A spatial sampling scheme based on innovations diffusion in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Innovations diffusion: a spatial sampling scheme for distributed estimation and detection
IEEE Transactions on Signal Processing
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In this paper, we consider a many-to-one sensor network where a large number of sensors are deployed to monitor a physical environment. We explore sensor activity management to maximize the network lifetime, while meeting the quality-of-service (QoS) requirement. Specifically, in each round the sink estimates the number of active sensors and the control information is fed back to the sensors for activity control. We start with a basic case where the total number of sensors N is known, and the estimator of the number of active sensors ncirct is accurate. We devise a sensor activity control scheme under which the number of active sensors would converge to the minimum that can meet the QoS requirement. Next, we generalize the study to the following two more complicated cases: (1) The case with known N and inaccurate ncirct: For this case, we propose a stochastic approximation algorithm to minimize the average number of active sensors while meeting the QoS requirement. (2) The case with unknown N and accurate ncirct: For this case, we cast the problem as the adaptive control of a Markov chain with unknown parameters and propose a composite optimization-oriented approach for the corresponding sensor activity control. We show that using this composite optimization-oriented approach the number of active sensors would converge to the minimum that can meet the QoS requirement