Scheduling Multiprocessor Tasks with Correlated Failures Using Population Learning Algorithm
The paper considers a problem of scheduling multiprocessor tasks with correlated failures to maximize schedule reliability under time constraints. Since the problem is NP-hard the approximation algorithms based on a population learning algorithm are proposed.
KeywordsLocal Search Tabu Search Multiple Processor Redundant Variant Variant Software
Unable to display preview. Download preview PDF.
- J. Błażewicz, K.H. Ecker, E. Pesch, G. Schmidt, J. Węglarz, Scheduling Computer and Manufacturing Processes, Springer, Berlin 1996.Google Scholar
- I. Czarnowski, P. Jędrzejowicz, E. Ratajczak, Scheduling Fault-Tolerant Programs on Multiple Processors to Maximize Schedule Reliability, Lecture Notes in Computer Science 1698, Springer (1999), pp. 385–395.Google Scholar
- I. Czarnowski, W.J. Gutjahr, P. Jędrzejowicz, E. Ratajczak, A. Skakowski, I. Wierzbowska, Scheduling multiprocessor tasks in presence of the correlated failures, Procedings of the 2nd Intl. Workshop on Soft Computing Applied to Software Engineering, Rotterdam 2001, (Accepted paper).Google Scholar