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An Efficient Task Scheduling of Multiprocessor using Genetic Algorithm based on Task Height

초록

영어

Static task scheduling in multiprocessor frameworks is one of the well-defined NP Hard Problem. Due to optimal utilization of processors and in addition investing less time, the Scheduling of tasks in multiprocessor frameworks is of extraordinary significance. To Solve NP Hard Problem using traditional strategies takes reasonable measures of time. Over the time, various heuristic procedures were presented for comprehending it. Therefore, heuristic methods such as Genetic Algorithms are appropriate methods for task scheduling in multiprocessor system. In this paper, a new GA for static task scheduling in multiprocessor systems has been presented whose priority of tasks’ execution is based on the height of task in graph and other mentioned parameters and then scheduling is performed. This proposed method is simulated and then compared with Basic Genetic algorithm.

목차

Abstract
 1. Introduction
 2. Review of Genetic Algorithm Literature for Multiprocessors Task Scheduling
 3. Proposed Algorithm
  3.1. Encoding Chromosomes
  3.2. Generation of Population
  3.3. Adjust Height
  3.4. Fitness Function
  3.5. Reproduction
 4. Scheduling Algorithm
 4. Implementation and Experimental Results of Proposed Algorithm
  4.1 Implementation Environment
  4.2. Results and Discussion
 5. Conclusion
 References

저자정보

  • Ashish Sharma Department of Computer Science and Engineering Guru Nanak Dev University, Regional Campus, Jalandhar, India
  • Mandeep Kaur Department of Computer Science and Engineering Guru Nanak Dev University, Regional Campus, Jalandhar, India

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