Optimized Big Data Handling with Cloud-Based Parallel Divide and Conquer Techniques (A Review)

The explosive growth of data across industries has challenged traditional data processing systems, necessitating scalable, efficient, and distributed solutions. This review explores the integration of the divide and conquer paradigm with parallel computing and cloud technologies to address Big Data handling. By examining current techniques, frameworks, and challenges, the article offers a comprehensive overview of how cloud-based parallel divide and conquer strategies optimize Big Data processing in terms of performance, scalability, and cost-efficiency.

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Publication Details

Journal
Oriental journal of computer science and technology
Published
2025-08-30
DOI
https://doi.org/10.13005/ojcst17.01.04
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimized Big Data Handling with Cloud-Based Parallel Divide and Conquer Techniques (A Review)

Yousuf Jamal, Rajeev Kumar Singh
Oriental journal of computer science and technology
Cloud Computing and Resource Management
article

Optimized Big Data Handling with Cloud-Based Parallel Divide and Conquer Techniques (A Review)

Yousuf Jamal, Rajeev Kumar Singh
article en

Abstract

The explosive growth of data across industries has challenged traditional data processing systems, necessitating scalable, efficient, and distributed solutions. This review explores the integration of the divide and conquer paradigm with parallel computing and cloud technologies to address Big Data handling. By examining current techniques, frameworks, and challenges, the article offers a comprehensive overview of how cloud-based parallel divide and conquer strategies optimize Big Data processing in terms of performance, scalability, and cost-efficiency.

Oriental journal of computer science and technologyVol. 17(01)
ITM University (IN)
Openalex Percentile: Top 64%
Cloud Computing and Resource Management
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