Publications (12)
Accelerating Geo-distributed Machine Learning with Network-Aware Adaptive Tree and Auxiliary Route
Zonghang Li, Wenjiao Feng, Weibo Cai +5
Distributed machine learning is becoming increasingly popular for geo-distributed data analytics, facilitating the collaborative analysis of data scattered across data centers in d…
Learning In Chaos: Efficient Autoscaling and Self-Healing for Multi-Party Distributed Training
Wenjiao Feng, Rongxing Xiao, Zonghang Li +6
Node and link churn in multi-party, cross-region clusters over wide-area networks (WANs) often disrupts distributed training. However, checkpoint-based recovery and cloud-centric a…
A Survey of Network Protocol Fuzzing: Model, Techniques and Directions
Shihao Jiang, Yu Zhang, Junqiang Li +3
As one of the most successful and effective software testing techniques in recent years, fuzz testing has uncovered numerous bugs and vulnerabilities in modern software, including…
A Fragmentation-Aware Adaptive Bilevel Search Framework for Service Mapping in Computing Power Networks
Jingzhao Xie, Zhenglian Li, Gang Sun +2
Computing Power Network (CPN) unifies wide-area computing resources through coordinated network control, while cloud-native abstractions enable flexible resource orchestration and…
Scalable Fine-grained Path Control in Software Defined Networks
Long Luo, Hongfang Yu, Shouxi Luo
The OpenFlow-based SDN is widely studied to better network performance through planning fine-grained paths. However, being designed to configure path hop-by-hop, it faces the scala…
HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse
Shenglai Zeng, Zonghang Li, Hongfang Yu +4
Federated Learning (FL), as a rapidly evolving privacy-preserving collaborative machine learning paradigm, is a promising approach to enable edge intelligence in the emerging Indus…