Hi! I am currently a second-year Ph.D. student at BUPT, where I am lucky to be advised by Prof. Yuchao Zhang. Before that, I earned my M.Eng degree in Computer Technology from Soochow University, where I was grateful to be supervised by Prof. Jin Wang. Prior to that, I received double B.S. degrees in Computer Science from Northern Arizona University and Computer Science & Technology from Yangzhou University in 2020, respectively.
I would love to work with all people together on some interesting projects! Feel free to drop me an email if you have any ideas to discuss!
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Dong-Yang Yu, Yuchao Zhang*, Xiaodi Wang, Jun Wang, Wenfei Wu, Haipeng Yao, Wendong Wang, Ke Xu (* corresponding author)
21st European Conference on Computer Systems (EuroSys 2026), CCF-A (Acceptance Ratio 138/792=17.4%)
RDMA-empowered cloud services are gradually deployed across datacenters (DCs) with multiple paths, which exhibit new properties of path asymmetry, delayed congestion signals, and simultaneous flow routing collisions, and further fail existing routing methods. We present LCMP, a distributed long-haul cost-aware multi-path routing framework that aims to place RDMA flows on multiple inter-DC paths, achieving low-cost, low-latency, and congestion-responsive transmission. LCMP combines a control-plane path-quality score with compact on-switch congestion signals, where the former unifies quality assessment for asymmetric paths and the latter enables responsive reaction to path congestion. LCMP further resolves the simultaneous flow decision collision problem by filtering high-cost candidates, and performing a diversity-preserving hash inside the reduced set. On an 8-DC testbed, LCMP reduces median and tail FCT slowdown by up to 76% and 64%, respectively compared to state-of-the-art (SOTA) DCN routing strategies. And large-scale NS-3 simulations under the 2000 km inter-DC scenario confirm similar improvements.
Dong-Yang Yu, Yuchao Zhang*, Xiaodi Wang, Jun Wang, Wenfei Wu, Haipeng Yao, Wendong Wang, Ke Xu (* corresponding author)
21st European Conference on Computer Systems (EuroSys 2026), CCF-A (Acceptance Ratio 138/792=17.4%)
RDMA-empowered cloud services are gradually deployed across datacenters (DCs) with multiple paths, which exhibit new properties of path asymmetry, delayed congestion signals, and simultaneous flow routing collisions, and further fail existing routing methods. We present LCMP, a distributed long-haul cost-aware multi-path routing framework that aims to place RDMA flows on multiple inter-DC paths, achieving low-cost, low-latency, and congestion-responsive transmission. LCMP combines a control-plane path-quality score with compact on-switch congestion signals, where the former unifies quality assessment for asymmetric paths and the latter enables responsive reaction to path congestion. LCMP further resolves the simultaneous flow decision collision problem by filtering high-cost candidates, and performing a diversity-preserving hash inside the reduced set. On an 8-DC testbed, LCMP reduces median and tail FCT slowdown by up to 76% and 64%, respectively compared to state-of-the-art (SOTA) DCN routing strategies. And large-scale NS-3 simulations under the 2000 km inter-DC scenario confirm similar improvements.