A recurrent task in coordinated systems is managing (estimating, predicting, or controlling) signals that vary in space, such as distributed sensed data or computation outcomes. Especially in large-scale settings, the problem can be addressed through decentralised and situated computing systems: nodes can locally sense, process, and act upon signals, and coordinate with neighbours to implement collective strategies. Accordingly, in this work we devise distributed coordination strategies for the estimation of a spatial phenomenon through collaborative adaptive sampling. Our design is based on the idea of dynamically partitioning space into regions that compete and grow/shrink to provide accurate aggregate sampling. Such regions hence define a sort of virtualised space that is “fluid”, since its structure adapts in response to pressure forces exerted by the underlying phenomenon. We provide an adaptive sampling algorithm in the field-based coordination framework. Finally, we verify by simulation that the proposed algorithm effectively carries out a spatially adaptive sampling.
Casadei R., Mariani S., Pianini D., Viroli M., Zambonelli F. (2022). Space-Fluid Adaptive Sampling: A Field-Based, Self-organising Approach. CHAM : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-08143-9_7].
Space-Fluid Adaptive Sampling: A Field-Based, Self-organising Approach
Casadei R.;Pianini D.;Viroli M.;
2022
Abstract
A recurrent task in coordinated systems is managing (estimating, predicting, or controlling) signals that vary in space, such as distributed sensed data or computation outcomes. Especially in large-scale settings, the problem can be addressed through decentralised and situated computing systems: nodes can locally sense, process, and act upon signals, and coordinate with neighbours to implement collective strategies. Accordingly, in this work we devise distributed coordination strategies for the estimation of a spatial phenomenon through collaborative adaptive sampling. Our design is based on the idea of dynamically partitioning space into regions that compete and grow/shrink to provide accurate aggregate sampling. Such regions hence define a sort of virtualised space that is “fluid”, since its structure adapts in response to pressure forces exerted by the underlying phenomenon. We provide an adaptive sampling algorithm in the field-based coordination framework. Finally, we verify by simulation that the proposed algorithm effectively carries out a spatially adaptive sampling.File | Dimensione | Formato | |
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paper-2022-coordination-space-fluid.pdf
Open Access dal 15/06/2023
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