You are currently viewing Séminaire ACMES, présenté par Rania Ben Halima le 10/05/2017 à 14h en C06, à Télécom SudParis.

Séminaire ACMES, présenté par Rania Ben Halima le 10/05/2017 à 14h en C06, à Télécom SudParis.

Quand: le 10/05/2017 à 14h
Où: Salle C06
Titre de la présentation: « Optimal Pricing Strategy for Time-Aware Cloud Resource Allocation in Business Process ».

Résumé: Cloud Computing infrastructures are being increasingly used for running business process activities due to its high performance level and low operating cost. The enterprise QoS requirements are diverse and different resources are offered by Cloud providers in various QoS-based pricing strategies. Furthermore, business process activities are constrained by hard timing constraints and if they are not executed correctly the enterprise will pay penalties costs. Therefore, finding the optimal Cloud resources allocation for a business process becomes a highly challenging problem. While optimizing the Cloud resource allocation cost, it is important to respect activities QoS requirements and temporal constraints and Cloud pricing strategies constraints. The aim of the present paper is to offer a method that assists users finding the optimal pricing strategy for Cloud resource used by business process activities. Basically, we use a binary/(0-1) linear program with an objective function under a set of constraints. In order to show its feasibility, our approach has been implemented and the results of our experiments highlight the effectiveness of our proposed solution.

Biographie:

Rania Ben Halima received the graduation degree in computer science engineer from the National Engineering School of Sfax (ENIS), Tunisia, in 2014. She is currently working toward the PhD degree under the joint supervision of Prof. Walid Gaaloul, a professor in the TELECOM SudParis School, France, and Prof. Mohamed Jmaiel, a professor in the National Engineering School of Sfax (ENIS), Tunisia. Her research interests include in business process management, temporal constraints, cloud computing and cost optimization.