Effective resource management for distributed real-time embedded (DRE) systems is hard due to their unique characteristics, including (1) constraints in multiple resources and (2) highly fluctuating resource availability and input workload. DRE systems can benefit from a middleware framework that enables adaptive resource management algorithms to ensure application QoS requirements are met. This paper identifies key challenges in designing and extending resource allocation algorithms for DRE systems. We present an empirical study of bin-packing algorithms enhanced to meet these challenges. Our analysis identifies input application patterns that help generate appropriate heuristics for using these algorithms effectively in DRE systems.