There is an increasing demand to introduce adaptive capabilities in distributed real-time and embedded (DRE) systems that execute in open environments where system operational conditions, input workload, and resource availability cannot be characterized accurately a priori. To meet these needs, this paper presents the Hierarchical Distributed Resource-management Architecture (HiDRA), which provides adaptive resource management using control-theoretic techniques that adapt to workload fluctuations and resource availability. In contrast to adaptive control techniques that manage only one type of system resource, HiDRA features a hierarchical control scheme that manages both bandwidth and processor utilization simultaneously. This paper presents three contributions to research in adaptive resource management for DRE systems. First, we describe the structure and functionality of HiDRA. Second, we present an analytical model of HiDRA that formalizes its control theoretic behavior and present analytical performance guarantees. Third, we evaluate the performance of HiDRA via experiments on a representative DRE system that performs distributed target tracking in real-time. Our analytical and empirical results indicate that HiDRA yields predictable, stable, and high system performance, even in the face of changing workload.