Predictable deployment and configuration (D&C) of components in response to dynamic environmental changes or system mode changes is essential for ensuring open distributed real-time and embedded (DRE) system real-time QoS. This paper provides three contributions to research on the predictability of D&C for component-based open DRE systems. First, we describe how the dependency relationships among different components and their criticality levels can cause deployment order inversion of tasks, which impedes deployment predictability. Second, we describe how to minimize D&C latency of mission-critical tasks with a multi-graph dependency tracing and graph recomposition algorithm called CaDAnCE. Third, we empirically evaluate the effectiveness of CaDAnCE on a representative open DRE system case study based on NASA Earth Science Enterprise's Magnetospheric Multi-Scale (MMS) mission system. Our results show that CaDAnCE avoids deployment order inversion while incurring negligible (<1%) performance overhead, thereby significantly improving D&C predictability.

As quality of service (QoS)-enabled component middleware technologies gain widespread acceptance to build distributed real-time and embedded (DRE) systems, it becomes necessary for these technologies to support real-time publish/subscribe services, which is a key requirement of a large class of DRE systems. To date there have been very limited systematic studies evaluating different approaches to integrating real-time publish/subscribe services in QoS-enabled component middleware. This paper makes two contributions in addressing these key research questions. First, we evaluate the pros and cons of three different design alternatives for integrating publish/subscribe services within QoS-enabled component middleware. Second, we empirically evaluate the performance of our container-based design and compare it with mature object-oriented real-time publish/subscribe implementations. Our studies reveal that both the performance and scalability of our design and implementation are comparable to its object-oriented counterpart, which provides a key guidance to the suitability of component technologies for DRE systems.

Component-based software engineering (CBSE) is increasingly being adopted for large-scale software systems, particularly for enterprise distributed real-time and embedded (DRE) systems. One of the most challenging-and often most neglected-problems in CBSE for enterprise DRE systems is the system (re)deployment and (re)configuration (D&C) process, where the increasing heterogeneity and versatility of application domains requires supports for an unprecedented level of configurability and adaptability. Existing D&C technologies suffer from two major problems: (1) insufficient module-level reusability and ability to evolve in the face of functionality evolution and diversification due to the interaction of too many orthogonal concerns imposed by a wide range of application requirements and (2) significant inherent and accidental complexities stemming from inadequate design tools. To address these problems, my research focuses on improving both computing performance and human productivity associated with the D&C of component-based enterprise DRE systems. To improve computing performance, my research has systematically identified bottlenecks with conventional D&C approaches and provides an aspect-oriented approach to decouple "extrinsic" orthogonal D&C concerns from "intrinsic" core D&C infrastructure, thereby enabling different crosscutting D&C concerns to be weaved independently to create a light-weight, highly optimized and extensible D&C infrastructure. To improve human performance, my research provides model-driven tools and analysis techniques to alleviate key inherent and accidental complexities in the D&C process.

Model-driven development (MDD) is gaining importance as an approach to resolving lifecycle challenges of large-scale distributed real-time and embedded (DRE) systems (e.g., avionics mission computing). DRE systems are characterized by their stringent requirements for quality of service (QoS), such as predictable end-to-end latencies, timeliness and scalability. Delivering the QoS needs of DRE systems entails the need to configure correctly, fine tune and provision the infrastructure used to host the DRE systems, which crosscuts different layers of middleware, operating systems and networks. Addressing these tangled deployment and configuration concerns of DRE systems requires integrating the principles of Aspect-Oriented Software Development (AOSD) with MDD. This demo showcases a set of software tools that resolve both the inherently and accidental complexities arising due to the configuration and deployment crosscutting concerns of component middleware-based DRE systems.

Developing real-time software for large-scale distributed real-time and embedded (DRE) systems is hard due to variabilities that arise from (I) integration with various subsystems based on different programming languages and hardware, OS, middleware platforms, (2) fine tuning the system to satisfy a range of customer requirements, such as various quality-of-service (QoS) properties, and (3) changing functional and QoS properties of the system based on available system resources. This paper describes our experience applying model-driven development (MDD) tools and QoS-enabled component middleware technologies to address domain- and middleware-specific variability challenges in an inventory tracking system, which manages the storage and flow of items in warehouses. Our results show that (I) coherent integration of MDD tools and component middleware can provide a productive software process for developing DRE systems by modularizing and composing variability concerns and (2) significant challenges remain that must be overcome to apply these technologies to a broader range of DRE systems.