Dynamic Tasks Scheduling Model for Performance Evaluation of a Distributed Computing System through Artificial Neural Network

  • M. P. Singh
  • P. K. Yadav
  • Harendra Kumar
  • Babita Agarwal
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 130)


As technology has quickly and relentlessly advanced in the field of computer hardware, Distributed Computing System [DCS] has become increasingly popular. Performance enhancement is one of the most important issues in distributed systems. In this paper we have proposed a dynamic task allocation model based on artificial neural network [ANN] scheduling approach to arrange the tasks to the processors. Relocating the tasks from one processor to another at certain points during the course of execution of the program that contributes to the total cost of the running program has been taken into account. Phase-wise Execution Cost [EC], Inter Task Communication Cost [ITCC], Residence Cost [RC] of each task on different processors and Relocation Cost [REC] for each task has been considered while preparing the model.


Distributed Computing System Artificial Neural Network Phase-wise Execution Inter-Tasks Communication Cost Execution Cost Relocation Cost 


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Copyright information

© Springer India Pvt. Ltd. 2012

Authors and Affiliations

  • M. P. Singh
    • 1
  • P. K. Yadav
    • 2
  • Harendra Kumar
    • 1
  • Babita Agarwal
    • 1
  1. 1.Department of Mathematics & StatisticsGurkula Kangari UniversityHardwarIndia
  2. 2.Research Planing & Business Development C.B.R.I.RoorkeeIndia

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