Today, the use of software is generally regulated by licenses, whether they are free or paid and with or without access to their sources. The world of licenses is very vast and unknown. Often only the public version is known (a software purchase corresponds to a license). For enterprises, the reality is much more complex, especially for main software publishers. Very few, if any, deployment algorithm takes Software Asset Management (SAM) considerations into account when placing software on Cloud architecture. This could have huge financial impact on the company using theses software. In this article, we present the SAM problem more deeply, then, after expressing our problem mathematically, we present GreenSAM, our multi-parametric heuristic handling performance and energy parameters as well as SAM considerations. We will then show the use of this heuristic on two realistic situations, first with an Oracle Database deployment and second with a larger scenario of managing a small OpenStack platform deployment. In both cases, we will compare GreenSAM with other heuristics to show how it handles the performance/energy criteria and the SAM compliance.

In the Cloud Era, we want to be able to quickly deploy any software anywhere in the world to provide high availability and fast services while maintaining acceptable levels of performance, low energy consumption and ensuring the compliance with every software level agreements contracted. To answer some of these needs, different tools exist in parallel to a big variety of Cloud architectures. Several interesting problems arise like deployment, networking, storage, security, and many others. In this paper, we will focus on the deployment issue with a Software Asset Management point of view. Most Cloud providers use proprietary software to ensure different kinds of services, and with them comes the licensing problem. We will tackle and propose a heuristic to solve the problem of deploying software in a Cloud architecture while considering license compliance, license price, and other important criteria. We will prove the NP-completeness of this problem and compare our heuristic with others to evaluate the enhancement we propose.

No abstract