@conference { ISI:000380407100019,
	title = {A pareto-based Artificial Bee Colony and Product Line for Optimizing Scheduling of VM on Cloud Computing},
	booktitle = {2015 INTERNATIONAL CONFERENCE ON CLOUD TECHNOLOGIES AND APPLICATIONS (CLOUDTECH 15)},
	year = {2015},
	note = {International Conference on Cloud Computing Technologies and Applications (CloudTech), Marrakech, MOROCCO, JUN 02-04, 2015},
	pages = {159-165},
	abstract = {In this paper, we present a task scheduling management based on the utility model which is used in economics to represent the needs of both the client and the provider. Indeed, our work copes with two man parameters that affect the broker, the cost of virtual machine instances and their response time. Minimizing those two objectives give the best quality of service to the customers and offer the broker an important profit. In fact, we consider the virtual machines as a product line and use the feature models to represent the virtual machines configurations to select the efficient resources that suit customer requirements and try at same time to minimize virtual machine cost. An efficient task scheduling mechanism can not only fit client{\textquoteright}s requirements, but also improve the resource utilization, be aware of the changing environment and intends to try to balance the system. Thus, our work is based on Artificial Bee Colony to optimize the scheduling of tasks on virtual machine in cloud computing by analyzing the difference of virtual machine load balancing algorithm.},
	isbn = {978-1-4673-8149-9},
	author = {Benali, Asmae and El Asri, Bouchra and Kriouile, Houda}
}
@conference { ISI:000380407100058,
	title = {Towards Deployment of a User-Aware Tenancy Using Rich-Variant Components for SaaS Applications},
	booktitle = {2015 INTERNATIONAL CONFERENCE ON CLOUD TECHNOLOGIES AND APPLICATIONS (CLOUDTECH 15)},
	year = {2015},
	note = {International Conference on Cloud Computing Technologies and Applications (CloudTech), Marrakech, MOROCCO, JUN 02-04, 2015},
	pages = {50-55},
	abstract = {The approach of User-Aware Tenancy integrates the high configurability of multi-tenant applications with the flexibility and the functional variability of Rich-Variant Component use. Multi-tenancy concept consists in sharing instances among a large group of customers, called tenants. Multi-tenancy is a tool to exploit economies of scale widely promoted by Software as a Service (SaaS) models. However, the ability of a SaaS application to be adapted to individual tenant{\textquoteright}s needs seem to be a major requirement. Thus, our approach focuses on more flexibility and more reusability for Multi-tenant SaaS application using the multiview notion of Rich-Variant Components. The approach consists in a user-aware tenancy for SaaS. In this paper, we provide an application of an algorithm deriving the necessary instances of Rich-Variant Components building the application in a scalable and performing manner. The algorithm is based on fundamental concepts from the graph theory, and is accompanied by a reduced school management application as an illustrating example.},
	isbn = {978-1-4673-8149-9},
	author = {Kriouile, Houda and El Asri, Bouchra and El Haloui, M{\textquoteright}barek and Benali, Asmae}
}
