In this paper a semi-online algorithm for scheduling multiprocessor tasks with partial information is proposed. We consider the case in which it is possible to exploit probabilistic information and use this information to obtain better solutions in comparison with standard non clairvoyant on-line algorithms. A wide computational analysis shows the effectiveness of our algorithm. Moreover, we also consider a test framework with a continuous generation of tasks in order to study the behavior of the proposed approach in real applications, which confirms the efficiency of our approach. © 2006 Elsevier Ltd. All rights reserved.
Dell'Olmo, P., Iovanella, A., Lulli, G., Scoppola, B. (2008). Exploiting incomplete information to manage multiprocessor tasks with variable arrival rates. COMPUTERS & OPERATIONS RESEARCH, 35(5), 1589-1600 [10.1016/j.cor.2006.09.005].
Exploiting incomplete information to manage multiprocessor tasks with variable arrival rates
DELL'OLMO, PAOLO;IOVANELLA, ANTONIO;SCOPPOLA, BENEDETTO
2008-05-01
Abstract
In this paper a semi-online algorithm for scheduling multiprocessor tasks with partial information is proposed. We consider the case in which it is possible to exploit probabilistic information and use this information to obtain better solutions in comparison with standard non clairvoyant on-line algorithms. A wide computational analysis shows the effectiveness of our algorithm. Moreover, we also consider a test framework with a continuous generation of tasks in order to study the behavior of the proposed approach in real applications, which confirms the efficiency of our approach. © 2006 Elsevier Ltd. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.