127,738 research outputs found
Teaching high-performance service in a cluster computing course
[EN] Most courses on cluster computing in graduate and postgraduate studies are focused on parallel programming and high-performance/high-throughput computing. This is the typical usage of clusters in academia and research centres. However, nowadays, many companies are providing web, mail and, in general, Internet services using computer clusters. These services require a different ``cluster flavour'': high-performance service and high availability. Despite the fact that computer clusters for each environment demand a different configuration, most university cluster computing courses keep focusing only on high-performance computing, ignoring other possibilities. In this paper, we propose several teaching strategies for a course on cluster computing that could fill this gap. The content developed here would be taught as a part of the course. The subject shows several strategies about how to configure, test and evaluate a high-availability/load-balanced Internet server. A virtualization-based platform is used to build a cluster prototype, using Linux as its operating system. Evaluation of the course shows that students knowledge and skills on the subject are improved at the end of the course. On the other hand, regarding the teaching methodology, the results obtained in the yearly survey of the University confirm student satisfaction.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and by FEDER funds under Grant TIN2015-66972-C5-1-R.LĂłpez RodrĂguez, PJ.; Baydal Cardona, ME. (2018). Teaching high-performance service in a cluster computing course. Journal of Parallel and Distributed Computing. 117:138-147. https://doi.org/10.1016/j.jpdc.2018.02.027S13814711
Quality-aware model-driven service engineering
Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects
ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box
character of services
Managing evolution and change in web-based teaching and learning environments
The state of the art in information technology and educational technologies is evolving constantly.
Courses taught are subject to constant change from organisational and subject-specific reasons. Evolution
and change affect educators and developers of computer-based teaching and learning environments alike â
both often being unprepared to respond effectively. A large number of educational systems are designed
and developed without change and evolution in mind. We will present our approach to the design and
maintenance of these systems in rapidly evolving environments and illustrate the consequences of evolution
and change for these systems and for the educators and developers responsible for their implementation and
deployment. We discuss various factors of change, illustrated by a Web-based virtual course, with the
objective of raising an awareness of this issue of evolution and change in computer-supported teaching and
learning environments. This discussion leads towards the establishment of a development and management
framework for teaching and learning systems
Modelling multi-tier enterprise applications behaviour with design of experiments technique
Queueing network models are commonly used for performance modelling. However, through application development stage analytical models might not be able to continuously reflect performance, for example due to performance bugs or minor changes in the application code that cannot be readily reflected in the queueing model. To cope with this problem, a measurement-based approach adopting Design of Experiments (DoE) technique is proposed. The applicability of the proposed method is demonstrated on a complex 3-tier e-commerce application that is difficult to model with queueing networks
FORGE: An eLearning Framework for Remote Laboratory Experimentation on FIRE Testbed Infrastructure
The Forging Online Education through FIRE (FORGE) initiative provides educators and learners in higher education with access to world-class FIRE testbed infrastructure. FORGE supports experimentally driven research in an eLearning environment by complementing traditional classroom and online courses with interactive remote laboratory experiments. The project has achieved its objectives by defining and implementing a framework called FORGEBox. This framework offers the methodology, environment, tools and resources to support the creation of HTML-based online educational material capable accessing virtualized and physical FIRE testbed infrastruc- ture easily. FORGEBox also captures valuable quantitative and qualitative learning analytic information using questionnaires and Learning Analytics that can help optimise and support student learning. To date, FORGE has produced courses covering a wide range of networking and communication domains. These are freely available from FORGEBox.eu and have resulted in over 24,000 experiments undertaken by more than 1,800 students across
10 countries worldwide. This work has shown that the use of remote high- performance testbed facilities for hands-on remote experimentation can have a valuable impact on the learning experience for both educators and learners. Additionally, certain challenges in developing FIRE-based courseware have been identified, which has led to a set of recommendations in order to support the use of FIRE facilities for teaching and learning purposes
Estimating Fire Weather Indices via Semantic Reasoning over Wireless Sensor Network Data Streams
Wildfires are frequent, devastating events in Australia that regularly cause
significant loss of life and widespread property damage. Fire weather indices
are a widely-adopted method for measuring fire danger and they play a
significant role in issuing bushfire warnings and in anticipating demand for
bushfire management resources. Existing systems that calculate fire weather
indices are limited due to low spatial and temporal resolution. Localized
wireless sensor networks, on the other hand, gather continuous sensor data
measuring variables such as air temperature, relative humidity, rainfall and
wind speed at high resolutions. However, using wireless sensor networks to
estimate fire weather indices is a challenge due to data quality issues, lack
of standard data formats and lack of agreement on thresholds and methods for
calculating fire weather indices. Within the scope of this paper, we propose a
standardized approach to calculating Fire Weather Indices (a.k.a. fire danger
ratings) and overcome a number of the challenges by applying Semantic Web
Technologies to the processing of data streams from a wireless sensor network
deployed in the Springbrook region of South East Queensland. This paper
describes the underlying ontologies, the semantic reasoning and the Semantic
Fire Weather Index (SFWI) system that we have developed to enable domain
experts to specify and adapt rules for calculating Fire Weather Indices. We
also describe the Web-based mapping interface that we have developed, that
enables users to improve their understanding of how fire weather indices vary
over time within a particular region.Finally, we discuss our evaluation results
that indicate that the proposed system outperforms state-of-the-art techniques
in terms of accuracy, precision and query performance.Comment: 20pages, 12 figure
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