The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.12 - December (2009 vol.21)
pp: 1722-1736
Himanshu Gupta , Stony Brook University, Stony Brook
Xianjin Zhu , Microsoft, Inc., Seattle
ABSTRACT
Sensor networks are multihop wireless networks of resource-constrained sensor nodes used to realize high-level collaborative sensing tasks. To query or access data generated by the sensor nodes, the sensor network can be viewed as a distributed database. In this paper, we develop algorithms for communication-efficient implementation of join of multiple (two or more) data streams in a sensor network. The distributed implementation of join in sensor networks is particularly challenging due to unique characteristics of the sensor networks such as limited memory and battery energy on individual nodes, arbitrary and dynamic network topology, multihop communication, and unreliable infrastructure. One of our proposed approaches, viz., the Perpendicular Approach (PA), is load balanced, and in fact, incurs near-optimal communication cost for the special case of binary joins in grid networks under the assumption of uniform generation of tuples across the network. We compare the performance of our designed approaches through extensive simulations on the ns2 simulator, and show that PA results in substantially prolonging the network lifetime compared to other approaches, especially for joins involving spatial constraints.
INDEX TERMS
Distributed query processing, Sensor networks.
CITATION
Himanshu Gupta, Xianjin Zhu, "Join of Multiple Data Streams in Sensor Networks", IEEE Transactions on Knowledge & Data Engineering, vol.21, no. 12, pp. 1722-1736, December 2009, doi:10.1109/TKDE.2009.38
REFERENCES
[1] D. Abadi, S. Madden, and W. Lindner, “REED: Robust, Efficient Filtering and Event Detection in Sensor Networks,” Proc. Int'l Conf. Very Large Data Bases (VLDB), 2005.
[2] A. Arasu, S. Babu, and J. Widom, “The CQL Continuous Query Language: Semantic Foundations and Query Execution,” Very Large Data Base J., vol. 15, pp. 121-142, 2006.
[3] B. Babcock, S. Babu, M. Datar, R. Motwani, and J. Widom, “Models and Issues in Data Stream Systems,” Proc. ACM Symp. Principles of Database Systems (PODS), 2002.
[4] B. Bonfils and P. Bonnet, “Adaptive and Decentralized Operator Placement for In-Network Query Processing,” Proc. Int'l Workshop Information Processing in Sensor Networks (IPSN), 2003.
[5] P. Bonnet, J. Gehrke, and P. Seshadri, “Towards Sensor Database Systems,” Proc. Int'l Conf. Mobile Data Management (MDM), 2001.
[6] J. Chen, D.J. DeWitt, F. Tian, and Y. Wang, “NiagaraCQ: A Scalable Continuous Query System for Internet Databases,” Proc. ACM SIGMOD Conf., 2000.
[7] S. Cheung, M. Ammar, and M. Ahamad, “The Grid Protocol: A High Performance Scheme for Maintaining Replicated Data,” Proc. Int'l Conf. Database Eng. (ICDE), 1990.
[8] V. Chowdhary and H. Gupta, “Communication-Efficient Implementation of Join Operation in Sensor Networks,” Proc. Int'l Conf. Database Systems for Advanced Applications (DASFAA), 2005.
[9] D. Chu, L. Popa, A. Tavakoli, J. Hellerstein, P. Levis, S. Shenker, and I. Stoica, “The Design and Implementation of a Declarative Sensor Network System,” Proc. Int'l Conf. Embedded Networked Sensor Systems (SenSys), 2007.
[10] A. Das, J. Gehrke, and M. Riedewald, “Approximate Join Processing over Data Streams,” Proc. ACM SIGMOD Conf., 2003.
[11] M. Datar, P. Indyk, N. Immorlica, and V. Mirrokni, “Locality-Sensitive Hashing Scheme Based on P-Stable Distributions,” Proc. ACM Symp. Computation Geometry (SoCG), 2004.
[12] A. Deshpande, C. Guestrin, S. Madden, J. Hellerstein, and W. Hong, “Model-Based Approximation Querying in Sensor Networks,” Very Large Data Base J., vol. 14, pp. 417-443, 2005.
[13] L. Ding, N. Mehta, E. Rundensteiner, and G. Heineman, “Joining Punctuated Streams,” Proc. Int'l Conf. Extending Database Technology (EDBT), 2004.
[14] D. Abadi et al., “Aurora: A New Model and Architecture for Data Stream Management,” Very Large Data Base J., vol. 12, pp. 120-139, 2003.
[15] D. Abadi et al., “The Design of the Borealis Stream Processing Engine,” Proc. Int'l Conf. Innovative Data Systems Research (CIDR), 2005.
[16] S. Chandrasekaran et al., “TelegraphCQ: Continuous Dataflow Processing,” Proc. ACM SIGMOD Conf., 2003.
[17] S. Madden et al., “TinyDB: In-Network Query Processing in TinyOS,” http://telegraph.cs.berkeley.edutinydb, 2009.
[18] The ns Manual, K. Fall and K. Varadhan, eds., http://www-mash.cs.berkeley.eduns, 2009.
[19] L. Golab and M. Ozsu, “Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams,” Proc. Int'l Conf. Very Large Data Bases (VLDB), 2003.
[20] R. Govindan, J. Hellerstein, W. Hong, S. Madden, M. Franklin, and S. Shenker, “The Sensor Network as a Database,” technical report, Univ. of Southern California, 2002.
[21] L. Guibas, “Sensing, Tracking, and Reasoning with Relations,” IEEE Signal Processing Magazine, vol. 19, no. 2, pp. 73-85, Mar. 2002.
[22] H. Gupta, V. Navda, S. Das, and V. Chowdhary, “Energy-Efficient Gathering of Correlated Data in Sensor Networks,” Proc. MobiHoc, 2005.
[23] H. Gupta, X. Zhu, and X. Xu, “Deductive Approach for Programming Sensor Networks,” Proc. Int'l Conf. Database Eng. (ICDE), 2009.
[24] M. Hammad, W. Aref, and A. Elmagarmid, “Stream Window Join: Tracking Moving Objects in Sensor-Network Databases,” Proc. Int'l Conf. Scientific and Statistical Database Management (SSDBM), 2003.
[25] J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, and D. Ganesan, “Building Efficient Wireless Sensor Networks with Low-Level Naming,” Proc. Symp. Operating Systems Principles (SOSP), 2001.
[26] T. Ibaraki and T. Kameda, “On the Optimal Nesting Order for Computing N-Relational Joins,” ACM Trans. Database Systems (TODS), 1984.
[27] J. Kang, J. Naughton, and S. Viglas, “Evaluating Window Joins over Unbounded Streams,” Proc. Int'l Conf. Database Eng. (ICDE), 2003.
[28] B. Karp and H.T. Kung, “Greedy Perimeter Stateless Routing for Wireless Networks,” Proc. MobiCom, 2000.
[29] S. Li, Y. Lin, S. Son, J. Stankovic, and Y. Wei, “Event Detection Services Using Data Service Middleware in Distributed Sensor Networks,” Telecomm. Systems, special issue on wireless sensor networks, vol. 26, pp. 351-368, 2004.
[30] X. Liu, Q. Huang, and Y. Zhang, “Combs, Needles, Haystacks: Balancing Push and Pull for Discovery in Sensor Networks,” Proc. Int'l Conf. Embedded Networked Sensor Systems (SenSys), 2004.
[31] H. Lu, M. Shan, and K. Tan, “Optimization of Multi-Way Join Queries for Parallel Execution,” Proc. Int'l Conf. Very Large Data Bases (VLDB), 1991.
[32] M. Srivastava, “Power Considerations for Sensor Networks,” http://ipsn.acm.org/2001/slidesSrivastava.pdf , 2009.
[33] S. Madden and M. Franklin, “Fjording the Stream: An Architecture for Queries over Streaming Sensor Data,” Proc. Int'l Conf. Database Eng. (ICDE), 2002.
[34] S. Madden, M. Franklin, J. Hellerstein, and W. Hong, “TAG: A Tiny Aggregation Service for Ad-Hoc Sensor Networks,” Proc. Symp. Operating Systems Design and Implementation (OSDI), 2002.
[35] S. Madden, M. Franklin, J. Hellerstein, and W. Hong, “The Design of an Acquisitional Query Processor for Sensor Networks,” Proc. ACM SIGMOD Conf., 2003.
[36] S. Madden and J.M. Hellerstein, “Distributing Queries over Low-Power Wireless Sensor Networks,” Proc. ACM SIGMOD Conf., 2002.
[37] R. Motwani, J. Widom, A. Arasu, B. Babcock, S. Babu, M. Datar, G. Manku, C. Olston, J. Rosenstein, and R. Varma, “Query Processing, Approximation, and Resource Management in a Data Stream Management System,” Proc. Int'l Conf. Innovative Data Systems Research (CIDR), 2003.
[38] A. Pandit and H. Gupta, “Efficient Implementation of Range-Joins in Sensor Networks,” Proc. Int'l Conf. Database Systems for Advanced Applications (DASFAA), 2006.
[39] S. Patil, S. Das, and A. Nasipuri, “Serial Data Fusion Using Space-Filling Curves in Wireless Sensor Networks,” Proc. Int'l Conf. Sensor and Ad Hoc Comm. and Networks (SECON), 2004.
[40] S. Ratnasamy, B. Karp, S. Shenker, D. Estrin, R. Govindan, L. Yin, and F. Yu, “Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table,” Mobile Networks and Applications, vol. 8, no. 4, pp. 427-442, 2003.
[41] J. Richardson, H. Lu, and K. Mikkilineni, “Design and Evaluation of Parallel Pipelined Join Algorithms,” Proc. ACM SIGMOD Conf., 1987.
[42] R. Sarkar, X. Zhu, and J. Gao, “Double Rulings for Information Brokerage in Sensor Networks,” Proc. MobiCom, 2006.
[43] A. Savvides, M. Srivastava, L. Girod, and D. Estrin, “Localization in Sensor Networks,” Wireless Sensor Networks, Kluwer Academic Publishers, 2004.
[44] D. Schneider and D. DeWitt, “A Performance Evaluation of Four Parallel Join Algorithms in a Shared-Nothing Multiprocessor Environment,” Proc. ACM SIGMOD Conf., 1989.
[45] U. Srivastava, K. Munagala, and J. Widom, “Operator Placement for In-Network Stream Query Processing,” Proc. ACM Symp. Principles of Database Systems (PODS), 2005.
[46] U. Srivastava and J. Widom, “Memory-Limited Execution of Windowed Stream Joins,” Proc. Int'l Conf. Very Large Data Bases (VLDB), 2004.
[47] K. Tan and H. Lu, “Processing Multi-Join Query in Parallel Systems,” Proc. Symp. Applied Computing, 1992.
[48] Y. Xing, J. Hwang, U. Cetintemel, and S. Zdonik, “Providing Resiliency to Load Variations in Distributed Stream Processing,” Proc. Int'l Conf. Very Large Data Bases (VLDB), 2006.
[49] T.W. Yan and H. Garcia-Molina, “The SIFT Information Dissemination System,” ACM Trans. Database Systems (TODS), vol. 24, pp. 529-565, 1999.
[50] S. Yang, J. Wu, and J. Cao, “Connected $k$ -Hop Clustering in Ad Hoc Networks,” Proc. Int'l Conf. Parallel Processing (ICPP), 2005.
[51] Y. Yao and J. Gehrke, “The Cougar Approach to In-Network Query Processing in Sensor Networks,” ACM SIGMOD Record, vol. 31, no. 3, pp. 9-18, 2002.
[52] Y. Yao and J. Gehrke, “Query Processing in Sensor Networks,” Proc. Int'l Conf. Innovative Data Systems Research (CIDR), 2003.
21 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool