Scheduling decisions in time-critical systems are very difficult, due to the vast number of systems' parameters and tasks' attributes involved in such decisions. Value-based scheduling heuristics have been found to experience a more graceful degradation under overload situations than various other heuristics. However, currently existing value-based heuristics utilize the tasks' static attributes, and therefore, they derive fixed scheduling priorities. In this paper, we propose value-based scheduling heuristics that utilize the tasks' dynamic attributes in order to enhance the overall system's performance under normal operating loads and to reduce performance degradation under overload situations.

BibTex Entry

@inproceedings{Aldarmi1999,
 author = {S. A. Aldarmi and A. Burns},
 booktitle = {The 11th Euromicro Conference on Real-Time Systems},
 category = {scheduling},
 month = {Jun},
 title = {Dynamic Value-Density For Scheduling Real-Time Systems},
 year = {1999}
}