Efficient and robust query processing in dynamic environments using random walk techniques
Proceedings of the 3rd international symposium on Information processing in sensor networks
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
REED: robust, efficient filtering and event detection in sensor networks
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Contour map matching for event detection in sensor networks
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Scalable data aggregation for dynamic events in sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Sparse data aggregation in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Two-Tier Multiple Query Optimization for Sensor Networks
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
An energy-efficient protocol for data gathering and aggregation in wireless sensor networks
The Journal of Supercomputing
Opportunistic Aggregation over Duty Cycled Communications in Wireless Sensor Networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Asynchronous in-network prediction: Efficient aggregation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Query Processing in Sensor Networks
IEEE Pervasive Computing
Reliable and Fast Detection of Gradual Events in Wireless Sensor Networks
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Distributed Event Detection in Wireless Sensor Networks for Disaster Management
INCOS '10 Proceedings of the 2010 International Conference on Intelligent Networking and Collaborative Systems
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With the development of wireless sensor networks, more and more applications require the high data rate and real time decision making based on sensing data. In this paper, to achieve energy efficiency and quick reaction to real time event monitoring, a novel algorithms for collecting WSN data based on clustering is proposed. The algorithm depends on the similarity to cluster sensor nodes. In every cluster, only one representative node needs to report its data. Hence, the time slots of other nodes can be saved. When there is an event monitoring query offered by users, the query evaluation can return a query answer as soon as possible. Significant reaction time then can be saved. Furthermore, with the reduced reaction time, less sensor nodes are involved in the data communication, the energy efficiency can also be achieved in terms of transmission because of longer sleeping time can be guaranteed.