Home // International Journal On Advances in Intelligent Systems, volume 12, numbers 1 and 2, 2019 // View article

A Hybrid Approach for Personalized and Optimized IaaS Services Selection

Authors:
Hamdi Gabsi
Rim Drira
Henda Benghezala

Keywords: IaaS services selection; Services Consolidation; Cost Optimization; Recommender Systems; Multi-Criteria Decision Making.

Abstract:
Cloud computing offers several service models that change the way applications are developed and deployed. In particular, Infrastructures as a Service (IaaS) has changed application deployment as apart from cost savings, it removes the confines of limited resources’ physical locations and enables a faster time-to-market. Actually, a huge number of IaaS providers and services is becoming available with different configuration options including pricing policy, storage capacity, and computing performance. This fact makes the selection of the suitable IaaS provider and the appropriate service configuration time consuming and requiring a high level of expertise. For these reasons, we aim to assist beginner cloud users in making educated decisions and optimized selection with regard to their applications’ requirements, their preferences, and their previous experiences. To do so, we propose a hybrid approach merging both Multi-Criteria Decision Making Methods and Recommender Systems for IaaS provider selection and services configuration. Moreover, we propose a service consolidation method to optimize the selection results by improving the resources’ consumption and decreasing the total deployment cost. Our solution is implemented in a framework called IaaS Selection Assistant (ISA); its effectiveness is demonstrated through evaluation experiments.

Pages: 14 to 26

Copyright: Copyright (c) to authors, 2019. Used with permission.

Publication date: June 30, 2019

Published in: journal

ISSN: 1942-2679