CloudGenius: Automated Decision Support for Migrating Multi-Component Enterprise Applications to Clouds

TL;DR

CloudGenius is a decision support framework that automates the selection of optimal VM images and cloud services for migrating complex enterprise applications, ensuring QoS and cost considerations are balanced.

Contribution

It introduces a structured migration process and a multi-criteria decision making algorithm using AHP for cloud service selection, addressing complex dependencies and conflicting criteria.

Findings

Demonstrates the effectiveness of the CloudGenius framework.

Shows the decision process can meet QoS requirements.

Analyzes time complexity of the selection algorithm.

Abstract

One of the key problems in migrating multi-component enterprise applications to Clouds is selecting the best mix of VM images and Cloud infrastructure services. A migration process has to ensure that Quality of Service (QoS) requirements are met, while satisfying conflicting selection criteria, e.g. throughput and cost. When selecting Cloud services, application engineers must consider heterogeneous sets of criteria and complex dependencies across multiple layers impossible to resolve manually. To overcome this challenge, we present the generic recommender framework CloudGenius and an implementation that leverage well known multi-criteria decision making technique Analytic Hierarchy Process to automate the selection process based on a model, factors, and QoS requirements related to enterprise applications. In particular, we introduce a structured migration process for multi-component enterprise applications, clearly identify the most important criteria relevant to the selection problem and present a multi-criteria-based selection algorithm. Experiments with the software prototype CumulusGenius show time complexities.