In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in co...
Richard McClatchey, Ashiq Anjum, Heinz Stockinger,...
In high energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets. So...
In parallel computing environments such as HPC clusters and the Grid, data-intensive applications involve large overhead costs due to a concentration of access to the files on co...
Data streaming applications, usually composed with sequential/parallel tasks in a data pipeline form, bring new challenges to task scheduling and resource allocation in grid envir...
Advances in network technologies and the emergence of Grid computing have both increased the need and provided the infrastructure for computation and data intensive applications to...
Anastasios Gounaris, Rizos Sakellariou, Norman W. ...