7 research outputs found
New e-Learning system architecture based on knowledge engineering technology
The paper focuses on the field of research on next generational e-Learning facility, in which knowledge-enhanced systems are the most important candidates. In the paper, a reference architecture based on the technologies of knowledge engineering is proposed, which has following three intrinsic characteristics, first, education ontologies are used to facilitate the integration of static learning resource and dynamic learning resource, second, based on semantic-enriched relationships between Learning Objects (LOs), it provides more advanced features for sharing, reusing and repurposing of LOs, third, with the concept of knowledge object, which is extended from LO, an implementing mechanism for knowledge extraction and knowledge evolution in e-Learning facilities is provided. With this reference architecture, a prototype system called FekLoma (Flexible Extensive Knowledge Learning Object Management Architecture) has been realized, and testing on it is carrying out
Survey of grid resource monitoring and prediction strategies.
This literature focuses on grid resource monitoring and prediction, representative monitoring and prediction systems are analyzed and evaluated, then monitoring and prediction strategies for grid resources are summarized and discussed, recommendations are also given for building monitoring sensors and prediction models. During problem definition, one-step-ahead prediction is extended to multi-step-ahead prediction, which is then modeled with computational intelligence algorithms such as neural network and support vector regression. Numerical simulations are performed on benchmark data sets, while comparative results on accuracy and efficiency indicate that support vector regression models achieve superior performance. Our efforts can be utilized as direction for building online monitoring and prediction system for grid resources
Uniform resource visualization
Computing environments continue to increase in scale, heterogeneity, and hierarchy, with resource usage varying dynamically during program execution. Computational and data grids and distributed collaboration environments are examples. To understand performance and gain insights into developing applications that efficiently use system resources, performance visualization has proven useful. Performance visualization tools, however, often are specific to a particular resource at a certain level of the system, possibly with fixed views. Thus, they limit a user\u27s ability to observe a performance problem associated with multiple resources across system levels and platforms. To address this limitation, information integration is necessary. In this research, we propose a new performance visualization framework, Uniform Resource Visualization (URV), focusing on integration of performance information into system-level visualizations. The goal of URV research is to systemize the performance visualization of resources with reusable and composable visualizations
Pattern operators for grid
The definition and programming of distributed applications has become a major research
issue due to the increasing availability of (large scale) distributed platforms
and the requirements posed by the economical globalization. However, such a task
requires a huge effort due to the complexity of the distributed environments: large
amount of users may communicate and share information across different authority
domains; moreover, the “execution environment” or “computations” are dynamic
since the number of users and the computational infrastructure change in time. Grid
environments, in particular, promise to be an answer to deal with such complexity, by
providing high performance execution support to large amount of users, and resource
sharing across different organizations. Nevertheless, programming in Grid environments
is still a difficult task. There is a lack of high level programming paradigms
and support tools that may guide the application developer and allow reusability of
state-of-the-art solutions.
Specifically, the main goal of the work presented in this thesis is to contribute to
the simplification of the development cycle of applications for Grid environments by
bringing structure and flexibility to three stages of that cycle through a commonmodel.
The stages are: the design phase, the execution phase, and the reconfiguration phase.
The common model is based on the manipulation of patterns through pattern operators,
and the division of both patterns and operators into two categories, namely
structural and behavioural. Moreover, both structural and behavioural patterns are
first class entities at each of the aforesaid stages. At the design phase, patterns can
be manipulated like other first class entities such as components. This allows a more
structured way to build applications by reusing and composing state-of-the-art patterns.
At the execution phase, patterns are units of execution control: it is possible, for
example, to start or stop and to resume the execution of a pattern as a single entity. At
the reconfiguration phase, patterns can also be manipulated as single entities with the
additional advantage that it is possible to perform a structural reconfiguration while
keeping some of the behavioural constraints, and vice-versa. For example, it is possible
to replace a behavioural pattern, which was applied to some structural pattern,
with another behavioural pattern.
In this thesis, besides the proposal of the methodology for distributed application
development, as sketched above, a definition of a relevant set of pattern operators
was made. The methodology and the expressivity of the pattern operators were assessed
through the development of several representative distributed applications. To
support this validation, a prototype was designed and implemented, encompassing
some relevant patterns and a significant part of the patterns operators defined. This
prototype was based in the Triana environment; Triana supports the development and
deployment of distributed applications in the Grid through a dataflow-based programming
model. Additionally, this thesis also presents the analysis of a mapping of some
operators for execution control onto the Distributed Resource Management Application
API (DRMAA).
This assessment confirmed the suitability of the proposed model, as well as the
generality and flexibility of the defined pattern operatorsDepartamento de Informática and Faculdade de Ciências e Tecnologia of the Universidade
Nova de Lisboa;
Centro de Informática e Tecnologias da Informação of the FCT/UNL;
Reitoria da Universidade Nova de Lisboa;
Distributed Collaborative Computing Group, Cardiff University, United Kingdom;
Fundação para a Ciência e Tecnologia;
Instituto de Cooperação Científica e Tecnológica Internacional;
French Embassy in Portugal;
European Union Commission through the Agentcities.NET and Coordina projects;
and the European Science Foundation, EURESCO
A dynamic prediction and monitoring framework for distributed applications
This research builds on an application performance prediction and characterisation environment (known as PACE), whose aim is to characterise the performance-critical elements of both an application and its target execution environment and deduce from this model a predicted behaviour of the application prior to its execution.
Underlying the research presented in this thesis are a number of themes: the tasks involved in the performance characterisation of applications and how this might be semi- automated: the level of abstraction at which these characterisations are performed in order to maintain a sufficient predictive accuracy: the automated refinement of these characterisations from runtime performance data: the extension of both the target programming languages and the class of application at which these techniques are aimed.
In this thesis a number of novel extensions to PACE are described. These include: a new transaction-based performance characterisation language that provides a flexible framework for describing broader classes of application; a performance monitoring framework (based on an extension to the OpenGroup’s Application Response Measurement (ARM) standard) for the runtime monitoring of an application's data-dependent components and the automated refinement of performance models: an adaptation of this performance characterisation for the prediction of Java applications. These contributions are demonstrated through their application to a number of scientific kernels. This thesis also documents how these predictive results can be used in a real-time distributed runtime management environment, and also how these techniques can be applied to non-scientific codes, in particular to an IBM request-driven distributed web services demonstrator
237 An Infrastructure for Monitoring and Management in Computational Grids
Abstract. We present the design and implementation of an infrastructure that enables monitoring of resources, services, and applications in a computational grid and provides a toolkit to help manage these entities when faults occur. This infrastructure builds on three basic monitoring components: sensors to perform measurements, actuators to perform actions, and an event service to communicate events between remote processes. We describe how we apply our infrastructure to support a grid service and an application: (1) the Globus Metacomputing Directory Service; and (2) a long-running and coarse-grained parameter study application. We use these application to show that our monitoring infrastructure is highly modular, conveniently retargettable, and extensible.