Brice Morin

Models@ Run.time to Support Dynamic Adaptation

Todays society increasingly depends on software systems deployed in large companies, banks, airports, and so on. These systems must be available 24/7 and continuously adapt to varying environmental conditions and requirements. Such dynamically adaptive systems exhibit degrees of variability that depend on user needs and runtime fluctuations in their contexts. The paper presents an approach for specifying and executing dynamically adaptive software systems that combines model-driven and aspect-oriented techniques to help engineers tame the complexity of such systems while offering a high degree of automation and validation.

Taming Dynamically Adaptive Systems using models and aspects

Since software systems need to be continuously available under varying conditions, their ability to evolve at runtime is increasingly seen as one key issue. Modern programming frameworks already provide support for dynamic adaptations. However the high-variability of features in Dynamic Adaptive Systems (DAS) introduces an explosion of possible runtime system configurations (often called modes) and mode transitions. Designing these configurations and their transitions is tedious and error-prone, making the system feature evolution difficult. While Aspect-Oriented Modeling (AOM) was introduced to improve the modularity of software, this paper presents how an AOM approach can be used to tame the combinatorial explosion of DAS modes. Using AOM techniques, we derive a wide range of modes by weaving aspects into an explicit model reflecting the runtime system. We use these generated modes to automatically adapt the system. We validate our approach on an adaptive middleware for home-automation currently deployed in Rennes metropolis.

Towards Model-Driven Provisioning, Deployment, Monitoring, and Adaptation of Multi-cloud Systems

In the landscape of cloud computing, the competition between providers has led to an ever growing number of cloud solutions offered to consumers. The ability to run and manage multi-cloud systems (i.e., applications on multiple clouds) allows exploiting the peculiarities of each cloud solution and hence optimising the performance, availability, and cost of the applications. However, these cloud solutions are typically heterogeneous and the provided features are often incompatible. This diversity hinders the proper exploitation of the full potential of cloud computing, since it prevents interoperability and promotes vendor lock-in, as well as it increases the complexity of development and administration of multi-cloud systems. This problem needs to be addressed promptly. In this paper, we provide a classification of the state-of-the-art of cloud solutions, and argue for the need for model-driven engineering techniques and methods facilitating the specification of provisioning, deployment, monitoring, and adaptation concerns of multi-cloud systems at design-time and their enactment at run-time.

An Aspect-Oriented and Model-Driven Approach for Managing Dynamic Variability

Constructing and executing distributed systems that can adapt to their operating context in order to sustain provided services and the service qualities are complex tasks. Managing adaptation of multiple, interacting services is particularly difficult since these services tend to be distributed across the system, interdependent and sometimes tangled with other services. Furthermore, the exponential growth of the number of potential system configurations derived from the variabilities of each service need to be handled. Current practices of writing low-level reconfiguration scripts as part of the system code to handle run time adaptation are both error prone and time consuming and make adaptive systems difficult to validate and evolve. In this paper, we propose to combine model driven and aspect oriented techniques to better cope with the complexities of adaptive systems construction and execution, and to handle the problem of exponential growth of the number of possible configurations. Combining these techniques allows us to use high level domain abstractions, simplify the representation of variants and limit the problem pertaining to the combinatorial explosion of possible configurations. In our approach we also use models at runtime to generate the adaptation logic by comparing the current configuration of the system to a composed model representing the configuration we want to reach.

A generic weaver for supporting product lines

Aspects have gained attention in the earlier steps of the software life-cycle leading to the creation of numerous ad-hoc Aspect-Oriented Modeling (AOM) approaches. These approaches mainly focus on architecture diagrams, class diagrams, state-charts, scenarios or requirements and generally propose Aspect-Oriented composition mechanisms specific to a given kind of models defined by its own meta-model. Recently, some generic AOM approaches propose to extend the notion of aspect to any domain specific modelling language (DSML). In this trend, this paper presents GeKo. GeKo has the following properties. i) It is a generic AOM approach easily adaptable to any DSML with no need to modify the domain meta-model or to generate domain-specific frameworks. ii) It keeps a graphical representation of the weaving between an aspect model and the base model. iii) It is a tool-supported approach with a clear semantics of the different operators used to define the weaving. GeKo relies on the definition of mappings between the different views of an aspect, based on the concrete (graphical) syntax associated to the DSML. To illustrate GeKo, we derive, from the Arcade Game Maker Pedagogical Product Line, a new product in which new features are woven into the Product Line models.

Modeling and Validating Dynamic Adaptation

This paper discusses preliminary work on modeling and validation dynamic adaptation. The proposed approach is on the use of aspect-oriented modeling (AOM) and models at runtime. Our approach covers design and runtime phases. At design-time, a base model and different variant architecture models are designed and the adaptation model is built. Crucially, the adaptation model includes invariant properties and constraints that allow the validation of the adaptation rules before execution. During runtime, the adaptation model is processed to produce a correct system configuration that can be executed.

Weaving Variability into Domain Metamodels

Domain-Specific Modeling Languages (DSMLs) describe the concepts of a particular domain and their relationships, in a metamodel. From a given DSML, it is possible to describe a wide range of different models. These models often share a common base and vary on some parts. Current approaches tend to distinguish the variability language from the DSMLs themselves, implying greater learning curve for DSMLs stakeholders and a significant overhead in product line engineering of DSMLs. We propose to consider variability as an independent aspect to be woven into the DSML to introduce variability capabilities. In particular we detail how variability is woven and how to perform product line derivation. We validate our approach through the weaving of variability into two very different metamodels: Ecore and SmartAdapter, our Aspect-Oriented modeling weaver, thus adding flexibility in the weaving process itself. These results emphasize how new abilities of the language can be provided by this means.

A dynamic component model for cyber physical systems

Cyber Physical Systems (CPS) offer new ways for people to interact with computing systems: every thing now inte- grates computing power that can be leveraged to provide safety, assistance, guidance or simply comfort to users. CPS are long living and pervasive systems that intensively rely on microcontrollers and low power CPUs, integrated into build- ings (e.g. automation to improve comfort and energy opti- mization) or cars (e.g. advanced safety features involving car-to-car communication to avoid collisions). CPS operate in volatile environments where nodes should cooperate in opportunistic ways and dynamically adapt to their context. This paper presents ¼-Kevoree, the projection of Kevoree (a component model based on models@runtime) to microcon- trollers. ¼-Kevoree pushes dynamicity and elasticity con- cerns directly into resource-constrained devices. Its evalua- tion regarding key criteria in the embedded domain (mem- ory usage, reliability and performance) shows that, despite a contained overhead, ¼-Kevoree provides the advantages of a dynamically reconfigurable component-based model (safe, fine-grained, and efficient reconfiguration) compared to tra- ditional techniques for dynamic firmware upgrades.

Managing multi-cloud systems with CloudMF

Dynamically adaptive systems (DAS) enable the continuous design and adaptation of complex software systems, but their main focus is limited to the application itself rather than the underlying platform and infrastructure. Cloud computing, in contrast, enables the management of the complete software stack, but it lacks integration with software engineering approaches, techniques, and methods from DAS. Model-based approaches have been successfully adopted for modelling DAS at design-time and facilitate their adaptation at run-time. Therefore, a natural next step is to adopt model-based approaches to enable cloud-based DAS. In this paper, we present the Cloud Modelling Framework (CloudMF), a model-based framework that addresses this issue. It consists of (i) a tool-supported domain-specific modelling language to model the provisioning and deployment of multi-cloud systems, and (ii) a models@run-time environment for enacting the provisioning, deployment and adaptation of these systems.

Introducing variability into aspect-oriented modeling approaches

Aspect-Oriented Modeling (AOM) approaches propose to model reusable aspects, or cross-cutting concerns, that can be composed in different systems at a model or code level. Building complex systems with reusable aspects helps managing software complexity. But in general, reusability of an aspect is limited to a particular context. On the one hand, if the target model does not match the template point-to-point, the aspect cannot be applied. On the other hand, even when it is actually applied, it is woven into the target model always in the same way. In this paper, we point out the needs of variability in the AOM approaches and introduce seamless variability mechanisms in an existing AOM approach to improve reusability. Our aspects can fit various contexts and can be composed into the base model in different ways. Introducing variability into AOM approaches will turn standard aspects into highly reusable aspects.