A Pattern-Based Approach to Scaffold the IT Infrastructure Design Process

Context. The design of Information Technology (IT) infrastructures is a challenging task since it implies proficiency in several areas that are rarely mastered by a single person, thus raising communication problems among those in charge of conceiving, deploying, operating and maintaining/managing them. Most IT infrastructure designs are based on proprietary models, known as blueprints or product-oriented architectures, defined by vendors to facilitate the configuration of a particular solution, based upon their services and products portfolio. Existing blueprints can be facilitators in the design of solutions for a particular vendor or technology. However, since organizations may have infrastructure components from multiple vendors, the use of blueprints aligned with commercial product(s) may cause integration problems among these components and can lead to vendor lock-in. Additionally, these blueprints have a short lifecycle, due to their association with product version(s) or a specific technology, which hampers their usage as a tool for the reuse of IT infrastructure knowledge. Objectives. The objectives of this dissertation are (i) to mitigate the inability to reuse knowledge in terms of best practices in the design of IT infrastructures and, (ii) to simplify the usage of this knowledge, making the IT infrastructure designs simpler, quicker and better documented, while facilitating the integration of components from different vendors and minimizing the communication problems between teams. Method. We conducted an online survey and performed a systematic literature review to support the state of the art and to provide evidence that this research was relevant and had not been conducted before. A model-driven approach was also used for the formalization and empirical validation of well-formedness rules to enhance the overall process of designing IT infrastructures. To simplify and support the design process, a modeling tool, including its abstract and concrete syntaxes was also extended to include the main contributions of this dissertation. Results. We obtained 123 responses to the online survey. Their majority were from people with more than 15 years experience with IT infrastructures. The respondents confirmed our claims regarding the lack of formality and documentation problems on knowledge transfer and only 19% considered that their current practices to represent IT Infrastructures are efficient. A language for modeling IT Infrastructures including an abstract and concrete syntax is proposed to address the problem of informality in their design. A catalog of IT Infrastructure patterns is also proposed to allow expressing best practices in their design. The modeling tool was also evaluated and according to 84% of the respondents, this approach decreases the effort associated with IT infrastructure design and 89% considered that the use of a repository with infrastructure patterns, will help to improve the overall quality of IT infrastructures representations. A controlled experiment was also performed to assess the effectiveness of both the proposed language and the pattern-based IT infrastructure design process supported by the tool. Conclusion. With this work, we contribute to improve the current state of the art in the design of IT infrastructures replacing the ad-hoc methods with more formal ones to address the problems of ambiguity, traceability and documentation, among others, that characterize most of IT infrastructure representations. Categories and Subject Descriptors:C.0 [Computer Systems Organization]: System architecture; D.2.10 [Software Engineering]: Design-Methodologies; D.2.11 [Software Engineering]: Software Architectures-Patterns

From Data Modeling to Knowledge Engineering in Space System Design

The technologies currently employed for modeling complex systems, such as aircraft, spacecraft, or infrastructures, are sufficient for system description, but do not allow deriving knowledge about the modeled systems. This work provides the means to describe space systems in a way that allows automating activities such as deriving knowledge about critical parts of the system’s design, evaluation of test success, and identification of single points of failure

Enhancing Infrastructure Resilience Under Conditions of Incomplete Knowledge of Interdependencies

Today’s infrastructures — such as road, rail, gas, electricity and ICT — are highly interdependent, and may best be viewed as multi-infrastructure systems. A key challenge in seeking to enhance the resilience of multi-infrastructure systems in practice relates to the fact that many interdependencies may be unknown to the operators of these infrastructures. How can we foster infrastructure resilience lacking complete knowledge of interdependencies? In addressing this question, we conceptualize the situation of a hypothetical infrastructure operator faced with incomplete knowledge of the interdependencies to which his infrastructure is exposed. Using a computer model which explicitly represents failure propagations and cascades within a multi-infrastructure system, we seek to identify robust investment strategies on the part of the operator to enhance infrastructure resilience. Our results show that a strategy of constructing redundant interdependencies may be the most robust option for a financially constrained infrastructure operator. These results are specific to the infrastructure configuration tested. However, the developed model may be tailored to the conditions of real-world infrastructure operators faced with a similar dilemma, ultimately helping to foster resilient infrastructures in an uncertain world

Towards semantic software engineering environments

Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they are a way towards Semantic SEEs. In this paper we discuss an ontology-based approach to tool integration and present ODE, an ontology-based SEE

Development of a piezoelectric energy-harvesting sensor: from concept to reality

This study focuses on the development and integrated design over a 24-month period of a high efficiency energy-harvesting (EH) temperature sensor, based on piezoelectric materials, with applications for the sustainability of smart buildings, structures and infrastructures. The EH sensor, harvests the airflow inside Heating, Ventilation and Air Conditioning (HVAC) systems, using a piezoelectric component and an appropriate customizable aerodynamic fin that takes advantage of specific air flow effects, and is implemented for optimizing the energy consumption in buildings. The project was divided in several work-packages (some running in parallel) that cover different aspects of the device development. Some of them focus on engineering aspects (starting from the numerical modeling, then prototyping, and concluding with experimental testing). Other aspects focus on the sensor promotion (including the development of a business plan, the intellectual property rights, the final design and the go-to-market actions). Considering the multidisciplinary character of the project (involving knowledge from fields such as wind engineering, electrical engineering, industrial design, entrepreneurship), this study tries to provide an insight on the complex design issues that arise when such complex, sometimes conflicting and overlapping aspects have to be managed within strict deadlines. In doing so, the most important design and development aspects are critically presented

Data driven wireless network design : a multi-level modeling approach

A

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version