A hierarchical approach to improve job scheduling and data replication in data grid

In dynamic environment of data grid effective job scheduling methods consider location of required data in dispatching jobs to resources. Also, job scheduling methods are combined with data replication mechanisms to reduce remote data access as well as save network bandwidth. In this paper, we combine job scheduling method and dynamic data replication to reduce data access delay and job execution time. Also, we expand our work by applying bloom filter in job scheduling decision. In data grid, appropriate mechanisms for recording, deleting and inquiring information about data files are required for implementing proper job scheduling method. Therefore, we apply counting bloom filter for recording/deleting and inquiring information about data files in Replica Catalogue (RC). Result of simulation indicates that proposed job scheduling and data replication methods reduce job execution time, also using bloom filter saves network bandwidth and reduces time of gathering information for selecting appropriate resources in job scheduling.