An energy-efficient querying framework in sensor networks for detecting node similarities
Proceedings of the 9th ACM international symposium on Modeling analysis and simulation of wireless and mobile systems
Top-k Monitoring in Wireless Sensor Networks
IEEE Transactions on Knowledge and Data Engineering
BiSNET: A biologically-inspired middleware architecture for self-managing wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
ASAP: An Adaptive Sampling Approach to Data Collection in Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
An energy-efficient data-driven power management for wireless sensor networks
Proceedings of the 5th workshop on Data management for sensor networks
IEEE/ACM Transactions on Networking (TON)
Energy conservation in wireless sensor networks: A survey
Ad Hoc Networks
Silent networking for energy-constrained nodes
Computer Communications
A model-driven approach for data collection in sensor networks
PDCN '08 Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Networks
An index-based privacy preserving service trigger in context-aware computing environments
Expert Systems with Applications: An International Journal
Quality-aware sensor data collection
International Journal of Sensor Networks
Journal of Real-Time Image Processing
Processing continuous top-k data collection queries in lifetime-constrained wireless sensor networks
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Stochastically consistent caching and dynamic duty cycling for erratic sensor sources
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
PAQ: time series forecasting for approximate query answering in sensor networks
EWSN'06 Proceedings of the Third European conference on Wireless Sensor Networks
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Sensors are typically deployed to gather data about the physical world and its artifacts for a variety of purposes that range from environment monitoring, control, to data analysis. Since sensors are resource constrained, often sensor data is collected into a sensor database that resides at (more powerful) servers. A natural tradeoff exists between the sensor resources (bandwidth, energy) consumed and the quality of data collected at the server. Blindly transmitting sensor updates at a .xed periodicity to the server results in a suboptimal solution due to the differences in stability of sensor values and due to the varying application needs that impose different quality requirements across sensors. This paper proposes adaptive data collection mechanisms for sensor environments that adjusts to these variations while at the same time optimizing the energy consumption of sensors. Our experimental results show significant energy savings compared to the naive approach to data collection.