This paper gives an overview of two middleware systems that have been developed over the
last 6 years to address the challenges involved in developing parallel and distributed …

Summary form only given. As scientific simulations are generating large amounts of data,
analyzing this data to gain insights into scientific phenomenon is increasingly becoming a …

For a grid middleware to perform resource allocation, prediction models are needed, which
can determine how long an application will take for completion on a particular platform or …

Analysis of large geographically distributed scientific datasets, also referred to as distributed
data-intensive science, has emerged as an important area in recent years. An application …

In this paper, we consider the problem of developing service-oriented implementations of
data-intensive applications that process data on remote servers. While the existing grid and …

We have been developing a middleware which enables development, support, and
deployment of services that can transparently access and process data from remote servers …

We have been developing a middleware which en-ables development, support, and
deployment of services that can transparently access and process data from remote servers …

Initial efforts on applying mining techniques on scientific simulation datasets has
demonstrated that 1) the algorithms and the algorithmic parameters that give desirable …

As scientific simulations are generating large amounts of data, analyzing this data to gain
insights into scientific phenomena is increasingly becoming a challenge. With the …

For a grid middleware to perform resource allocation, prediction models are needed, which
can determine how long an application will take for completion on a particular platform or …