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...
One of the first motivations of using grids comes from applications managing large data sets in field such as high energy physics or life sciences. To improve the global throughput...
We present an algorithm for scheduling distributed data intensive Bag-of-Task applications on Data Grids that have costs associated with requesting, transferring and processing da...
Distributed computations, dealing with large amounts of data, are scheduled in Grid clusters today using either a task-centric mechanism, or a worker-centric mechanism. Because of ...
Existing data grid scheduling systems handle huge data I/O via replica location services coupled with simple staging, decoupled from scheduling of computing tasks. However, when th...