Author

Chang Xu

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Open access Aug 2026

Rethinking Cache Eviction: Low-Overhead and Precise Learning-based Design

Caches reduce latency and network traffic, and cache performance largely depends on the eviction policy. Eviction effectiveness is typically measured by byte and object miss ratios. Although learning-based eviction policies can reduce misses, their high computational overhead limits practical deployment. This work pres...

Qian Wang, Chang Xu, Wenbin Zhou et al. · ACM Transactions on Computer... · 0 citations

2026

SLA-Aware RSU-Edge Delegate Orchestration for IoV Consensus

Ensuring reliable and timely consensus among Internet of Vehicles (IoV) nodes is critical for safety and operational efficiency, particularly under high mobility and dynamic network conditions. Traditional consensus protocols, however, do not explicitly incorporate service-level objectives (SLOs) such as commit latency...

Awais Bilal, Kashif Sharif, Lie-Huang Zhu et al. · IEEE Transactions on Network... · 0 citations

#edge computing Sep 2026

Blockchain-Assisted Privacy-Preserving and Robust Federated Learning in Edge Computing

Federated learning (FL) enables distributed clients to collaboratively train machine learning models without sharing raw data, making it well-suited for edge computing environments. However, deploying FL at the edge introduces critical challenges, including potential model poisoning by malicious clients or edge servers...

Xiaodong Shen, Chang Xu, Liehuang Zhu et al. · IEEE Internet of Things Jour... · 0 citations