A distributed neural network architecture for dynamic sensor selection with application to bandwidth-constrained body-sensor networks

• URL: http://arxiv.org/abs/2308.08379v1
• Date: Wed, 16 Aug 2023 14:04:50 GMT
• Title: A distributed neural network architecture for dynamic sensor selection with application to bandwidth-constrained body-sensor networks
• Authors: Thomas Strypsteen and Alexander Bertrand
• Abstract summary: We propose a dynamic sensor selection approach for deep neural networks (DNNs) It is able to derive an optimal sensor subset selection for each specific input sample instead of a fixed selection for the entire dataset. We show how we can use this dynamic selection to increase the lifetime of a wireless sensor network (WSN) by imposing constraints on how often each node is allowed to transmit.
• Score: 53.022158485867536
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose a dynamic sensor selection approach for deep neural networks (DNNs), which is able to derive an optimal sensor subset selection for each specific input sample instead of a fixed selection for the entire dataset. This dynamic selection is jointly learned with the task model in an end-to-end way, using the Gumbel-Softmax trick to allow the discrete decisions to be learned through standard backpropagation. We then show how we can use this dynamic selection to increase the lifetime of a wireless sensor network (WSN) by imposing constraints on how often each node is allowed to transmit. We further improve performance by including a dynamic spatial filter that makes the task-DNN more robust against the fact that it now needs to be able to handle a multitude of possible node subsets. Finally, we explain how the selection of the optimal channels can be distributed across the different nodes in a WSN. We validate this method on a use case in the context of body-sensor networks, where we use real electroencephalography (EEG) sensor data to emulate an EEG sensor network. We analyze the resulting trade-offs between transmission load and task accuracy.

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