AO-OIL: um middleware orientado a aspectos baseado em uma arquitetura de referência

Middleware platforms have been widely used as an underlying infrastructure to the development of distributed applications. They provide distribution and heterogeneity transparency and a set of services that ease the construction of distributed applications. Nowadays, the middlewares accommodate an increasing variety of requirements to satisfy distinct application domains. This broad range of application requirements increases the complexity of the middleware, due to the introduction of many cross-cutting concerns in the architecture, which are not properly modularized by traditional programming techniques, resulting in a tangling and spread of theses concerns in the middleware code. The presence of these cross-cutting concerns limits the middleware scalability and aspect-oriented paradigm has been used successfully to improve the modularity, extensibility and customization capabilities of middleware. This work presents AO-OiL, an aspect-oriented (AO) middleware architecture, based on the AO middleware reference architecture. This middleware follows the philosophy that the middleware functionalities must be driven by the application requirements. AO-OiL consists in an AO refactoring of the OiL (Orb in Lua) middleware in order to separate basic and crosscutting concerns. The proposed architecture was implemented in Lua and RE-AspectLua. To evaluate the refactoring impact in the middleware architecture, this paper presents a comparative analysis of performance between AO-OiL and OiL

AdaptMCloud: uma estratégia para adaptação dinâmica de aplicações Multi-Cloud

Multi-Cloud Applications are composed of services offered by multiple cloud platforms where the user/developer has full knowledge of the use of such platforms. The use of multiple cloud platforms avoids the following problems: (i) vendor lock-in, which is dependency on the application of a certain cloud platform, which is prejudicial in the case of degradation or failure of platform services, or even price increasing on service usage; (ii) degradation or failure of the application due to fluctuations in quality of service (QoS) provided by some cloud platform, or even due to a failure of any service. In multi-cloud scenario is possible to change a service in failure or with QoS problems for an equivalent of another cloud platform. So that an application can adopt the perspective multi-cloud is necessary to create mechanisms that are able to select which cloud services/platforms should be used in accordance with the requirements determined by the programmer/user. In this context, the major challenges in terms of development of such applications include questions such as: (i) the choice of which underlying services and cloud computing platforms should be used based on the defined user requirements in terms of functionality and quality (ii) the need to continually monitor the dynamic information (such as response time, availability, price, availability), related to cloud services, in addition to the wide variety of services, and (iii) the need to adapt the application if QoS violations affect user defined requirements. This PhD thesis proposes an approach for dynamic adaptation of multi-cloud applications to be applied when a service is unavailable or when the requirements set by the user/developer point out that other available multi-cloud configuration meets more efficiently. Thus, this work proposes a strategy composed of two phases. The first phase consists of the application modeling, exploring the similarities representation capacity and variability proposals in the context of the paradigm of Software Product Lines (SPL). In this phase it is used an extended feature model to specify the cloud service configuration to be used by the application (similarities) and the different possible providers for each service (variability). Furthermore, the non-functional requirements associated with cloud services are specified by properties in this model by describing dynamic information about these services. The second phase consists of an autonomic process based on MAPE-K control loop, which is responsible for selecting, optimally, a multicloud configuration that meets the established requirements, and perform the adaptation. The adaptation strategy proposed is independent of the used programming technique for performing the adaptation. In this work we implement the adaptation strategy using various programming techniques such as aspect-oriented programming, context-oriented programming and components and services oriented programming. Based on the proposed steps, we tried to assess the following: (i) the process of modeling and the specification of non-functional requirements can ensure effective monitoring of user satisfaction; (ii) if the optimal selection process presents significant gains compared to sequential approach; and (iii) which techniques have the best trade-off when compared efforts to development/modularity and performance.