Literature Database Entry

yuan2026byzantine-resilient

Yuan Yuan, Lin Sun, Yan Li, Xiao Zhang, Yifei Zou, Falko Dressler and Dongxiao Yu, "Byzantine-Resilient Collaborative Learning in Heterogeneous Resource-Adaptive Systems," IEEE Transactions on Mobile Computing, 2026. (to appear)

Abstract

Collaborative learning across heterogeneous resource-adaptive systems has emerged as a promising paradigm for enabling large-scale edge intelligence. However, the heterogeneity of resources and model components often leads to inconsistent optimization behaviors among participants, which makes the learning process highly sensitive to unreliable or even malicious nodes. To tackle this challenge, we propose a novel Byzantine Resilient Collaborative Learning algorithm (BRCL), which achieves Byzantine robustness while adapting to the dynamic and resource-constrained nature of heterogeneous environments. The proposed BRCL framework integrates adaptive resource scheduling with robust aggregation to maintain learning efficiency under adversarial conditions. We theoretically prove that BRCL attains an asymptotically optimal convergence rate of O(1/√︁T K(Γ∗ − f)), where Γ∗ is the minimum covering number, and f is the number of Byzantine clients. Special cases show that BRCL generalizes several classical algorithms, including FedAvg and OAP, under different system configurations. Extensive experiments on multiple learning tasks demonstrate that BRCL consistently outperforms state-of-the-art methods, achieving at least a 4.2% improvement in accuracy on average, while preserving robustness and resource efficiency in heterogeneous edge systems.

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Yuan Yuan
Lin Sun
Yan Li
Xiao Zhang
Yifei Zou
Falko Dressler
Dongxiao Yu

BibTeX reference

@article{yuan2026byzantine-resilient,
    author = {Yuan, Yuan and Sun, Lin and Li, Yan and Zhang, Xiao and Zou, Yifei and Dressler, Falko and Yu, Dongxiao},
    note = {to appear},
    title = {{Byzantine-Resilient Collaborative Learning in Heterogeneous Resource-Adaptive Systems}},
    journal = {IEEE Transactions on Mobile Computing},
    issn = {1536-1233},
    publisher = {IEEE},
    year = {2026},
   }
   
   

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Last modified: 2026-10-08