Design methods for sequence controllers play an important role in modern industrial automation. The Programmable Logic Controller (PLC) in general meets today's automation requirements. The increasing complexity and varying needs of modern discrete industrial systems have challenged the traditional design methods such as the use of Ladder Logic Diagrams (LLDs) for PLCs. This paper presents a new method for using Petri net models in order to design and implement a sequence controller for a small scale robotic cell which consists of a robotic manipulator, a variety of sensors and electro-pneumatic actuators. The proposed method leads directly to the generation of the associated LLD and it has proved to be effective through the application to sequence control of a small-scale industrial system. In addition, it has reduced the period for developing, debugging and reengineering of the LLD, compared to the traditional method that directly prepares an LLD. Experimental results are included to show the effectiveness of the PN/LLD controller.

Accessing objects in software applications usually breaks down to four basic operations: Create, Read, Update, and Delete (CRUD). The latter is a well-known pattern in software development and web application domains. CRUD has been applied primarily to relational database-backed systems, object-relational mappers (ORMs), and relevant tools since the early ’80s. In the era of cloud computing, though, relational databases are not always the most efficient service to store application data due to the application requirements shifting towards non-functional requirements such as observability. Command Query Responsibility Segregation (CQRS) and Event Sourcing (ES) are a couple of alternative patterns on which one can build applications. However, there is a lack of tooling and guidance, especially for inexperienced practitioners. In addition, as reported in the literature, this approach requires a thorough understanding of the application domain. In this paper, we investigate the possibility of bridging CRUD modeling technics with the CQRS-ES patterns systematically and generically. Upon success, we will be able to build new event-sourced applications in the same manner as we now utilize ORMs and tools to accelerate the process. Moreover, legacy systems might also benefit by enhancing their current operation with an event-source component and, if needed, gradually replacing obsolete parts.

This paper presents a novel approach to address the challenges of self-adaptive privacy in cloud computing environments (CCE). Under the Cloud-InSPiRe project, the aim is to provide an interdisciplinary framework and a beta-version tool for self-adaptive privacy design, effectively focusing on the integration of technical measures with social needs. To address that, a pilot taxonomy that aligns technical, infrastructural, and social requirements is proposed after two supplementary surveys that have been conducted, focusing on users’ privacy needs and developers’ perspectives on self-adaptive privacy. Through the integration of users’ social identity-based practices and developers’ insights, the taxonomy aims to provide clear guidance for developers, ensuring compliance with regulatory standards and fostering a user-centric approach to self-adaptive privacy design tailored to diverse user groups, ultimately enhancing satisfaction and confidence in cloud services.

The rapid development of cloud computing environments has resulted in various advances and personalized services for users, raising thus several privacy issues. Towards this, research focused on privacy safeguard in the cloud, indicating solutions on the area of self-adaptive privacy. A detailed review is produced to bring forward the carried out work and to analyze it in terms of privacy interdisciplinary standards. In this regard, our work presents the existing self-adaptive privacy approaches and identifies the context for which they have been developed. Moreover, a corresponding classification scheme is provided. The findings give also insights on the proposed tools, which were critically analyzed. This review aims at indicating the developments and limitations of the area, providing potentials of future work in less discussed aspects of the self-adaptive privacy in cloud under an interdisciplinary point of view.