Solving Task Scheduling Problem in Multi-processors with Genetic Algorithm and Task Duplication

Parallel arithmetic are methods for processing in distributed and multi processors environments. The purpose of parallel arithmetic is to accelerate executing a group of tasks,dividing applications to sub-tasks and executing them at the same time. In this paper, we propose a genetic based technique forsolving task scheduling in multi-processor systems. In some cases, the cost to execute a task becomes more than retrieving theinformation of task from one processor to another. To address this property we use a thought-out task duplication policy to decrease the overall computation time. Because each task canduplicate more than once, the length of chromosomes in the proposed method will change dynamically. Furthermore, asimple and efficient strategy is proposed for task priority assignment. Experimental results confirm the effectiveness of ourproposed method in seven benchmark problems in comparison with previous works.

کلیدواژه ها:

Multi-processor Task Scheduling ، Genetic Algorithm ، Task Duplication ، Parallel Processing