Randomized algorithms for optimizing large join queries
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Wireless information networks
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The cougar approach to in-network query processing in sensor networks
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Asynchronous wakeup for ad hoc networks
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The design of an acquisitional query processor for sensor networks
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Energy-Aware Routing in Cluster-Based Sensor Networks
MASCOTS '02 Proceedings of the 10th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
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OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Tuning query performance in mobile sensor databases
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Timely data delivery in sensor networks using whirlpool
DMSN '05 Proceedings of the 2nd international workshop on Data management for sensor networks
Network scheduling for data archiving applications in sensor networks
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Scalable medium access control for in-network data aggregation
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Sensor Queries: Algebraic Optimization for Time and Energy
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Comprehensive Optimization of Declarative Sensor Network Queries
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
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CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
SNEE: a query processor for wireless sensor networks
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Extending query languages for in-network query processing
Proceedings of the 10th ACM International Workshop on Data Engineering for Wireless and Mobile Access
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Queries in sensor networks are expected to produce results in a timely manner and for long periods, as needed. This implies that sensor queries need to be optimized with respect to both response time and energy consumption. With these requirements in mind, we develop novel cross-layer optimization techniques that utilize information about how the medium access control (MAC) layer operates while processing queries in large scale sensor network environments. The central framework of our approach is a Data Transmission Algebra that uniformly captures the structure of data transmissions along with their constraints and requirements. Our framework enables both qualitative analysis and quantitative cost-based optimization of sensor queries. We illustrate the effectiveness of our framework by developing a collision-aware scheduler and evaluating it experimentally.