A Parametrized Branch-and-Bound Strategy for Scheduling Precedence-Constrained Tasks on a Multiprocessor System
Paper i proceeding, 1997

In this paper we experimentally evaluate the performance of a parametrized branch-and-bound (B&B) algorithm for scheduling real-time tasks on a multiprocessor system. The objective of the B&B algorithm is to minimize the maximum task lateness in the system. We show that a last-in-first-out (LIFO) vertex selection rule clearly outperforms the commonly used least-lower-bound (LLB) rule for the scheduling problem. We also present a new adaptive lower-bound cost function that greatly improves the performance of the B&B algorithm when parallelism in the application cannot be fully exploited on the multiprocessor architecture. Finally, we evaluate a set of heuristic strategies, one of which generates near-optimal results with performance guarantees and another of which generates approximate results without performance guarantees.


Jan Jonsson

Institutionen för datorteknik

Kang G. Shin

Proceedings of the 26th International Conference on Parallel Processing, Bloomingdale, Illinois, August 11–15, 1997




Datavetenskap (datalogi)


Informations- och kommunikationsteknik

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