Open AccessScience DMZ network architecture deployment and performance evaluation to large scaled data transfer efficiency
Author(s) -
JongSeon Park,
Seunghae Kim,
Min Ki Noh,
Bu Seung Cho
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.33.13884
Subject(s) - computer science , data transmission , dmz , supercomputer , distributed computing , firewall (physics) , network architecture , software deployment , computer network , network security , parallel computing , operating system , physics , schwarzschild radius , classical mechanics , gravitation , charged black hole
Background/Objectives: Recently, it has been great issue to transfer large-scale science dada such as scientific field of high energy physic, astronomical space, super-computing simulation. To solve the transfer issue and to increase transfer efficiency, it needs a multi-dimensional approaches.Methods/Statistical analysis: To improve the transfer performance, approaches from the perspective of components such as network equipment, transmission protocol, and transmission application have been suggested. Effort to TCP congestion control algorithm and parallelism of data transfer channel are representative example to improve performance. However, the solution through the each component has a limitation in maximizing the transmission efficiency.Findings: Science DMZ is a new network architecture that can maximize transfer performance. It maximizes transfer efficiency through approach to all components, such as network equipment, dedicated network path, transfer applications, and local institute firewall policies. With these complicated components, science DMZ network architecture can greatly improve the transfer efficiency. In this paper, we design and construct a science DMZ network architecture between two organizations that utilize supercomputing resources based on KREONET and evaluate the performance.Improvements/Applications: After configuring the experiment environment, we measured network performance through iperf and file transfer performance test through SCP. Experiment result showed around 388% Improvement than that of existing method.