Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Localization for mobile sensor networks
Proceedings of the 10th annual international conference on Mobile computing and networking
A MAC Protocol to Reduce Sensor Network Energy Consumption Using a Wakeup Radio
IEEE Transactions on Mobile Computing
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Energy-scalable algorithms and protocols for wireless microsensor networks
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Query Processing in Sensor Networks
IEEE Pervasive Computing
Routing techniques in wireless sensor networks: a survey
IEEE Wireless Communications
IEEE Communications Magazine
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Sensor networks have recently attracted significant attention for many military and civil applications, such as environment monitoring, target tracking, and surveillance. A high-level abstraction of sensor networks forms the distributed database view, in which query is adopted to retrieve data from the network. Sensor nodes have limited energy resources and their functionality continues until their energy drains. Therefore, query for sensor networks should be wisely designed to extend the lifetime of sensors. This paper presents a query optimization method based on user-specified delay item for wireless sensor networks. When issuing a query, user may specify a delay constraint according to which the best report time of sensor readings can be determined. Therefore at each single sensor node, combination of sensor data can be performed before transmission to sink other than immediate sending. Energy and time models of both computation and communication are created. Conditions and algorithm of performing data combination are described. The performance of the proposed algorithm is analyzed, and it shows that the method can achieve better performance than without performing the optimization.