An Adaptive And Parameterized Job Grouping Algorithm For Scheduling Grid Jobs

An unorganized deployment of grid applications with a large amount of fine-grain jobs would let the communication overhead dominate the overall processing time, resulting in a low computation-communication ratio. Grid's dynamic nature complicates the planning of the job scheduling activity for minimizing the application processing time. This paper presents a grid job scheduling algorithm, based on a parameterized job grouping strategy, which is adaptive to the runtime grid environment. Jobs are grouped based on the job processing requirements, resource policies, network conditions and user's QoS requirements. Simulations using the GridSim toolkit reveal that the algorithm reduces the overall application processing time significantly.