Study of Effective Scheduling Algorithm for Application of Big Data

Tanmay Paul

Study of Effective Scheduling Algorithm for Application of Big Data

Tanmay Paul * §

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§ Adamas Institute of Technology

Study of Effective Scheduling Algorithm for Application of Big Data

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Abstract

In this new era with the advancement in the technological world the data storage, analysis becomes a major problem. Although the availability of different data storage component like electronic storage such as hard drive or virtual storage such as cloud still the problems remains. The major issue is processing the data because usually the data is in several format and size. Usually processing such huge amount of data with several formats can be time consuming. Using of application such as Hadoop can be beneficial but using of scheduling algorithm can be the best way to for data set analysis to make the process time efficient and analysis the requirement of different scheduling algorithm for the specific data set. In this paper we analysis different data set to explain the most effective scheduling algorithm for that specific data set and then store and execute data set after processing.

References

10 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Tanmay Paul. 2017. "Study of Effective Scheduling Algorithm for Application of Big Data". Global Journal of Computer Science and Technology GJCST-C Volume 17 (GJCST Volume 17 Issue C1).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Classification

H.2.8

Submission ReceivedDecember 10, 2016
Peer Review Double Blind
Handling Editor
Accepted January 4, 2017
Published April 26, 2017

Version of record

v1.2

Issue date

April 26, 2017

Language

English

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Article Matrices

Total Score: 141

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Tanmay Paul (PhD/Dr. count: 0)

View Count (all-time): 482

Total Views (Real + Logic): 2749

Total Downloads (simulated): 188

Publish Date: 2017 01, Sun

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Total Views: 2.7K

Total Downloads: 188

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