activity
20182023
most citedInterpreting Deep Learning-Based Networking Systems

98 citations · 161 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NI2023★ 1 cited

Confucius: Achieving Consistent Low Latency with Practical Queue Management for Real-Time Communications

Zili Meng, Nirav Atre, Mingwei Xu +2

Real-time communication applications require consistently low latency, which is often disrupted by latency spikes caused by competing flows, especially Web traffic. We identify the…

cs.NI2023

Robustifying Measurement-Based Congestion Control Algorithms

Zhu Yuxi, Meng Zili, Shen Yixin +2

The design methodology of congestion control algorithms (CCAs) has shifted from control-based to measurement-based in recent years. However, we find that measurement-based CCAs, al…

cs.NI2019★ 98 cited

Interpreting Deep Learning-Based Networking Systems

Zili Meng, Minhu Wang, Jiasong Bai +3

While many deep learning (DL)-based networking systems have demonstrated superior performance, the underlying Deep Neural Networks (DNNs) remain blackboxes and stay uninterpretable…

cs.LG2018★ 50 cited

Learning Scheduling Algorithms for Data Processing Clusters

Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan +2

Efficiently scheduling data processing jobs on distributed compute clusters requires complex algorithms. Current systems, however, use simple generalized heuristics and ignore work…

cs.NI2018★ 2 cited

PAM: When Overloaded, Push Your Neighbor Aside!

Zili Meng, Jun Bi, Chen Sun +3

Recently SmartNICs are widely used to accelerate service chains in NFV. However, when the SmartNIC is overloaded, casually migrating vNFs away from SmartNIC to CPU may lead to addi…

cs.NI2018★ 10 cited

CoCo: Compact and Optimized Consolidation of Modularized Service Function Chains in NFV

Zili Meng, Jun Bi, Haiping Wang +2

The modularization of Service Function Chains (SFCs) in Network Function Virtualization (NFV) could introduce significant performance overhead and resource efficiency degradation d…