most citedMultibit Tries Packet Classification with Deep Reinforcement Learning

8 citations · 17 across the 5 of their papers we have counts for

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cs.NI2024

FlowTracer: A Tool for Uncovering Network Path Usage Imbalance in AI Training Clusters

Hasibul Jamil, Abdul Alim, Laurent Schares +6

The increasing complexity of AI workloads, especially distributed Large Language Model (LLM) training, places significant strain on the networking infrastructure of parallel data c…

cs.NI2024

Carbon-Aware End-to-End Data Movement

Jacob Goldverg, Hasibul Jamil, Elvis Rodriguez +1

The latest trends in the adoption of cloud, edge, and distributed computing, as well as a rise in applying AI/ML workloads, have created a need to measure, monitor, and reduce the…

cs.NI20221 cited

A Reinforcement Learning Approach to Optimize Available Network Bandwidth Utilization

Hasibul Jamil, Elvis Rodrigues, Jacob Goldverg +1

Efficient data transfers over high-speed, long-distance shared networks require proper utilization of available network bandwidth. Using parallel TCP streams enables an application…

cs.NI20228 cited

Multibit Tries Packet Classification with Deep Reinforcement Learning

Hasibul Jamil, Ning Weng

High performance packet classification is a key component to support scalable network applications like firewalls, intrusion detection, and differentiated services. With ever incre…

cs.NI20228 cited

Many Field Packet Classification with Decomposition and Reinforcement Learning

Hasibul Jamil, Ning Yang, Ning Weng

Scalable packet classification is a key requirement to support scalable network applications like firewalls, intrusion detection, and differentiated services. With ever increasing…