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arXiv · 2504.10109

Lightweight Trustworthy Distributed Clustering

Hongyang Li·Caesar Wu·Mohammed Chadli·Said Mammar·Pascal Bouvry
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Abstract

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.

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Hongyang Li, Caesar Wu, Mohammed Chadli, Said Mammar, Pascal Bouvry. 2025-04-14. Lightweight Trustworthy Distributed Clustering. https://arxiv.org/abs/2504.10109

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