AbstractIn large‐scale data‐intensive applications data play a pivotal role in the execution of these applications, and data transfer is a primary cause of job execution delay. In environments such as the data grids where execution of jobs that require large amounts of data is undertaken, a smart collaborative environment between the scheduling and data management services to achieve a synergistic effect on the performance of the grid becomes essential. This paper presents an intelligent data grid framework where job scheduling and data and replica management are coupled to provide an integrated environment for efficient access to data and job scheduling. The data management service predicts and estimates the appropriate locations of replica and proactively replicates the data sets in these locations while the intelligent tabu‐search‐based scheduler incorporating information about the data sets dispatches the jobs to the sites expected to facilitate minimum job execution time and better overall system utilization. Evaluation of the framework shows significant improvement in the performance of the grid and job execution time. Copyright © 2008 John Wiley & Sons, Ltd.