The operational cost of a cloud computing platform is one of the most significant Quality of Service (QoS) criteria for schedulers, crucial to keep up with the growing computational demands. Several data-driven deep neural network (DNN)-based schedulers have been proposed in recent years that outperform alternative approaches by providing scalable and effective resource management for dynamic workloads. However, state-of-the-art schedulers rely on advanced DNNs with high computational requirements, implying high scheduling costs. In non-stationary contexts, the most sophisticated schedulers may not always be required, and it may be sufficient to rely on low-cost schedulers to temporarily save operational costs. In this work, we propose MetaNet, a surrogate model that predicts the operational costs and scheduling overheads of a large number of DNN-based schedulers and chooses one on-the-fly to jointly optimize job scheduling and execution costs. This facilitates improvements in execution costs, energy usage and service level agreement violations of up to 11%, 43% and 13% compared to the state-of-the-art methods.
Use the below installation instructions or spin a Gitpod container with pre-installed dependencies.
# install prerequisites
sudo apt -y update && sudo apt install -y rsync python3-pip
pip3 install --upgrade pip
pip3 install matplotlib scikit-learn
pip3 install -r requirements.txt
export PATH=$PATH:~/.local/bin
sudo chmod 400 keys/id_rsa
# install Azure CLI
curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bashpython3 metanet.pyA preliminary version of this work was accepted as a poster in ACM SIGMETRICS 2022: https://arxiv.org/pdf/2205.10640.pdf.
The conference version is available here: https://arxiv.org/pdf/2205.10642.pdf.
Our work is published in IEEE CLOUD Conference. Cite using the following bibtex entry.
@article{tuli2022metanet,
author={Tuli, Shreshth and Casale, Giuliano and Jennings, Nicholas R.},
journal={IEEE CLOUD},
title={{MetaNet: Automated Dynamic Selection of Scheduling Policies in Cloud Environments}},
year={2022}
}BSD-3-Clause. Copyright (c) 2022, Shreshth Tuli. All rights reserved.
See License file for more details.