A multi-agent approach for design consistency checking

The last decade has seen an explosion of interest to advanced product development methods, such as Computer Integrated Manufacture, Extended Enterprise and Concurrent Engineering. As a result of the globalization and future distribution of design and manufacturing facilities, the cooperation amongst partners is becoming more challenging due to the fact that the design process tends to be sequential and requires communication networks for planning design activities and/or a great deal of travel to/from designers' workplaces. In a virtual environment, teams of designers work together and use the Internet/Intranet for communication. The design is a multi-disciplinary task that involves several stages. These stages include input data analysis, conceptual design, basic structural design, detail design, production design, manufacturing processes analysis, and documentation. As a result, the virtual team, normally, is very changeable in term of designers' participation. Moreover, the environment itself changes over time. This leads to a potential increase in the number of design. A methodology of Intelligent Distributed Mismatch Control (IDMC) is proposed to alleviate some of the related difficulties. This thesis looks at the Intelligent Distributed Mismatch Control, in the context of the European Aerospace Industry, and suggests a methodology for a conceptual framework based on a multi-agent architecture. This multi-agent architecture is a kernel of an Intelligent Distributed Mismatch Control System (IDMCS) that aims at ensuring that the overall design is consistent and acceptable to all participating partners. A Methodology of Intelligent Distributed Mismatch Control is introduced and successfully implemented to detect design mismatches in complex design environments. A description of the research models and methods for intelligent mismatch control, a taxonomy of design mismatches, and an investigation into potential applications, such as aerospace design, are presented. The Multi-agent framework for mismatch control is developed and described. Based on the methodology used for the IDMC application, a formal framework for a multi-agent system is developed. The Methods and Principles are trialed out using an Aerospace Distributed Design application, namely the design of an A340 wing box. The ontology of knowledge for agent-based Intelligent Distributed Mismatch Control System is introduced, as well as the distributed collaborative environment for consortium based projects

Protecting Personal Private Information in Collaborative Environments

The ability to collaborate has always been vitally important to businesses and enterprises. With the availability of current networking and computing power, the creation of Collaborative Working Environments (CWEs) has allowed for this process to occur anytime over any geographical distance. Sharing information between individuals through collaborative environments creates new challenges in privacy protection for organizations and the members of organizations. This thesis confronts the problems when attempting to protect the personal private information of collaborating individuals. In this thesis, a privacy-by-policy approach is taken to addressing the issue of protecting private information within collaborative environments. A privacy-by-policy approach to privacy protection provides collaborating individuals with notice and choice surrounding their private information, in order to provide an individual with a level of control over how their information is to be used. To this end, a collaborative privacy architecture for providing privacy within a collaborative environment is presented. This architecture uses ontologies to express the static concept and relation definitions required for privacy and collaboration. The collaborative privacy architecture also contains a Collaborative Privacy Manager (CPM) service which handles changes in dynamic collaborative environments. The goals of this thesis are to provide privacy mechanisms for the non-client centric situation of collaborative working environments. This thesis also strives to provide privacy through technically enforceable and customizable privacy policies. To this end, individual collaborators are provided with access, modification rights, and transparency through the use of ontologies built into the architecture. Finally, individual collaborators are provided these privacy protections in a way that is easy to use and understand and use. A collaborative scenario as a test case is described to present how this architecture would benefit individuals and organizations when they are engaged in collaborative work. In this case study a university and hospital are engaged in collaborative research which involves the use of private information belonging to collaborators and patients from the hospital. This case study also highlights how different organizations can be under different sets of legislative guidelines and how these guidelines can be incorporated into the privacy architecture. Through this collaboration scenario an implementation of the collaborative privacy architecture is provided, along with results from semantic and privacy rule executions, and measurements of how actions carried out by the architecture perform under various conditions

A mapping study on documentation in Continuous Software Development

Context: With an increase in Agile, Lean, and DevOps software methodologies over the last years (collectively referred to as Continuous Software Development (CSD)), we have observed that documentation is often poor. Objective: This work aims at collecting studies on documentation challenges, documentation practices, and tools that can support documentation in CSD. Method: A systematic mapping study was conducted to identify and analyze research on documentation in CSD, covering publications between 2001 and 2019. Results: A total of 63 studies were selected. We found 40 studies related to documentation practices and challenges, and 23 studies related to tools used in CSD. The challenges include: informal documentation is hard to understand, documentation is considered as waste, productivity is measured by working software only, documentation is out-of-sync with the software and there is a short-term focus. The practices include: non-written and informal communication, the usage of development artifacts for documentation, and the use of architecture frameworks. We also made an inventory of numerous tools that can be used for documentation purposes in CSD. Overall, we recommend the usage of executable documentation, modern tools and technologies to retrieve information and transform it into documentation, and the practice of minimal documentation upfront combined with detailed design for knowledge transfer afterwards. Conclusion: It is of paramount importance to increase the quantity and quality of documentation in CSD. While this remains challenging, practitioners will benefit from applying the identified practices and tools in order to mitigate the stated challenges

Awareness support for learning designers in collaborative authoring for adaptive learning

Adaptive learning systems offer students a range of appropriate learning options based on the learners’ characteristics. It is, therefore, necessary for such systems to maintain a hyperspace and knowledge space that consists of a large volume of domain and pedagogical knowledge, learner information, and adaptation rules. As a consequence, for a solitary teacher, developing learning resources would be time consuming and requires the teacher to be an expert of many topics. In this research, the problems of authoring adaptive learning resources are classified into issues concerning interoperability, efficiency, and collaboration.This research particularly addresses the question of how teachers can collaborate in authoring adaptive learning resources and be aware of what has happened in the authoring process. In order to experiment with collaboration, it was necessary to design a collaborative authoring environment for adaptive learning. This was achieved by extending an open sourced authoring tool of IMS Learning Design (IMS LD), ReCourse, to be a prototype of Collaborative ReCourse that includes the workspace awareness information features: Notes and History. It is designed as a tool for asynchronous collaboration for small groups of learning designers. IMS LD supports interoperability and adaptation. Two experiments were conducted. The first experiment was a workspace awareness study in which participants took part in an artificial collaborative scenario. They were divided into 2 groups; one group worked with ReCourse, the other with Collaborative ReCourse. The results provide evidence regarding the advantages of Notes and History for enhancing workspace awareness in collaborative authoring of learning designs.The second study tested the system more thoroughly as the participants had to work toward real goals over a much longer time frame. They were divided into four groups; two groups worked with ReCourse, while the others worked with Collaborative ReCourse. The experiment result showed that authoring of learning designs can be approached with a Process Structure method with implicit coordination and without role assignment. It also provides evidence that collaboration is possible for authoring IMS LD Level A for non-adapting and Level B for adapting materials. Notes and History assist in producing good quality output.This research has several contributions. From the literature study, it presents a comparison analysis of existing authoring tools, as well as learning standards. Furthermore, it presents a collaborative authoring approach for creating learning designs and describes the granularity level on which collaborative authoring for learning designs can be carried out. Finally, experiments using this approach show the advantages of having Notes and History for enhancing workspace awareness that and how they benefit the quality of learning designs

Distributed Load Testing by Modeling and Simulating User Behavior

Modern human-machine systems such as microservices rely upon agile engineering practices which require changes to be tested and released more frequently than classically engineered systems. A critical step in the testing of such systems is the generation of realistic workloads or load testing. Generated workload emulates the expected behaviors of users and machines within a system under test in order to find potentially unknown failure states. Typical testing tools rely on static testing artifacts to generate realistic workload conditions. Such artifacts can be cumbersome and costly to maintain; however, even model-based alternatives can prevent adaptation to changes in a system or its usage. Lack of adaptation can prevent the integration of load testing into system quality assurance, leading to an incomplete evaluation of system quality. The goal of this research is to improve the state of software engineering by addressing open challenges in load testing of human-machine systems with a novel process that a) models and classifies user behavior from streaming and aggregated log data, b) adapts to changes in system and user behavior, and c) generates distributed workload by realistically simulating user behavior. This research contributes a Learning, Online, Distributed Engine for Simulation and Testing based on the Operational Norms of Entities within a system (LODESTONE): a novel process to distributed load testing by modeling and simulating user behavior. We specify LODESTONE within the context of a human-machine system to illustrate distributed adaptation and execution in load testing processes. LODESTONE uses log data to generate and update user behavior models, cluster them into similar behavior profiles, and instantiate distributed workload on software systems. We analyze user behavioral data having differing characteristics to replicate human-machine interactions in a modern microservice environment. We discuss tools, algorithms, software design, and implementation in two different computational environments: client-server and cloud-based microservices. We illustrate the advantages of LODESTONE through a qualitative comparison of key feature parameters and experimentation based on shared data and models. LODESTONE continuously adapts to changes in the system to be tested which allows for the integration of load testing into the quality assurance process for cloud-based microservices

Advances in Grid Computing

This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems

Interconnected Services for Time-Series Data Management in Smart Manufacturing Scenarios

xvii, 218 p.The rise of Smart Manufacturing, together with the strategic initiatives carried out worldwide, have promoted its adoption among manufacturers who are increasingly interested in boosting data-driven applications for different purposes, such as product quality control, predictive maintenance of equipment, etc. However, the adoption of these approaches faces diverse technological challenges with regard to the data-related technologies supporting the manufacturing data life-cycle. The main contributions of this dissertation focus on two specific challenges related to the early stages of the manufacturing data life-cycle: an optimized storage of the massive amounts of data captured during the production processes and an efficient pre-processing of them. The first contribution consists in the design and development of a system that facilitates the pre-processing task of the captured time-series data through an automatized approach that helps in the selection of the most adequate pre-processing techniques to apply to each data type. The second contribution is the design and development of a three-level hierarchical architecture for time-series data storage on cloud environments that helps to manage and reduce the required data storage resources (and consequently its associated costs). Moreover, with regard to the later stages, a thirdcontribution is proposed, that leverages advanced data analytics to build an alarm prediction system that allows to conduct a predictive maintenance of equipment by anticipating the activation of different types of alarms that can be produced on a real Smart Manufacturing scenario