Marta Mattoso

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The recent evolution of internet technologies, mainly guided by the Extensible Markup Language (XML) and its related technologies, are extending the role of the World Wide Web from information interaction to service interaction. This next wave of the internet era is being driven by a concept named Web services. The Web services technology provides the(More)
Most of the large-scale scientific experiments modeled as scientific workflows produce a large amount of data and require workflow parallelism to reduce workflow execution time. Some of the existing Scientific Workflow Management Systems (SWfMS) explore parallelism techniques - such as parameter sweep and data fragmentation. In those systems, several(More)
Scientific Workflow Management Systems (SWfMS) have been helping scientists to prototype and execute in silico experiments. They can systematically collect provenance information for the derived data products to be later queried. Despite the efforts on building a standard Open Provenance Model (OPM), provenance is tightly coupled to SWfMS. Thus scientific(More)
Component Based Developed aims at constructing software through the inter-relationship between pre-existing components. However, these components should be bound to a specific application domain in order to be effectively reused. Reusable domain components and Their related documentation are usually stored in a great variety of data sources. Thus, a(More)
Large-scale scientific experiments based on computer simulations are typically modeled as scientific workflows, which eases the chaining of different programs. These scientific workflows are defined, executed, and monitored by scientific workflowmanagement systems (SWfMS). As these experiments manage large amounts of data, it becomes critical to execute(More)
In the last years, scientific workflows have emerged as a fundamental abstraction for structuring and executing scientific experiments in computational environments. Scientific workflows are becoming increasingly complex and more demanding in terms of computational resources, thus requiring the usage of parallel techniques and high performance computing(More)
The design of distributed databases involves making decisions on the fragmentation and placement of data and programs across the sites of a computer network. The first phase of the distribution design in a top-down approach is the fragmentation phase, which clusters in fragments the information accessed simultaneously by applications. Most distribution(More)
In many scientific workflows, particularly those that operate on spatially oriented data, jobs that process adjacent regions of space often reference large numbers of files in common. Such workflows, when processed using workflow planning algorithms that are unaware of the application's file reference pattern, result in a huge number of redundant file(More)
Nowadays, more and more computer-based scientific experiments need to handle massive amounts of data. Their data processing consists of multiple computational steps and dependencies within them. A data-intensive scientific workflow is useful for modeling such process. Since the sequential execution of data-intensive scientific workflows may take much time,(More)
OLAP query processing is critical for enterprise grids. Capitalizing on our experience with the ParGRES database cluster, we propose a middleware solution, GParGRES, which exploits database replication and interand intra-query parallelism to efficiently support OLAP queries in a grid. GParGRES is designed as a wrapper that enables the use of ParGRES in PC(More)