Pré-Publication, Document De Travail Année : 2025

Lightweight Trustworthy Distributed Clustering

Résumé

Ensuring data trustworthiness within individual edge nodes while facilitating collaborative data processing poses a critical challenge in edge computing systems (ECS), particularly in resource-constrained scenarios such as autonomous systems sensor networks, industrial IoT, and smart cities. This paper presents a lightweight, fully distributed k-means clustering algorithm specifically adapted for edge environments, leveraging a distributed averaging approach with additive secret sharing, a secure multiparty computation technique, during the cluster center update phase to ensure the accuracy and trustworthiness of data across nodes.

Dates et versions

hal-05191950 , version 1 (29-07-2025)

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Citer

Hongyang Li, Caesar Wu, Mohammed Chadli, Saïd Mammar, Pascal Bouvry. Lightweight Trustworthy Distributed Clustering. 2025. ⟨hal-05191950⟩
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