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.