Migrating software to mobile technology: a model driven engineering approach

Nowadays, organizations are facing the problematic of having to modernize or replace their legacy software. This software has involved the investment of money, time and other resources through the ages and there is a high risk in replacing it. The purpose of reengineering is to adapt software in a disciplined way in order to improve its quality in aspects such as operability, functionality or performance. The focus of reengineering is on improving an existing system with a higher return on investment than would be achieved by developing a new system. In the context of reengineering, the term legacy was associated with software that survived several generations of developers, administrators and users. The entry into the market of new technologies or paradigms is increasingly occurring and, motivates the growing demand for the adaptation of systems developed more recently. Mobile Computing is crucial to harvesting the potential of these new paradigms. Smartphones are the most used computing platform worldwide. They come with a variety of sensors (GPS, accelerometer, digital compass, microphone and camera) enabling a wide range of applications in Pervasive Computing, Cloud Computing and Internet of Things (IoT)

MapIt : a model based pattern recovery tool

Design patterns provide a means to reuse proven solutions during development, but also to identify good practices during analysis. These are particularly relevant in complex and critical software, such as is the case of ubiquitous and pervasive systems. Model Driven Engineering (MDE) presents a solution for this problem, with the usage of high level models. As part of an effort to develop approaches to the migration of applications to mobile contexts, this paper reports on a tool that identifies design patterns in source code. Code is transformed into both platform specific and independent models, and from these design patterns are inferred. MapIt, the tool which implements these functionalities is described.This work was partly funded by ERDF -- European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT -- Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-015095

A Precise Model for Google Cloud Platform

International audienceToday, Google Cloud Platform (GCP) is one of the leaders among cloud APIs. Although it was established only five years ago, GCP has gained notable expansion due to its suite of public cloud services that it based on a huge, solid infrastructure. GCP allows developers to use these services by accessing GCP RESTful API that is described through HTML pages on its website. However, the documentation of GCP API is written in natural language (English prose) and therefore shows several drawbacks, such as Informal Heterogeneous Documentation, Imprecise Types, Implicit Attribute Metadata, Hidden Links, Redundancy and Lack of Visual Support. To avoid confusion and misunderstandings, the cloud developers obviously need a precise specification of the knowledge and activities in GCP. Therefore, this paper introduces GCP MODEL, an inferred formal model-driven specification of GCP which describes without ambiguity the resources offered by GCP. GCP MODEL is conform to the Open Cloud Computing Interface (OCCI) metamodel and is implemented based on the open source model-driven Eclipse-based OCCIWARE tool chain. Thanks to our GCP MODEL, we offer corrections to the drawbacks we identified

Model driven simulation of elastic OCCI cloud resources

International audienceDeploying a cloud configuration in a real cloud platform is mostly cost-and time-consuming, as large number of cloud resources have to be rent for the time needed to run the configuration. Thereafter, cloud simulation tools are used as a cheap alternative to test Cloud configuration. However, most of existing cloud simulation tools require extensive technical skills and does not support simulation of any kind of cloud resources. In this context, using a model-driven approach can be helpful as it allows developers to efficiently describe their needs at a high level of abstraction. To do, we propose, in this article, a Model-Driven Engineering (MDE) approach based on the OCCI (Open Cloud Computing Interface) standard metamodel and CloudSim toolkit. We firstly extend OCCI metamodel for supporting simulation of any kind of cloud resources. Afterward, to illustrate the extensibility of our approach, we enrich the proposed metamodel by new simulation capabilities. As proof of concept, we study the elasticity and pricing strategies of Amazon Web Services (AWS). This article benefits from OCCIware Studio to design an OCCI simulation extension and to provide a simulation designer for designing cloud configurations to be simulated. We detail the approach process from defining an OCCI simulation extension until the generation and the simulation of the OCCI cloud configurations. Finally, we validate the proposed approach by providing a realistic experimentation to study its usability, the resources coverage rate and the cost. The results is compared with the ones computed from AWS

A Model-Driven Tool Chain for OCCI

International audienceOpen Cloud Computing Interface (OCCI) is the only open standard for managing any kinds of cloud resources, e.g., Infrastructure as a Service, Platform as a Service, and Software as a Service. However, no model-driven tooling exists to assist OCCI users in designing, editing, validating, generating, and managing OCCI artifacts (i.e., extensions that represent specific application domains and configurations that define the running systems). In this paper, we propose the first model-driven tool chain for OCCI called OCCIware Studio. This tool chain is based on a metamodel defining the static semantics for the OCCI standard in Ecore and OCL. OCCIware Studio provides OCCI users facilities for designing, editing, validating, generating, and managing OCCI artifacts. We detail the tooled process to define an OCCI extension. In addition, we show how the cloud user can leverage the generated tooling for this extension to create his own OCCI configurations and manage them in the cloud.We illustrate our paper with the OCCI infrastructure extension proposed to define OCCI-compliant compute, network, and storageresources

Towards an Open Set of Real-World Benchmarks for Model Queries and Transformations

International audienceWith the growing size and complexity of systems under design, industry needs a generation of Model-Driven Engineering (MDE) tools, especially model query and transformation, with the proven capability to handle large-scale scenarios. While researchers are proposing several technical solutions in this sense, the community lacks a set of shared scalability benchmarks, that would simplify quantitative assessment of advancements and enable cross-evaluation of different proposals. Benchmarks in previous work have been synthesized to stress specific features of model management, lacking both generality and industrial validity. In this paper, we initiate an effort to define a set of shared benchmarks, gathering queries and transformations from real-world MDE case studies. We make these case available to community evaluation via a public MDE benchmark repository

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu