LucasBoTang / Cloud_Computing_with_Stochastic_Programming_Decomposition

Optimizing Costs for Cloud Computing with Stochastic Programming

Optimizing Costs for Cloud Computing with Stochastic Programming

Introduction

Cloud computing exploits virtualization to provision resources efficiently. And the emerging of Software Defined Network (SDN) allows users to pay and custom bandwidth flow across Internet. There is a challenge for the combining of VM and bandwidth provisioning. This project allows for uncertainty of VM and bandwidth demands by formulating a two-satge stochastic optimization. And several decomposition methods are tested.

Reference

Chase, J., & Niyato, D. (2015). Joint optimization of resource provisioning in cloud computing. IEEE Transactions on Services Computing, 10(3), 396-409.

Dependencies

• Python 3.7
• Gurobi 9.1

Methods

• Extensive From
• Multi-Cut Benders
• Single-Cut Benders
• Regularized Decomposition
• Level Method
• Trust Region

Performance

Time Elapse

Iterations