@conference {Benali2016, title = {Cloud environment assignment: A context-aware and Dynamic Software Product Lines-based approach}, booktitle = {Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA}, volume = {2016-July}, year = {2016}, note = {cited By 0}, abstract = {With the increase in number of mobile devices deployed in cloud computing, the demand of context-aware services to assign increases. Indeed, Information about the user{\textquoteright}s environment exposes new challenges to cloud computing in terms of location-aware, time-aware, device-aware and personalized applications to cope with the constraints of mobile devices in matters of interaction abilities and communication restrictions. In addition, the user also needs context information about services provided by the provider. For instance, the user can check the availability of service, the response time of service, the cost, quality of the service and quality of context information. This paper proposes a software framework which supports context-awareness behavior to assign services to Consumers and especially mobile users. This framework is based on Dynamic Software Product Line approach to handle this variability and adaptation in context at runtime. In fact, changes can occur in the application context requiring the cloud environment to be reconfigured, for instance, non-functional requirements like response-time, availability or pricing are violated. {\textcopyright} 2015 IEEE.}, doi = {10.1109/AICCSA.2015.7507225}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84980328145\&doi=10.1109\%2fAICCSA.2015.7507225\&partnerID=40\&md5=79647337f4c5ee7fcb4c6e501857840d}, author = {Benali, A. and El Asri, B. and Kriouile, H.} } @conference {Benali2015, title = {A pareto-based Artificial Bee Colony and product line for optimizing scheduling of VM on cloud computing}, booktitle = {Proceedings of 2015 International Conference on Cloud Computing Technologies and Applications, CloudTech 2015}, year = {2015}, note = {cited By 0}, 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. {\textcopyright} 2015 IEEE.}, doi = {10.1109/CloudTech.2015.7336980}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962909836\&doi=10.1109\%2fCloudTech.2015.7336980\&partnerID=40\&md5=2a3ad1b3ec1a9d144ab4537c9de687dd}, author = {Benali, A. and El Asri, B. and Kriouile, H.} } @conference {Kriouile2015, title = {Towards deployment of a user-aware tenancy using rich-variant components for SaaS applications}, booktitle = {Proceedings of 2015 International Conference on Cloud Computing Technologies and Applications, CloudTech 2015}, year = {2015}, note = {cited By 0}, 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. {\textcopyright} 2015 IEEE.}, doi = {10.1109/CloudTech.2015.7337019}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962798426\&doi=10.1109\%2fCloudTech.2015.7337019\&partnerID=40\&md5=1097c82a9d464b18b102f40d386e959a}, author = {Kriouile, H. and El Asri, B. and El Haloui, M. and Benali, A.} }