I7 Logo
Chair for Foundations of Software Reliability and Theoretical Computer Science
Informatik Logo TUM Logo
Publications - Mapping Data-Flow Dependencies onto Distributed Embedded Systems

Reference:

Stefan Kugele and Wolfgang Haberl. Mapping Data-Flow Dependencies onto Distributed Embedded Systems. In Hamid R. Arabnia and Hassan Reza, editors, Proceedings of the 2008 International Conference on Software Engineering Research & Practice, SERP 2008, volume 1, pages 272–278. CSREA Press, July 2008.

Abstract:

Model-driven development (MDD) is an emerging paradigm and has become state-of-the-art for embedded systems software design. In the overall design process, several steps have to be taken in order to get from a high-level system design to the deployed binaries on the target platform: starting from model design, software partitioning and code generation reaching down to task and bus scheduling. In this paper we focus on the later steps in the overall developing process and present a way to deploy clusters, which are tasks from an operational point of view, specified using the Component Language (COLA). In this context, we introduce the notion of a Cluster Dependency Graph (CDG) which forms the basis for scheduling, address generation and estimation of memory requirements for the used middleware. Moreover the CDG provides clues about possibly parallelizable tasks. A case-study, namely an adaptive cruise control system (ACC), taken from the automotive domain serves as example throughout this paper to demonstrate our new approach.

Suggested BibTeX entry:

@inproceedings{kugele:haberl:serp08,
    author = {Stefan Kugele and Wolfgang Haberl},
    booktitle = {Proceedings of the 2008 International Conference on Software Engineering Research & Practice, SERP 2008},
    editor = {Hamid R. Arabnia and Hassan Reza},
    month = {July},
    pages = {272--278},
    publisher = {CSREA Press},
    title = {{Mapping Data-Flow Dependencies onto Distributed Embedded Systems}},
    volume = {1},
    year = {2008}
}

PDF (158 kB)