Deep Reinforcement Learning-based Virtual Machine Rescheduling

We are still working on this repository. A more complete and clean version will be provided soon.

Installation Steps

1. Install Anaconda:

$ conda create -n rl_vm_scheduling python=3.7
$ conda activate rl_vm_scheduling

2. Install RLlib:

$ pip install gym==0.23.1
$ pip install "ray[rllib]" tensorflow torch
$ pip install -e gym-reschdule_combination

Running Steps

• Train PPO-based agent

  $ python3 main.py

• To use pretrained model for VM selection

  $ python3 main.py --track --model [mlp/attn] --pretrain

• Evaluation

  $ python3 eval.py --restore-name [] --restore-file-name [] --model [mlp/attn]

Environments

• generalizer-v0: Base environment. Fixed number of VMs.
• generalizer-v1: Dynamic number of VMs.
• graph-v1: Dynamic number of VMs with vm-pm affiliations to support graph models.