An Approximation Algorithm for Optimizing Multiple Path Tracking Queries over Sensor Data Streams
Pages 532 - 546
Abstract
Sensor networks have received considerable attention in recent years and played an important role in data collection applications. Sensor nodes have limited supply of energy. Therefore, one of the major design considerations for sensor applications is to reduce the power consumption. In this paper, we study an application that combines RFID and sensor network technologies to provide an environment for moving object path tracking, which needs efficient join processing. This paper considers multi-query optimization to reduce query evaluation cost, and therefore power consumption. We formulate the multi-query optimization problem and present a novel approximation algorithm which provides solutions with suboptimal guarantees. In addition, extensive experiments are made to demonstrate the performance of the proposed optimization strategy.
References
[1]
Viglas, S., Naughton, J.F., Burger, J.: Maximizing the output rate of multi-way join queries over streaming information sources. In: Proc. of the Intl. Conf. on Very Large Data Bases, pp. 285-296 (2003).
[2]
Babu, S., et al.: Adaptive ordering of pipeline stream filters. In: Proc. of the ACM SIGMOD Conf. on Management of Data, pp. 407-418 (2004).
[3]
Balas, E., Padberg, M.: Set partition: a survey. SIAM review (18), 710-760 (1976).
[4]
Han, J., Kamber, M.: Data Mining Concepts and Techniques. Morgan Kaufmann, San Francisco (2001).
[5]
Motwani, R., Raghavan, P.: Randomized Algorithms. Cambridge Press (1995).
[6]
Levis, P., Gay, D.: Maté: a tiny virtual machine for sensor networks. In: Proc. of Intl. Conf. on Architectural Support for Programming Languages and Operating Systems, pp. 85-95 (2002).
[7]
Hammad, M.A., et al.: Scheduling for shared window joins over data streams. In: Proc. of the Intl. Conf. on Very Large Data Bases, pp. 297-308 (2003).
[8]
Cranor, C.D., et al.: Gigascope: a stream database for network application. In: Proc. of the ACM SIGMOD Conf. on Management of Data, pp. 647-651 (2003).
[9]
Srivastava, D., et al.: Multiple aggregations over data streams. In: Proc. of the ACM SIGMOD Conf. on Management of Data, pp. 299-310 (2005).
[10]
Chandrasekaran, S., Franklin, M.J.: Streaming Queries over Streaming Data. In: Proc. of the Intl. Conf. on Very Large Data Bases, pp. 203-214 (2002).
[11]
Madden, S., et al.: Continuously Adaptive Continuous Queries over Streams. In: Proc. of the ACM SIGMOD Conf. on Management of Data, pp. 49-60 (2002).
[12]
Krishnamurthy, S., et al.: On-the-fly sharing for streamed aggregation. In: Proc. of the ACM SIGMOD Conf. on Management of Data, pp. 623-634 (2006).
[13]
Huebsch, R., et al.: Sharing aggregate computation for distributed queries. In: Proc. of the Intl. Conf. on Very Large Data Bases (2007).
[14]
Yao, Y., Gehrke, J.: Query processing in sensor networks. In: Proc. of Intl. Conf. on Innovative Data Systems Research (2003).
[15]
Madden, S., et al.: TAG: a tiny aggregation service for ad-hoc sensor networks. In: Proc. of Annual Symps. on Operating System Design and Implementation, pp. 131-146 (2002).
[16]
Madden, S., et al.: TinyDB: an acquisitional query processing system for sensor networks. ACM Trans. on Database Systems 30(1), 122-173 (2005).
[17]
Trigoni, N., et al.: Multi-query optimization for sensor networks. In: Proc. of Intl. Conf. on Distributed Computing in Sensor Systems, pp. 301-321 (2005).
[18]
Müller, R., Alonso, G.: Efficient sharing of sensor networks. In: Proc. of Intl. Conf. on Mobile Ad-hoc and Sensor Systems, pp. 101-118 (2005).
[19]
Xian, S., et al.: Two-Tier Multiple query optimization for sensor networks. In: Proc. of the IEEE Intl. Conf. Distributed Computing System, pp. 39-47 (2007).
- An Approximation Algorithm for Optimizing Multiple Path Tracking Queries over Sensor Data Streams
Recommendations
Processing Ad-Hoc Queries in Wireless Sensor Networks
ITNG '08: Proceedings of the Fifth International Conference on Information Technology: New GenerationsA wireless sensor network (WSN) consists of a large number of sensor nodes that can measure and process data while communicating through wireless channels. In this paper, we propose a hybrid query processing (HQP) algorithm for user queries submitted to ...
TWINS: Efficient time-windowed in-network joins for sensor networks
Wireless sensor networks (WSNs) have recently received a lot of attention and several techniques have been proposed for in-network join processing. Since sensor readings are continuously collected and it is interesting to track the relationships between ...
Cost based in-network join strategy in tree routing sensor networks
The tiny and smart sensors enable applications which access a network of hundreds or thousands of sensors. In many applications, joins are used frequently to find relationships of readings of different sensors such as the correlation of sensor readings ...
Comments
Information & Contributors
Information
Published In
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 25 August 2009
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 03 Feb 2025