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Cloud computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for cloud computing and there seems to be no consensus on what a cloud is. On the other hand, cloud computing is not a completely new concept; it has intricate connection to the relatively new but thirteen-year established grid computing paradigm,(More)
In this paper, we propose a new clustering algorithm called <i>Fast Genetic K-means Algorithm (FGKA)</i>. FGKA is inspired by the Genetic K-means Algorithm (GKA) proposed by Krishna and Murty in 1999 but features several improvements over GKA. Our experiments indicate that, while K-means algorithm might converge to a local optimum, both FGKA and GKA always(More)
Scientific workflows have recently emerged as a new paradigm for scientists to formalize and structure complex and distributed scientific processes to enable and accelerate many scientific discoveries. In contrast to business workflows, which are typically control flow oriented, scientific workflows tend to be dataflow oriented, introducing a new set of(More)
Most existing workflow scheduling algorithms only consider a computing environment in which the number of compute resources is bounded. Compute resources in such an environment usually cannot be provisioned or released on demand of the size of a workflow, and these resources are not released to the environment until an execution of the workflow completes.(More)
Storing and querying XML documents using a RDBMS is a challenging problem since one needs to resolve the conflict between the hierarchical, ordered nature of the XML data model and the flat, unordered nature of the relational data model. This conflict can be resolved by the following XML-to-Relational mappings: schema mapping, data mapping and query(More)
Article history: Received 12 October 2008 Received in revised form 8 March 2010 Accepted 11 March 2010 Available online 23 March 2010 Provenance metadata has become increasingly important to support scientific discovery reproducibility, result interpretation, and problem diagnosis in scientific workflow environments. The provenance management problem(More)
In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are(More)
Scientific workflows have recently emerged as a new paradigm for scientists to formalize and structure complex and distributed scientific processes to enable and accelerate many scientific discoveries. In contrast to business workflows, which are typically control flow oriented, scientific workflows tend to be dataflow oriented, introducing a new set of(More)
Data replication has been well adopted in data intensive scientific applications to reduce data file transfer time and bandwidth consumption. However, the problem of data replication in Data Grids, an enabling technology for data intensive applications, has proven to be NP-hard and even non approximable, making this problem difficult to solve. Meanwhile,(More)