In this paper, we consider parallel tasks scheduling problems for hierarchical decentralized systems that consist of homogeneous computational resources such as clusters, PCs and supercomputers, and geographically dispersed. We concentrate on two-level hierarchy scheduling: at the first level, broker allocates computational tasks to the resource. At the second level, each resource schedules the tasks assigned to it using heuristics based, for instance, on strip-packing algorithms. The allocation strategies and efficiency of proposed hierarchical scheduling algorithms are discussed.