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Space-Fluid Adaptive Sampling: A Field-Based, Self-organising Approach

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Coordination Models and Languages (COORDINATION 2022)

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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.

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Notes

  1. 1.

    https://github.com/DanySK/Experiment-2022-Coordination-Space-Fluid.

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Acknowledgements

This work has been supported by the MIUR PRIN 2017 Project “Fluidware” (N. 2017KRC7KT) and the MIUR FSE REACT-EU PON R &I 2014-2022 (N. CCI2014IT16M2OP005).

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Authors and Affiliations

  1. Alma Mater Studiorum—Università Bologna, Cesena, Italy

    Roberto Casadei, Danilo Pianini & Mirko Viroli

  2. Università di Modena e Reggio Emilia, Reggio Emilia, Italy

    Stefano Mariani & Franco Zambonelli

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  1. Roberto Casadei
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  2. Stefano Mariani
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  3. Danilo Pianini
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  4. Mirko Viroli
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  5. Franco Zambonelli
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Corresponding author

Correspondence to Roberto Casadei .

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Editors and Affiliations

  1. Istituto di Scienza e Tecnologie dell'In, Pisa, Italy

    Maurice H. ter Beek

  2. Mälardalen University, Västerås, Sweden

    Marjan Sirjani

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Casadei, R., Mariani, S., Pianini, D., Viroli, M., Zambonelli, F. (2022). Space-Fluid Adaptive Sampling: A Field-Based, Self-organising Approach. In: ter Beek, M.H., Sirjani, M. (eds) Coordination Models and Languages. COORDINATION 2022. IFIP Advances in Information and Communication Technology, vol 13271. Springer, Cham. https://doi.org/10.1007/978-3-031-08143-9_7

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  • DOI: https://doi.org/10.1007/978-3-031-08143-9_7

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