A Minimum-Cost Flow Model for Workload Optimization on Cloud Infrastructure

TL;DR

This paper presents an ILP-based framework for optimizing workload placement on AWS cloud infrastructure to minimize costs and improve resource utilization, leveraging a classical minimum-cost flow model.

Contribution

It introduces a novel ILP model for workload assignment on cloud infrastructure based on the classical minimum-cost flow model.

Findings

Effective cost reduction demonstrated on AWS workloads

Improved resource utilization metrics achieved

Framework applicable to various cloud scenarios

Abstract

Recent technology advancements in the areas of compute, storage and networking, along with the increased demand for organizations to cut costs while remaining responsive to increasing service demands have led to the growth in the adoption of cloud computing services. Cloud services provide the promise of improved agility, resiliency, scalability and a lowered Total Cost of Ownership (TCO). This research introduces a framework for minimizing cost and maximizing resource utilization by using an Integer Linear Programming (ILP) approach to optimize the assignment of workloads to servers on Amazon Web Services (AWS) cloud infrastructure. The model is based on the classical minimum-cost flow model, known as the assignment model.