Title :
Model-Driven Development and Adaptation of Autonomous Control Applications
Author :
Parzyjegla, Helge ; Jaeger, Michael A. ; Muhl, G. ; Weis, Torben
Author_Institution :
Berlin Univ. of Technol., Berlin
Abstract :
Our vision is driven by rapid progress in hardware development, such as miniaturizing computing devices. On the software side, however, application development for such a setting is challenging for several reasons. One is the heterogeneity of devices and networking technologies, which vastly increases application development complexity. Other reasons include frequent reconfigurations and communication faults (such as network partitioning) that have to be handled appropriately. These reasons present problems for software developers - they can´t predetermine configurations or anticipate all of the potential runtime faults that might occur. Furthermore, users might not be willing or able to handle complex configuration or communication issues - they want to install their devices and use applications. Thus, devices and applications must be able to work as autonomously as possible, with little to no manual user intervention. Specifically, applications must be able to adapt at runtime to a changing environment and recover from faults.Here, we elaborate on ideas we presented in a previous paper2 and discuss in more detail a model- driven approach to developing and adapting autonomous control applications. In contrast to conventional approaches, we use the application model not only for design and deployment but also for dynamically adapting the application at runtime. This is in line with research that emphasizes the importance of exploiting the latent knowledge contained in models at runtime.3 Our goal is to empower application developers to create self-organizing and robust actuator and sensor network (AS-Net) applications with minimal expert knowledge. Our work is part of the Model-Driven Development of Self-Organizing Control Applications project (www.kbs.tu-berlin.de/modoc).
Keywords :
control engineering computing; distributed control; robust control; self-adjusting systems; autonomous control applications; model-driven development; robust actuator; self-organizing actuator; sensor network; Actuators; Adaptation model; Application software; Art; Computer vision; Control systems; Hardware; Middleware; Monitoring; Runtime environment; automatic programming; distributed applications; pervasive computing; ubiquitous computing;
Journal_Title :
Distributed Systems Online, IEEE
DOI :
10.1109/MDSO.2008.32