD '01.

[16]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[17]  Edward Y. Chang,et al.  Adaptive stream resource management using Kalman Filters , 2004, SIGMOD '04.

[18]  Mario A. Nascimento,et al.  A Distributed Algorithm for Joins in Sensor Networks , 2007, 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007).

[19]  Himanshu Gupta,et al.  Communication-efficient implementation of join in sensor networks , 2007, Ad Hoc Networks.

[20]  Philippe Bonnet,et al.  Adaptive and Decentralized Operator Placement for In-Network Query Processing , 2003, Telecommun. Syst..

[21]  Jörg Sander,et al.  On Join Location in Sensor Networks , 2007, 2007 International Conference on Mobile Data Management.

[22]  Patrick Valduriez,et al.  Principles of Distributed Database Systems , 1990 .

[23]  Kian-Lee Tan,et al.  In-network execution of monitoring queries in sensor networks , 2007, SIGMOD '07.

[24]  Himanshu Gupta,et al.  Communication-Efficient Implementation of Join in Sensor Networks , 2005, DASFAA.

[25]  H. Hindi A tutorial on convex optimization II: duality and interior point methods , 2006, 2006 American Control Conference.

[26]  Johannes Gehrke,et al.  Query Processing in Sensor Networks , 2003, CIDR.