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 …

Nowadays, more and more computer-based scientific experiments need to handle massive
amounts of data. Their data processing consists of multiple computational steps and …

Cloud computing is rapidly growing as an alternative to conventional computing. However, it
is based on models like cluster computing, distributed computing, utility computing and grid …

Many-task computing aims to bridge the gap between two computing paradigms, high
throughput computing and high performance computing. Many task computing differs from …

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s.
Online analysis methods are needed to enable the collection of only interesting subsets of …

The scheduling of a many-task workflow in a distributed computing platform is a well known
NP-hard problem. The problem is even more complex and challenging when the virtualized …

Geographical Information Systems or Geospatial Information Systems (GIS) is a collection of
tools that captures, stores, analyzes, manages, and presents data that are linked to …

The industry is nowadays confronted with large-scale monolithic and inflexible object-
oriented software. Because of their high business value, these legacy systems must be re …

We have extended the Falkon lightweight task execution framework to make loosely coupled
programming on petascale systems a practical and useful programming model. This work …

Workflow engines are commonly used to orchestrate large-scale scientific computations
such as, but not limited to weather, climate, natural disasters, food safety, and territorial …