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,...
Scheduling parallel jobs has been an active investigation area. The scheduler has to deal with heterogeneous workloads and try to obtain throughputs and response times such that en...
For data analysis or simulations (e.g. in particle physics) single users submit hundreds or thousands of jobs to the Grid. This puts a new burden on the users side - keeping an ov...
Buffered coscheduling is a scheduling methodology for time-sharing communicating processes in parallel and distributed systems. The methodology has two primary features: communica...
Knowledge about the workload is an important aspect for scheduling of resources as parallel computers or Grid components. As the scheduling quality highly depends on the character...