Design of complex systems implies various points of view expressed by stakeholders with different areas of expertise. Each stakeholder describes his model in a Domain Specific Language, according to his point of view. Ensuring the consistency of the global system and building a cross view is a challenging task. It requires the involvement of all stakeholders to produce intermodel correspondences that satisfy their concerns. In this paper, we first introduce a metamodel of collaboration that formalizes collaborative work, then we use this metamodel to define a collaborative process for heterogeneous design models matching. This approach establishes semantic links at metamodel level by following a group decision-making process, then it refines those links semi-automatically at model level by exploiting their semantics.

To design a complex system, we often proceed via separation of viewpoints. Each viewpoint is described by a model that represents a domain expertise. Those partial models are generally heterogeneous (i.e conform to different metamodels) and thus performed by different designers. We proposed a matching process that links partial models through a virtual global model in order to create a complete view of the system. As models evolve, we should consider the impact of changing an element involved in a correspondence on other models to keep the coherence of the global view. So, we have defined a process that automatically identify changes, classify them and treat their potential repercussions on elements of other partial models in order to maintain the global model consistency.

Design of complex systems goes through a multiview paradigm in which separate teams, from different business viewpoints, build partial models describing the system. As they are expressed in different languages, these partial models are called heterogeneous models. To maintain the global system's consistency, we propose a collaborative approach that combines Group Decision Making (GDM) and Model-Based Engineering. This paper presents a metamodel for collaborative decision elaboration via a set of decision policies which are instances of GDM patterns. Our approach is illustrated with a hospital Emergency Department case study and is supported by a tool allowing models alignment through GDM based processes. Keywords-collaboration, group decision-making, pattern, heterogeneous models, model-based engineering, model alignment, model matching.

Cloud Computing (CC) marks a new step towards IT infrastructure dematerialization. Cloud provides IT resources, software and hardware, remotely accessible, as a service. The adoption of this model raises a number of challenges, particularly with regard to Quality of the provided services. To cope with a highly dynamic environment such as the CC, it is essential to determine in real time Quality of Service (QoS) to meet consumer's SLA (Service Level Agreements) specifications. In this context, agreements (contract) service level form an appropriate solution to specify these QoS guarantees. It specifies one or more service level objectives (SLO), to guarantee that the delivered QoS satisfies the consumer expectations. Monitoring these QoS agreements for the management of the relationships, between, cloud providers and their services customers is an area that attracts the attention of many researchers and industrialists in the cloud. In our work we introduce the concept of monitoring and respect of the QoS, then we present a third party service provider that ensures the respect of the Quality of Service in real-time to guarantee the performance and the reliability of the Cloud.

Complex systems are typically designed collaboratively by stakeholders from different domains. This multi viewpoints paradigm promotes the separation of concerns since separate teams, from different business viewpoints, build partial models describing the system. These partial models are naturally heterogeneous. So, it is difficult to ensure their intermodel consistency if kept separately. For that, we propose a collaborative approach that combines Group Decision Making (GDM) and Model-Based Engineering (MBE). This paper highlights the GDM part of our approach and especially the concept of decision policy that enables coming up with collective decisions in group decision-making contexts.