Alessandro Rossini

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.

Cloud MF: Applying MDE to Tame the Complexity of Managing Multi-cloud Applications

The market of cloud computing encompasses an ever-growing number of cloud providers offering a multitude of infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) solutions. The heterogeneity of these solutions hinders the proper exploitation of cloud computing since it prevents interoperability and promotes vendor lock-in, which increases the complexity of executing and managing multi-cloud applications (i.e., Applications that can be deployed across multiple cloud infrastructures and platforms). Providers of multi-cloud applications seek to exploit the peculiarities of each cloud solution and to combine the delivery models of IaaS and PaaS in order to optimise performance, availability, and cost. In this paper, we show how the Cloud Modelling Framework leverages upon model-driven engineering to tame this complexity by providing: (i) a tool-supported domain-specific language for specifying the provisioning and deployment of multi-cloud applications, and (ii) a models@run-time environment for enacting the provisioning, deployment, and adaptation of these applications.

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.

A formal approach to the specification and transformation of constraints in MDE

Abstract This paper introduces a formal approach to constraint-aware model transformation which supports specifying constraints in the definition of transformation rules. These constraints are used to control which structure to create in the target model and which constraints to add to the created structure. The proposed approach is classified under heterogeneous, graph-based and out-place model transformations; and illustrated by applying it to a language translation. It is based on the Diagram Predicate Framework which provides a formalisation of (meta)modelling based on category theory and graph transformation. In particular, the proposed approach uses non-deleting transformation rules that are specified by a joined modelling language which is defined by relating the source and target languages. The relation between source and target languages is formalised by morphisms from their corresponding modelling formalisms into a joined modelling formalism. Furthermore, the application of transformation rules is formalised as a pushout construction and the final target model is obtained by a pullback construction.

SRL: A Scalability Rule Language for Multi-cloud Environments

The benefits of cloud computing have led to a proliferation of infrastructures and platforms covering the provisioning and deployment requirements of many cloud-based applications. However, the requirements of an application may change during its life cycle. Therefore, its provisioning and deployment should be adapted so that the application can deliver its target quality of service throughout its entire life cycle. Existing solutions typically support only simple adaptation scenarios, whereby scalability rules map conditions on fixed metrics to a single scaling action targeting a single cloud environment (e.g., Scale out an application component). However, these solutions fail to support complex adaptation scenarios, whereby scalability rules could map conditions on custom metrics to multiple scaling actions targeting multi-cloud environments. In this paper, we propose the Scalability Rule Language (SRL), a language for specifying scalability rules that support such complex adaptation scenarios of multi-cloud applications. SRL provides Eclipse-based tool support, thus allowing modellers not only to specify scalability rules but also to syntactically and semantically validate them. Moreover, SRL is well integrated with the Cloud Modelling Language (Cloud ML), thus allowing modellers to associate their scalability rules with the components and virtual machines of provisioning and deployment models.

A formalisation of the copy-modify-merge approach to version control in MDE☆

Abstract Models are the primary artefacts of the software development process in Model-Driven Engineering (MDE). Like other software artefacts, models undergo a complex evolution during their life cycles. Version control is one of the key techniques which enable developers to tackle this complexity. Traditional version control systems (VCS) are based on the copy-modify-merge approach which is not fully exploited in MDE since current implementations lack model-orientation. In this paper we provide a formalisation of the copy-modify-merge approach in the context of MDE. In particular, we analyse how the identification of commonalities and the calculation of differences can be defined by means of category-theoretical constructions. Moreover, we demonstrate how the properties of these constructions can be used to synchronise models and detect conflicting modifications.

A Category-Theoretical Approach to the Formalisation of Version Control in MDE

In Model-Driven Engineering (MDE) models are the primary artefacts of the software development process. Similar to other software artefacts, models undergo a complex evolution during their life cycles. Version control is one of the key techniques which enables developers to tackle this complexity. Traditional version control systems are based on the copy-modify-merge paradigm which is not fully exploited in MDE because of the lack of model-specific techniques. In this paper we give a formalisation of the copy-modify-merge paradigm in MDE. In particular, we analyse how common models and merge models can be defined by means of category-theoretical constructions. Moreover, we show how the properties of those constructions can be used to identify model differences and conflicting modifications.

A formalisation of deep metamodelling

Metamodelling is one of the pillars of model-driven engineering, used for language engineering and domain modelling. Even though metamodelling is traditionally based on a two-metalevel approach, several researchers have pointed out limitations of this solution and proposed an alternative deep (also called multi-level) approach to obtain simpler system specifications. However, this approach currently lacks a formalisation that can be used to explain fundamental concepts such as deep characterisation, double linguistic/ontological typing and linguistic extension. This paper provides such a formalisation based on the Diagram Predicate Framework, and discusses its practical realisation in the metaDepth tool.

A Diagrammatic Formalisation of MOF-Based Modelling Languages

In Model-Driven Engineering (MDE) models are the primary artefacts of the software development process. The usage of these models have resulted in the introduction of a variety of modelling languages and frameworks. Many of these languages and frameworks are based on the Object Management Group’s (OMG) Meta-Object Facility (MOF). In addition to their diagrammatic syntax, these languages use the Object Constraint Language to specify constraints that are difficult to specify diagrammatically. In this paper, we argue for a completely diagrammatic specification framework for MDE, where by diagrammatic we mean specification techniques which are targeting graph-based structures. We introduce the Diagram Predicate Framework, which provides a formal diagrammatic approach to modelling based on category theory – the mathematics of graph-based structures. The development of a generic and flexible formalisation of metamodelling is the main contribution of the paper. We illustrate our approach through the formalisation of the kernel of the Eclipse Modeling Framework.

Brokerage for Quality Assurance and Optimisation of Cloud Services: An Analysis of Key Requirements

As the number of cloud service providers grows and the requirements of cloud service consumers become more complex, the latter will come to depend more and more on the intermediation services of cloud service brokers. Continuous quality assurance and optimisation of services is becoming a mission-critical objective that many consumers will find difficult to address without help from cloud service intermediaries. The Broker@Cloud project envisages a software framework that will make it easier for cloud service intermediaries to address this need, and this paper provides an analysis of key requirements for this framework. We discuss the methodology that we followed to capture these requirements, which involved defining a conceptual service lifecycle model, carrying out a series of Design Thinking workshops, and formalising requirements based on an agile requirements information model. Then, we present the key requirements identified through this process in the form of summarised results.