Fuzzy MAP approach for accruing velocity of big data

Authors

  • Alzyadat WJ Department of Software Engineering, Faculty of Information Technology Isra University, Amman, Jordan
  • AlHroob A Department of Software Engineering, Faculty of Information Technology Isra University, Amman, Jordan
  • Almukahel IH Department of Software Engineering, Faculty of Information Technology Isra University, Amman, Jordan
  • Atan R Department of Software Engineering and Information Systems, Faculty of Computer Science and Information Technology, University Putra Malaysia, Selangor, Malaysia

Keywords:

Big Data, Velocity, Fuzzy Logic Controller, MapReduce

Abstract

Each characteristic of Big Data (volume, velocity, variety, and value) illustrate a unique challenge to Big Data Analytics. The performance of Big Data from velocity characteristic, in particular, appear challenging of time complexity for reduced processing in dissimilar frameworks ranging from batch-oriented, MapReduce-based to real-time and stream-processing frameworks such as Spark and Storm. We proposed an approach to use a Fuzzy logic controller combined with MapReduce frameworks to handle the vehicle analysis by comparing the driving data from the new outcome vehicle trajectory. The proposed approach is evaluated via amount of raw data from the original resource with dataset after the processing of the approach using ANOVA to estimate and analyze the differences. The difference before and after using approach is a positive impact in several stages of the volume of datasets, variances, and P-value that mean significantly and contribute for two aspects i.e. accuracy and performance.

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Published

2024-02-26

How to Cite

Alzyadat, W. J., AlHroob, A., Almukahel, I. H., & Atan, R. (2024). Fuzzy MAP approach for accruing velocity of big data. COMPUSOFT: An International Journal of Advanced Computer Technology, 8(04), 3112–3116. Retrieved from https://ijact.in/index.php/j/article/view/489

Issue

Section

Original Research Article

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