Lenin Erazo-Garzón

Cloud computing is an emerging technology that enables on-demand software deployment and the use of suitable infrastructure for native applications. In this context, cloud-native architectures have emerged as a promising alternative to monolithic applications, facilitating the sustainable growth of organizations. This paper presents a systematic review aimed at providing a comprehensive overview of the state of the art, current trends, and future research opportunities regarding strategies for migrating monolithic applications to cloud-native architectures. The review covers 41 relevant studies, which have been analyzed according to the key phases of the migration process: planning, evaluation, refactoring, transition, and integration into cloud-native environments. Among the most significant findings, microservice-based architectures and cloud-oriented design patterns are the most studied topics, accounting for approximately 73 % of the analyzed papers. Additionally, the review identifies approaches such as decision-making frameworks, refactoring of monolithic code, application of Model-Driven Engineering (MDE), reduction of technical debt, and use of orchestration tools.

The Internet of Things (IoT) has revolutionized numerous sectors, with healthcare being a prominent beneficiary. One key area of advancement is Ambient Assisted Living (AAL), which leverages Information and Communication Technologies (ICT) like IoT to improve the quality of life for vulnerable populations, particularly seniors. However, despite efforts to tailor solutions to the needs of these environments, the prevailing approach often becomes overly focused on intricate implementation details rather than the core characteristics of the problem domain. This narrow focus inhibits generalization and leads to unsustainable solutions due to these environments’ diverse, dynamic, and scalable nature. In response, emerging technology paradigms, such as Fog Computing (FC), have emerged to enhance performance and other quality aspects. FC enables the deployment of distributed, latency-aware applications and services. Therefore, this paper introduces FOGAAL, a Domain-Specific Language (DSL) tool crafted to design AAL architectures, including the FC advantages. To demonstrate FOGAAL’s practical applicability, this contribution uses FOGAAL to build an AAL architecture for a real scenario; in addition, it has an empirical evaluation employing the Technology Acceptance Model (TAM) to gauge user perceptions while utilizing the tool for modeling AAL Architectures. The evaluation, conducted as a quasi-experiment, underscore the tool’s alignment with requirements and its potential for adoption, as evidenced by software engineers who have expressed their intention to use FOGAAL when creating architecture for AAL environments.

Hoy en día, uno de los desafíos tecnológicos es el desarrollo de software para sistemas de IoT, ya que operan en escenarios altamente cambiantes, siendo complejo con las metodologías de Ingeniería de Software tradicionales identificar todos los requisitos del sistema en la etapa de desarrollo. Una alternativa es incrementar su autonomía, dotándoles de capacidades de autoconsciencia con el apoyo de los modelos en tiempo de ejecución, a fin de trasladar varias de las funcionalidades que se programan durante el desarrollo al tiempo de ejecución. Este trabajo doctoral propone desarrollar una metodología basada en modelos en tiempo de ejecución para la construcción y operación de sistemas autoconscientes de IoT.

The Internet of Things (IoT) is a technological paradigm involved in a diversity of domains with favorable impacts on people’s daily lives and the development of industry and cities. Nowadays, one of the most critical challenges is developing software for IoT systems since the traditional Software Engineering methodologies and tools are unproductive in the face of the complex requirements resulting from the highly distributed, heterogeneous, and dynamic scenarios in which these systems operate. Model-Driven Engineering (MDE) emerges as an appropriate approach to abstract the complexity of IoT systems. However, there are no domain-specific languages (DSLs) aligned to standardized reference architectures for IoT. Furthermore, existing DSLs have an incomplete language to represent the IoT entities that may be needed at the edge, fog, and cloud layers to monitor IoT environments. Therefore, this paper proposes a domain-specific language named Monitor-IoT, which supports developers in designing multi-layer monitoring architectures for IoT systems with high abstraction, expressiveness, and flexibility. Monitor-IoT consists of a high-level visual modeling language and a metamodel aligned with the ISO/IEC 30141:2018 reference architecture. In addition, it provides a language capable of modeling architectures with a wide variety of digital entities and dataflows (synchronous and asynchronous) between them across the edge, fog, and cloud layers to support the monitoring of a diversity of IoT scenarios. The empirical evaluation of Monitor-IoT through the application of an experiment, which contemplates the use of the Technology Acceptance Model (TAM), demonstrates the intention of the participants to use this tool in the future since they consider it easy to use and useful.