3 papers
eess.SY2023
A Framework for dynamically meeting performance objectives on a service mesh
Forough Shahab Samani, Rolf Stadler
We present a framework for achieving end-to-end management objectives for multiple services that concurrently execute on a service mesh. We apply reinforcement learning (RL) techni…
cs.LG2022
Dynamically meeting performance objectives for multiple services on a service mesh
Forough Shahab Samani, Rolf Stadler
We present a framework that lets a service provider achieve end-to-end management objectives under varying load. Dynamic control actions are performed by a reinforcement learning (…
cs.LG2020
Online feature selection for rapid, low-overhead learning in networked systems
Xiaoxuan Wang, Forough Shahab Samani, Rolf Stadler
Data-driven functions for operation and management often require measurements collected through monitoring for model training and prediction. The number of data sources can be very…