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DOI: 10.14569/IJACSA.2019.0100373
PDF

Efficient Load Balancing in Cloud Computing using Multi-Layered Mamdani Fuzzy Inference Expert System

Author 1: Naila Samar Naz
Author 2: Sagheer Abbas
Author 3: Muhammad Adnan Khan
Author 4: Benish Abid
Author 5: Nadeem Tariq
Author 6: Muhammad Farrukh Khan

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 3, 2019.

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Abstract: In this article, a new Multi-Layered mamdani fuzzy inference system (ML-MFIS) is propound for the Assessment of Efficient Load Balancing (ELB). The proposed ELB-ML-MFIS expert System can categorise the level of ELB in Cloud computing into Excellent, Normal or Low. ELB-ML-MFIS Expert System for ELB in cloud computing is developed under the guidelines from the Microsoft Organization and Pakistan’s Punjab Information Technology Board (PITB) Standard. ELB-ML-MFIS Expert System uses input Cloud Computing parameters such as Data-Center, Virtual-Machine, and Inter –of-Things (IOT) for different layers. This article also analyses the intensities of the Parametres and the results achieved by using the Proposed ELB-ML-MFIS Expert System. All these parameters and results are discussed with the experts of Pakistan’s Punjab Information Technology Board (PITB), Lahore. The accuracy of the proposed ELB-ML-MFIS Expert System is more accurate as compared to other approaches used for it.

Keywords: PITB; IOT; Virtual-Machine; Data-center; ML, ELB; MFIS

Naila Samar Naz, Sagheer Abbas, Muhammad Adnan Khan, Benish Abid, Nadeem Tariq and Muhammad Farrukh Khan, “Efficient Load Balancing in Cloud Computing using Multi-Layered Mamdani Fuzzy Inference Expert System” International Journal of Advanced Computer Science and Applications(IJACSA), 10(3), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100373

@article{Naz2019,
title = {Efficient Load Balancing in Cloud Computing using Multi-Layered Mamdani Fuzzy Inference Expert System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100373},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100373},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {3},
author = {Naila Samar Naz and Sagheer Abbas and Muhammad Adnan Khan and Benish Abid and Nadeem Tariq and Muhammad Farrukh Khan}
}



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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