Both parallel and distributed network environment systems play a vital role in the improvement of high performance computing. The primary concern when analyzing these systems is multiprocessor task scheduling. This paper addresses the problem of efficient multiprocessor task scheduling. A multiprocessor task scheduling problem is represented as directed acyclic task graph (DAG), for execution on multiprocessors with communication costs. In this paper we have investigated the effectiveness of a proposed paradigm based on genetic algorithms (GAs). GAs is a class of robust stochastic search algorithms for various combinatorial optimization problems. We have designed a GA based encoding mechanism that uses multi-chromosome encoding scheme. The implementation of the technique is simple. The performance of the designed algorithm has been tested on a variety of multiprocessor systems both heterogeneous as well as homogeneous. © 2012 Springer India Pvt. Ltd.
CITATION STYLE
Panwar, P., Lal, A. K., & Singh, J. (2012). A genetic algorithm based technique for efficient scheduling of tasks on multiprocessor system. In Advances in Intelligent and Soft Computing (Vol. 131 AISC, pp. 911–919). https://doi.org/10.1007/978-81-322-0491-6_84
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