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DOI: 10.14569/IJACSA.2019.0101254
PDF

A Mobile Agent Team Works based on Load-Balancing Middleware for Distributed Computing Systems

Author 1: Fatéma Zahra Benchara
Author 2: Mohamed Youssfi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.

  • Abstract and Keywords
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Abstract: The aim of this paper is to present a load balancing middleware for parallel and distributed systems. The great challenge is to balance the tasks between heterogeneous distributed nodes for parallel and distributed computing models based distributed systems, by the way to ensure HPC (High performance computing) of these models. Accordingly, the proposed middleware is based on mobile agent team work which implements an efficient method with two strategies: (i) Load balancing Strategy that determines the node tasks assignment based on node performance, and (ii) Rebalancing Strategy that detects the unbalanced nodes and enables tasks migration. The paper focuses on the proposed middleware and its cooperative mobile agent team work model strategies to dynamically balance the nodes, and scale up distributed computing systems. Indeed, some experimental results that highlight the performance and efficiency of the proposed middleware are presented.

Keywords: Load balancing; middleware; parallel and distributed systems; parallel and distributed computing models; high performance computing; mobile agents; distributed computing

Fatéma Zahra Benchara and Mohamed Youssfi, “A Mobile Agent Team Works based on Load-Balancing Middleware for Distributed Computing Systems” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101254

@article{Benchara2019,
title = {A Mobile Agent Team Works based on Load-Balancing Middleware for Distributed Computing Systems},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101254},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101254},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Fatéma Zahra Benchara and Mohamed Youssfi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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