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Job partition and allocation using the prediction model in non-dedicated heterogeneous wireless network environments

Job partition and allocation using the prediction model in non-dedicated heterogeneous wireless network environments

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  • Author(s): T.-K. Kim 1 ; J.H. Park 2 ; S.-S. Yeo 3 ; H.S. Seo 4 ; J. Kwak 5
    • View affiliations
    • Affiliations: 1: Department of Liberal Art, Seoul Theological University, Bucheon, South Korea
      2: Department of Computer Science and Engineering, Kyungnam University, Masan, South Korea
      3: R&D Department, BTWorks Inc., Seoul, South Korea
      4: School of Internetmedia Engineering, Korea University of Technology and Education, Byungcheon, South Korea
      5: Department of Information Security Engineering, Soonchunhyang University, Asan, South Korea
  • Source: Volume 3, Issue 5, May 2009, p. 764 – 771
    DOI:  10.1049/iet-com.2008.0257 , Print ISSN 1751-8628, Online ISSN 1751-8636
© The Institution of Engineering and Technology
Published

Adapting wireless devices to communicate within grid networks empower users. This makes deployment of a wide range of applications possible within appropriate limits, including intermittent network connectivity and non-dedicated heterogeneous system capacity. The performance prediction model is used to improve the performance of the mobile grid job scheduling algorithm (MG-JSA). The proposed algorithm predicts the response time for processing the distributed application in each mobile node, although considering wireless network environments and inherent non-dedicated heterogeneous system capacity. Using this prediction model, the algorithm partitions and allocates the distributed jobs to available mobile nodes for rapid job processing. The efficiency of the MG-JSA model is demonstrated by evaluating its performance.

Inspec keywords: mobile radio; mobile computing; distributed algorithms; scheduling; grid computing

Other keywords: non dedicated heterogeneous wireless network environment; wireless device; job partition; mobile grid job scheduling algorithm; prediction model; intermittent network connectivity; distributed application processing; response time

Subjects: Mobile radio systems; Distributed systems software

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