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Multiple Tasks Allocation in Arbitrarily Connected Distributed Computing Systems Using A* Algorithm and Genetic Algorithm

  • Biplab Kumer Sarker
  • Anil Kumar Tripathi
  • Deo Prakash Vidyarthi
  • Laurence Tianruo Yang
  • Kuniaki Uehara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4331)

Abstract

A number of algorithms is proposed for allocation of tasks in a DCS. Most of them did not consider allocation of various unrelated tasks partitioned into modules by taking into account the architectural capability of the processing nodes and the connectivity among them. This work considers allocation of disjoint multiple tasks with corresponding modules wherein multiple disjoint tasks with their modules compete for execution on an arbitrarily networked DCS. Two algorithms have been presented based on well-known A* algorithm and Genetic Algorithm techniques. The proposed algorithms consider a load balanced allocation for the purpose. The paper justifies the effectiveness of the proposed algorithms using several case studies.

Keywords

Task Allocation Task Graph Processing Node Multiple Task Distribute Computing System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Biplab Kumer Sarker
    • 1
  • Anil Kumar Tripathi
    • 2
  • Deo Prakash Vidyarthi
    • 3
  • Laurence Tianruo Yang
    • 4
  • Kuniaki Uehara
    • 5
  1. 1.Faculty of Computer ScienceUniversity of New BrunswickFrederictonCanada
  2. 2.Institute of TechnologyBanaras Hindu UniversityVaranasiIndia
  3. 3.Jawaharal Nehru UniversityNew DelhiIndia
  4. 4.Department of Computer ScienceSt. Francis Xavier UniversityCanada
  5. 5.Graduate School of Science and TechnologyKobe UniversityJapan

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