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

Atilla Ergüzen, Mahmut Ünver
2018 Applied Sciences  
Featured Application: The most important key features of this study are high performance, easy scalability and serverless architecture. In this way, the system can work with fewer hardware elements and be more robust than others that use name node architecture. Also, both the reliability and performance of the system are significantly increased by separating replication nodes from data nodes. As a result, a complete big data solution that is easy to manage and performs well has been produced
more » ... successfully used. Abstract: 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).
doi:10.3390/app8060913 fatcat:x5qhxpq7izfzzhexoc2i65jpda