Next Article in Journal
Formic Acid Manufacture: Carbon Dioxide Utilization Alternatives
Next Article in Special Issue
Stacked Sparse Autoencoders for EMG-Based Classification of Hand Motions: A Comparative Multi Day Analyses between Surface and Intramuscular EMG
Previous Article in Journal
Textile-Based Flexible Coils for Wireless Inductive Power Transmission
Previous Article in Special Issue
Predicting the Failure of Dental Implants Using Supervised Learning Techniques
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Appl. Sci. 2018, 8(6), 913;

Developing a File System Structure to Solve Healthy Big Data Storage and Archiving Problems Using a Distributed File System

Department of Computer Engineering, Faculty of Engineering, Kırıkkale University Ankara Yolu 7. Km, 71450 Kırıkkale, Turkey
Author to whom correspondence should be addressed.
Received: 7 May 2018 / Revised: 29 May 2018 / Accepted: 30 May 2018 / Published: 2 June 2018
(This article belongs to the Special Issue Deep Learning and Big Data in Healthcare)
Full-Text   |   PDF [3236 KB, uploaded 5 June 2018]   |  


Recently, the use of internet has become widespread, increasing the use of mobile phones, tablets, computers, Internet of Things (IoT) devices and other digital sources. In the health sector with the help of new generation digital medical equipment, this digital world also has tended to grow in an unpredictable way in that it has nearly 10% of the global wide data itself and continues to keep grow beyond what the other sectors have. This progress has greatly enlarged the amount of produced data which cannot be resolved with conventional methods. In this work, an efficient model for the storage of medical images using a distributed file system structure has been developed. With this work, a robust, available, scalable, and serverless solution structure has been produced, especially for storing large amounts of data in the medical field. Furthermore, the security level of the system is extreme by use of static Internet protocol (IP), user credentials, and synchronously encrypted file contents. One of the most important key features of the system is high performance and easy scalability. In this way, the system can work with fewer hardware elements and be more robust than others that use name node architecture. According to the test results, it is seen that the performance of the designed system is better than 97% from a Not Only Structured Query Language (NoSQL) system, 80% from a relational database management system (RDBMS), and 74% from an operating system (OS). View Full-Text
Keywords: big data; distributed file system; health data; medical imaging big data; distributed file system; health data; medical imaging

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Ergüzen, A.; Ünver, M. Developing a File System Structure to Solve Healthy Big Data Storage and Archiving Problems Using a Distributed File System. Appl. Sci. 2018, 8, 913.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top