Universidad Politécnica de Valencia
Department:Departamento de Sistemas Informaticos y Computacion
Position:Faculty Member
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Papers
Automatic Replication of WSRF-based Grid Services via Operation Providers
published in 'Future Generation Computer Systems (International Journal of Grid Computing)', 2008
The advent of service-oriented architectures in Grid environments has fostered the development of applications in distributed deployments. The Globus Toolkit 4 (GT4) and its implementation of stateful Web services, via the WS-Resource Framework (WSRF), is a suitable platform to develop these Grid services. This way, its increased usage in many scientific areas reveals new scenarios where fault-tolerance and high availability should be considered. This paper describes a library that manages the automatic replication of WSRF-based Grid services. This functionality can be plugged to existing Grid services, by means of minimal changes in its source code, to achieve state replication through WS-Resources. The architecture of the library and its performance evaluation are described. In particular, two different replica topologies are addressed: ring-based and leaf-to-root complete binary tree, in order to achieve resource state update in logarithmic time with respect to the number of replicas. Finally, the paper describes the integration of the replication library into a service-oriented metascheduler to enhance fault-tolerance and to guarantee service availability.
Download (.004)Protein Design Based on Parallel Dimensional Reduction
published in 'Journal of Chemical Information and Modelling', 2008
The design of proteins with targeted properties is a computationally intensive task with large memory requirements. We have developed a novel approach that combines a dimensional reduction of the problem with a High Performance Computing platform to efficiently design large proteins. This tool overcomes the memory limits of the process, allowing the design of proteins whose requirements prevent them to be designed in traditional sequential platforms. We have applied our algorithm to the design of functional proteins, optimizing for both catalysis and stability. We have also studied the redesign of dimerization interfaces, taking simultaneously into account the stability of the subunits of the dimer. However, our methodology can be applied to any computational chemistry application requiring combinatorial optimization techniques.
A Grid Computing-based Approach for the Acceleration of Simulations in Cardiology
published in 'IEEE Transactions on Information Technology in Biomedicine', 2008
This paper combines high-performance computing and grid computing technologies to accelerate multiple executions of a biomedical application that simulates the action potential propagation on cardiac tissues. First, a parallelization strategy was employed to accelerate the execution of simulations on a cluster of personal computers (PCs). Then, grid computing was employed to concurrently perform the multiple simulations that compose the cardiac case studies on the resources of a grid deployment, by means of a service-oriented approach. This way, biomedical experts are provided with a gateway to easily access a grid infrastructure for the execution of these research studies. Emphasis is stressed on the methodology employed. In order to assess the benefits of the grid, a cardiac case study, which analyzes the effects of premature stimulation on reentry generation during myocardial ischemia, has been carried out. The collaborative usage of a distributed computing infrastructure has reduced the time required for the execution of cardiac case studies, which allows, for example, to take more accurate decisions when evaluating the effects of new antiarrhythmic drugs on the electrical activity of the heart.
A service-oriented WSRF-based architecture for metascheduling on computational Grids
published in 'Future Generation Computer Systems (International Journal of Grid Computing)', 2008
This paper describes a Grid service developed over the Globus Toolkit 4, which provides multi-user resource brokering on computational Grids. Both the architecture and implementation details are covered, emphasising the usage of the WSRF specifications and GSI-based security to create a generic, secure and interoperable metascheduler. In addition, we also describe the development of a graphical client-side application that provides an ubiquitous access to the metascheduler service. This work is currently being employed in production for the execution of a biomedical application that simulates the electrical activity of cardiac tissues.
Vulnerability to Reentry in a Regionally Ischemic Tissue
published in 'Annals of Biomedical Engineering', 2007
Sudden cardiac death is mainly provoked by arrhythmogenic processes. During myocardial ischemia many malignant arrhythmias, such as reentry, take place and can degenerate into ventricular fibrillation. It is thus of great interest to unravel the intricate mechanisms underlying the initiation and maintenance of a reentry. In this computational study, we analyze the probability of reentry during different stages of the acute phase of ischemia. We also aimed at the understanding of the role of its main components: hypoxia, hyperkalemia, and acidosis analyzing the intricate ionic mechanisms responsible for reentry generation. We simulated the electrical activity of a ventricular tissue affected by regional ischemia based on a modified version of the Luo-Rudy model (LRd00). The ischemic conditions were varied to simulate different stages of this pathology. After premature stimulation, we evaluated the vulnerability to reentry. We obtained an unimodal behavior for the vulnerable window as ischemia progressed, peaking at the eighth minute after the onset of ischemia where the vulnerable window yielded 58 ms. Under more severe conditions the vulnerable window decreased and became zero for minute 8.75. The present work provides insight into the mechanisms of reentry generation during ischemia, highlighting the role of acidosis and hypoxia when hyperkalemia is present.
GMarte: Grid middleware to abstract remote task execution
published in 'Concurrency and Computation: Practice & Experience', 2006
Grid computing technologies are now being largely deployed with the widespread adoption of the Globus Toolkit as the industrial standard Grid middleware. However, its inherent steep learning curve discourages the use of these technologies for non-experts. Therefore, to increase the use of Grid computing, it is important to have high-level tools that simplify the process of remote task execution. In this paper we introduce a middleware, developed on top of the Java Commodity Grid, which offers an object-oriented, user-friendly application programming interface, from the Java language, which eases remote task execution for computationally intensive applications
Combining Neural Networks and Genetic Algorithms to Predict and Reduce Diesel Engine Emissions
published in 'IEEE Transactions on Evolutionary Computation', 2007
Diesel engines are fuel efficient which benefits the reduction of CO2 released to the atmosphere compared with gasoline engines, but still result in negative environmental impact related to their emissions. As new degrees of freedom are created, due to advances in technology, the complicated processes of emission formation are difficult to assess. This paper studies the feasibility of using artificial neural networks (ANNs) in combination with genetic algorithms (GAs) to optimize the diesel engine settings. The objective of the optimization was to find settings that complied with the increasingly stringent emission regulations while also maintaining, or even reducing the fuel consumption. A large database of stationary engine tests, covering a wide range of experimental conditions was used for this analysis. The ANNs were used as a simulation tool, receiving as inputs the engine operating parameters, and producing as outputs the resulting emission levels and fuel consumption. The ANN outputs were then used to evaluate the objective function of the optimization process, which was performed with a GA approach. The combination of ANN and GA for the optimization of two different engine operating conditions was analyzed and important reductions in emissions and fuel consumption were reached, while also keeping the computational times low