A novel approach for big data processing using message passing interface based on memory mapping

The analysis and processing of big data are one of the most important challenges that researchers are working on to find the best approaches to handle it with high performance, low cost and high accuracy. In this paper, a novel approach for big data processing and management was proposed that differ...

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Bibliographic Details
Published in:Journal of big data Vol. 6; no. 1; pp. 1 - 17
Main Authors: Dheyab, Saad Ahmed, Abdullah, Mohammed Najm, Abed, Buthainah Fahran
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 16.12.2019
Springer Nature B.V
SpringerOpen
Subjects:
Advanced Soft Computing Methodologies and Applications in Social Media Big Data Analytics
Big Data
Broadcasting
Communications Engineering
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Data processing
Database Management
High-performance computing
Information Storage and Retrieval
Libraries
Mapping
Mathematical Applications in Computer Science
Memory
Memory mapping
Message passing
Methodology
Networks
Parallel AES
Segmentation
Storage
Big data
Message passing
High-performance computing
Memory mapping
Parallel AES
ISSN:2196-1115, 2196-1115
Online Access:Get full text
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Summary:The analysis and processing of big data are one of the most important challenges that researchers are working on to find the best approaches to handle it with high performance, low cost and high accuracy. In this paper, a novel approach for big data processing and management was proposed that differed from the existing ones; the proposed method employs not only the memory space to reads and handle big data, it also uses space of memory-mapped extended from memory storage. From a methodological viewpoint, the novelty of this paper is the segmentation stage of big data using memory mapping and broadcasting all segments to a number of processors using a parallel message passing interface. From an application viewpoint, the paper presents a high-performance approach based on a homogenous network which works parallelly to encrypt-decrypt big data using AES algorithm. This approach can be done on Windows Operating System using .NET libraries.
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ISSN:2196-1115
2196-1115
DOI:10.1186/s40537-019-0275-3