Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Wireless Sensor Networks: An Information Processing Approach
Wireless Sensor Networks: An Information Processing Approach
Backcasting: adaptive sampling for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
A Survey on Data Compression in Wireless Sensor Networks
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
Near-optimal sensor placements in Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Countersniper system for urban warfare
ACM Transactions on Sensor Networks (TOSN)
Near-optimal sensor placements: maximizing information while minimizing communication cost
Proceedings of the 5th international conference on Information processing in sensor networks
Deploying a Wireless Sensor Network on an Active Volcano
IEEE Internet Computing
Monitoring Civil Structures with a Wireless Sensor Network
IEEE Internet Computing
VigilNet: An integrated sensor network system for energy-efficient surveillance
ACM Transactions on Sensor Networks (TOSN)
A utility-based sensing and communication model for a glacial sensor network
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Decentralized, adaptive resource allocation for sensor networks
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Power management in energy harvesting sensor networks
ACM Transactions on Embedded Computing Systems (TECS) - Special Section LCTES'05
Adaptive sampling in the COlumbia RIvEr observation network
Proceedings of the 5th international conference on Embedded networked sensor systems
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Gaussian Process Models for Censored Sensor Readings
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Convergence of probability collectives with adaptive choice of temperature parameters
LION'10 Proceedings of the 4th international conference on Learning and intelligent optimization
Benchmarking hybrid algorithms for distributed constraint optimisation games
Autonomous Agents and Multi-Agent Systems
Practical data compression in wireless sensor networks: A survey
Journal of Network and Computer Applications
The Knowledge Engineering Review
Autonomous Agents and Multi-Agent Systems
ACM Transactions on Sensor Networks (TOSN)
On location privacy and quality of information in participatory sensing
Proceedings of the 8h ACM symposium on QoS and security for wireless and mobile networks
Value of information and mobility constraints for sampling with mobile sensors
Computers & Geosciences
Local coordination in online distributed constraint optimization problems
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
Agent-based decentralised coordination for sensor networks using the max-sum algorithm
Autonomous Agents and Multi-Agent Systems
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The efficient allocation of the limited energy resources of a wireless sensor network in a way that maximizes the information value of the data collected is a significant research challenge. Within this context, this article concentrates on adaptive sampling as a means of focusing a sensor's energy consumption on obtaining the most important data. Specifically, we develop a principled information metric based upon Fisher information and Gaussian process regression that allows the information content of a sensor's observations to be expressed. We then use this metric to derive three novel decentralized control algorithms for information-based adaptive sampling which represent a trade-off in computational cost and optimality. These algorithms are evaluated in the context of a deployed sensor network in the domain of flood monitoring. The most computationally efficient of the three is shown to increase the value of information gathered by approximately 83%, 27%, and 8% per day compared to benchmarks that sample in a naïve nonadaptive manner, in a uniform nonadaptive manner, and using a state-of-the-art adaptive sampling heuristic (USAC) correspondingly. Moreover, our algorithm collects information whose total value is approximately 75% of the optimal solution (which requires an exponential, and thus impractical, amount of time to compute).