Paper Info
Title
Dynamic Mapping and Ordering Tasks of Embedded Real-Time Systems on Multiprocessor Platforms
Abstract
Tradeoff exploration can be found in several different areas of embedded system design. One example is task scheduling, where different task mapping and ordering choices for a target platform will lead to different performance/cost tradeoffs, which can be represented in a so-called Pareto curve. Though many scheduling algorithms have been suggested, on-line or off-line, few have been really implemented on a real platform, especially on. an embedded multi-processor one. We have implemented a middleware layer to handle that problem and we have integrated a hierarchical task scheduler into it. It is compatible with most current RTOS implementations as long as they have a well defined API for task activation and synchronization. A simple DCT example demonstrates that the extra overhead is acceptable low. With a real-life test case from H.263, we demonstrate how big an impact our approach can cause. The deadline miss rate is dramatically reduced since we map and order the tasks at run-time. When voltage scaling is considered, we can save 10% more energy compared to the state-of-the-art solution. Moreover, this integration enables a novel design methodology flow, which allows further design space exploration and optimization at run time.
Year
DOI
Venue
2004
10.1007/978-3-540-30113-4_13
LECTURE NOTES IN COMPUTER SCIENCE
Keywords
Field
DocType
scheduling algorithm,design methodology,middleware
Middleware,Scheduling (computing),Computer science,Real-time computing,Distributed computing,Synchronization,Parallel computing,Compiler,Real-time operating system,Multiprocessing,Earliest deadline first scheduling,Design space exploration,Embedded system
Conference
Volume
ISSN
Citations 
3199
0302-9743
8
PageRank 
References 
Authors
0.55
15
2
Name
Order
Citations
PageRank
Peng Yang119213.90
Francky Catthoor23932423.30