Summary cache: a scalable wide-area web cache sharing protocol
IEEE/ACM Transactions on Networking (TON)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Adaptive filters for continuous queries over distributed data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Adaptive stream resource management using Kalman Filters
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Versatile low power media access for wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Snapshot Queries: Towards Data-Centric Sensor Networks
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Approximate Data Collection in Sensor Networks using Probabilistic Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Constraint chaining: on energy-efficient continuous monitoring in sensor networks
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Suppression and failures in sensor networks: a Bayesian approach
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
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The suppression scheme is a solution for limited energy constraints in sensor networks. Temporal suppression, spatial suppression and spatio-temporal suppression are proposed to reduce energy consumption by transmitting data only if a certain condition is violated. Among these suppression schemes, spatio-temporal suppression is the most energy efficient than others because it combines the advantages of temporal suppression and spatial suppression. A critical problem of these suppression schemes is the transmission failure because every nonreport is considered as a suppression. This causes the accuracy problem of query results. In this paper, we propose an effective and efficient method for handling transmission failures in the spatio-temporal suppression scheme. In order to detect transmission failures, we devise an energy efficient method using Bloom Filter. We also devise a novel method for recovering failed transmissions which can save energy consumption and recover failed values more accurately. The experimental evaluation shows the effectiveness of our approach. On the average, the energy consumption of our approach is about 39% less than that of a recent approach and the accuracy of the query results of our approach is about 55% more accurate than that of the recent approach in terms of the error reduction.