With the advent of the Grid, task scheduling in heterogeneous environments becomes more and more important. Of particular interest is the fact that especially in scientific experiments a non negligible amount of data must be transferred to the processing node before a task can commence execution. Given bandwidth constraints, scheduling both computations and data transfers is required. In this paper we first develop a suitable model that captures heterogeneity in the processing nodes while imposing communication constraints. We proceed by proposing scheduling heuristics with the aim of minimizing the total makespan of a set of independent tasks. Through a series of experiments we illustrate the potential of a particular heuristic that is based on backfilling.