Design and Performance Evaluation of Resource-Management Framework for End-to-End Adaptation of Distributed Real-time Embedded Systems

Standards-based quality of service (QoS)-enabled component middleware is increasingly being used as a platform for developing distributed real-time embedded (DRE) systems. Although QoS-enabled component middleware offers many desirable features, until recently it lacked the ability to monitor utilization of system resources, efficiently allocate resources to application components, and ensure application QoS requirements are met. Moreover, it has also lacked the ability to handle fluctuations in availability of resource resources and application workload. This paper presents two contributions to research on adaptive resource management for component-based DRE systems. First, we describe the structure and functionality of the Resource Allocation and Control Engine (RACE), which is an opensource adaptive resource management framework built atop standards-based QoS-enabled component middleware. Second, we demonstrate and evaluate the effectiveness of RACE in the context of a representative DRE system: NASA’s Magnetospheric Multi-scale Mission system. Our empirical results demonstrate that when adaptive resource management algorithms for DRE systems are implemented using RACE, they yield in a predictable and high performance system, even in the face of changing operational conditions, workloads, and resource availability.