Abstract Computational Grids consist of a multitude of geographically distributed resources. The co-allocation of several of those resources allows for the execution of highly computing-intensive and dataintensive jobs. In order to obtain quality schedules (in terms of job response time and resource utilization), different factors such as resource load (computational resource load and bandwidth usage) and data location need to be taken into account. In addition, because of the size of realistic Grids, relevant parameters w.r.t. schedule quality can often only be obtained through simulations. In this paper, we detail how a discrete-event simulator was extended to support the simulation of scheduling both cpu- and data-intensive jobs on a Grid using network-aware scheduling algorithms. These jobs can either pre-stage data, or access data remotely while executing. We examine the case in which resource-toresource data connections with guaranteed bandwidth can be set up, both when capacitat...