Distributed Averaging for Accuracy Prediction in Networked Systems
Sirocchi C, Bogliolo A (2024)
Publication Type: Conference contribution
Publication year: 2024
Journal
Publisher: Springer
Series: Lecture Notes in Computer Science
City/Town: Cham
Pages Range: 130-145
Conference Proceedings Title: Modelling and Mining Networks
Event location: Warschau
ISBN: 9783031592041
DOI: 10.1007/978-3-031-59205-8_9
Abstract
Distributed averaging is among the most relevant cooperative control problems, with applications in sensor and robotic networks, distributed signal processing, data fusion, and load balancing. Gossip algorithms have been investigated and successfully deployed in multi-agent systems to perform distributed averaging in asynchronous settings. This study proposes a heuristic approach to estimate the convergence rate of averaging algorithms in a distributed manner, relying on the computation and propagation of local graph metrics while entailing simple data elaboration and small message passing. The proposed strategy enables nodes to predict the number of interactions needed to estimate the global average with the desired accuracy. Consequently, nodes can make informed decisions on their use of measured and estimated data while gaining awareness of the global structure of the network. The study presents applications to outliers identification and performance evaluation in switching topologies.
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Italy (IT)How to cite
APA:
Sirocchi, C., & Bogliolo, A. (2024). Distributed Averaging for Accuracy Prediction in Networked Systems. In Modelling and Mining Networks (pp. 130-145). Warschau, PL: Cham: Springer.
MLA:
Sirocchi, Christel, and Alessandro Bogliolo. "Distributed Averaging for Accuracy Prediction in Networked Systems." Proceedings of the 19th International Workshop, Warschau Cham: Springer, 2024. 130-145.
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