[ACM SIGCOMM 2024] "m3: Accurate Flow-Level Performance Estimation using Machine Learning" by Chenning Li, Arash Nasr-Esfahany, Kevin Zhao, Kimia Noorbakhsh, Prateesh Goyal, Mohammad Alizadeh, Thomas Anderson.
- Updated
Oct 2, 2024 - Python
[ACM SIGCOMM 2024] "m3: Accurate Flow-Level Performance Estimation using Machine Learning" by Chenning Li, Arash Nasr-Esfahany, Kevin Zhao, Kimia Noorbakhsh, Prateesh Goyal, Mohammad Alizadeh, Thomas Anderson.
Proof of concept lib for creating finagle-like composable Services/Filters in node.
[TBD] "m4: A Learned Flow-level Network Simulator" by Chenning Li, Anton A. Zabreyko, Om Chabra, Arash Nasr-Esfahany, Kevin Zhao, Prateesh Goyal, Mohammad Alizadeh, Thomas Anderson.
Simulation of adversarial queueing (high packet loss) events in computer networks.
Reverse proxy which eliminates the tail latency caused by non-deterministic garbage collection
Chasing the long tail of Clojure HTTP servers.
Linux kernel with CTS scheduler enabled.
Request hedging for tail latency reduction in distributed systems
Add a description, image, and links to the tail-latency topic page so that developers can more easily learn about it.
To associate your repository with the tail-latency topic, visit your repo's landing page and select "manage topics."