Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
An Upper Bound on the Loss from Approximate Optimal-Value Functions
Machine Learning
Learning to act using real-time dynamic programming
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
Incremental dynamic programming for on-line adaptive optimal control
Incremental dynamic programming for on-line adaptive optimal control
Adaptive protocols for information dissemination in wireless sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Proceedings of the twenty-first annual symposium on Principles of distributed computing
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Robust distributed estimation in sensor networks using the embedded polygons algorithm
Proceedings of the 3rd international symposium on Information processing in sensor networks
AIDA: Adaptive application-independent data aggregation in wireless sensor networks
ACM Transactions on Embedded Computing Systems (TECS)
Optimized Scheduling for Data Aggregation in Wireless Sensor Networks
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
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
A space-time diffusion scheme for peer-to-peer least-squares estimation
Proceedings of the 5th international conference on Information processing in sensor networks
On the optimal density for real-time data gathering of spatio-temporal processes in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
MAC protocols for wireless sensor networks: a survey
IEEE Communications Magazine
Distributed opportunistic scheduling with two-level probing
IEEE/ACM Transactions on Networking (TON)
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The scenario of distributed data aggregation in wireless sensor networks is considered, where sensors can obtain and estimate the information of the whole sensing field through local data exchange and aggregation. An intrinsic tradeoff between energy and aggregation delay is identified, where nodes must decide optimal instants for forwarding samples. The samples could be from a node's own sensor readings or an aggregation with samples forwarded from neighboring nodes. By considering the randomness of the sample arrival instants and the uncertainty of the availability of the multiaccess communication channel, a sequential decision process model is proposed to analyze this problem and determine optimal decision policies with local information. It is shown that, once the statistics of the sample arrival and the availability of the channel satisfy certain conditions, there exist optimal control-limit-type policies that are easy to implement in practice. In the case that the required conditions are not satisfied, the performance loss of using the proposed control-limit-type policies is characterized. In general cases, a finite-state approximation is proposed and two on-line algorithms are provided to solve it. Practical distributed data aggregation simulations demonstrate the effectiveness of the developed policies, which also achieve a desired energy-delay tradeoff.