Grids offer the potential of harnessing vast amounts of computational resources during the execution of demand- ing computations. These resources are geographically dis- tributed, owned by different organizations and are highly heterogeneous. All these create an uncertain environment in all phases of a Grid Scheduling Process (GSP). In this work, we focus on the resource discovery process dur- ing which clients of the grid discover possibly suitable re- sources available for their computation. We propose a net- work of resource representatives, which maintain the more- or-less static characteristics of available workers they rep- resent (e.g. OS, CPU type etc.). We show that clustering algorithms is a promising approach that can be used for the efficient discovery of suitable resources for a given task set.