A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers

Erotic Aspects of Everyday Life as a Challenge for Ubiquitous Computing

In this paper we discuss how interactive technology disables or enables erotic aspects of everyday life, and we discuss a number of design concepts in order to relate erotic aspects to the issue of visibility versus invisibility in ambient computing. This discussion has general relevance for the study of residual categories in ubiquitous computing

Pervasive Pedagogy: Collaborative Cloud-Based Composing Using Google Drive

Cloud-based services designed for educational use, like Google Apps for Education (GAFE), afford deeply collaborative activities across multiple applications. Through primary research, the authors discovered that cloud-based technologies such as GAFE and Google Drive afford new opportunities for collaborative cross-platform composing and student engagement. These affordances require new pedagogies to transform these potentialities into practice, as well as a reexamination of contemporary theory of computers and composition. The authors’ journey implementing Google Drive as a composing and communication environment required continually remediating content, relationships, practices, and their own identities as they interacted with students in the cloud. This chapter addresses how GAFE and Google Drive engage students in the composition classroom, redefine and transform pedagogical and curricular concepts, and improve students’ experience and learning

A Pervasive Computational Intelligence based Cognitive Security Co-design Framework for Hype-connected Embedded Industrial IoT

The amplified connectivity of routine IoT entities can expose various security trajectories for cybercriminals to execute malevolent attacks. These dangers are even amplified by the source limitations and heterogeneity of low-budget IoT/IIoT nodes, which create existing multitude-centered and fixed perimeter-oriented security tools inappropriate for vibrant IoT settings. The offered emulation assessment exemplifies the remunerations of implementing context aware co-design oriented cognitive security method in assimilated IIoT settings and delivers exciting understandings in the strategy execution to drive forthcoming study. The innovative features of our system is in its capability to get by with irregular system connectivity as well as node limitations in terms of scares computational ability, limited buffer (at edge node), and finite energy. Based on real-time analytical data, projected scheme select the paramount probable end-to-end security system possibility that ties with an agreed set of node constraints. The paper achieves its goals by recognizing some gaps in the security explicit to node subclass that is vital to our system’s operations

Cyberspace As/And Space

The appropriate role of place- and space-based metaphors for the Internet and its constituent nodes and networks is hotly contested. This essay seeks to provoke critical reflection on the implications of place- and space-based theories of cyberspace for the ongoing production of networked space more generally. It argues, first, that adherents of the cyberspace metaphor have been insufficiently sensitive to the ways in which theories of cyberspace as space themselves function as acts of social construction. Specifically, the leading theories all have deployed the metaphoric construct of cyberspace to situate cyberspace, explicitly or implicitly, as separate space. This denies all of the ways in which cyberspace operates as both extension and evolution of everyday spatial practice. Next, it argues that critics of the cyberspace metaphor have confused two senses of space and two senses of metaphor. The cyberspace metaphor does not refer to abstract, Cartesian space, but instead expresses an experienced spatiality mediated by embodied human cognition. Cyberspace in this sense is relative, mutable, and constituted via the interactions among practice, conceptualization, and representation. The insights drawn from this exercise suggest a very different way of understanding both the spatiality of cyberspace and its architectural and regulatory challenges. In particular, they suggest closer attention to three ongoing shifts: the emergence of a new sense of social space, which the author calls networked space; the interpenetration of embodied, formerly bounded space by networked space; and the ways in which these developments alter, instantiate, and disrupt geographies of power

An Exploratory Sequential Mixed Methods Approach to Understanding Researchers’ Data Management Practices at UVM: Integrated Findings to Develop Research Data Services

This article reports on the integrated findings of an exploratory sequential mixed methods research design aimed to understand data management behaviors and challenges of faculty at the University of Vermont (UVM) in order to develop relevant research data services. The exploratory sequential mixed methods design is characterized by an initial qualitative phase of data collection and analysis, followed by a phase of quantitative data collection and analysis, with a final phase of integration or linking of data from the two separate strands of data. A joint display was used to integrate data focused on the three primary research questions: How do faculty at UVM manage their research data, in particular how do they share and preserve data in the long-term?; What challenges or barriers do UVM faculty face in effectively managing their research data?; and What institutional data management support or services are UVM faculty interested in? As a result of the analysis, this study suggests four major areas of research data services for UVM to address: infrastructure, metadata, data analysis and statistical support, and informational research data services. The implementation of these potential areas of research data services is underscored by the need for cross-campus collaboration and support