Abstract
The rapid transfer of massive data in the cloud environment is required to prepare for unexpected situations like disaster recovery. With regard to this requirement, we propose a new approach to transferring cloud virtual machine images rapidly in the cloud environment utilizing dedicated Data Transfer Nodes (DTNs). The overall procedure is composed of local/remote copy processes and a DTN-to-DTN transfer process. These processes are coordinated and executed based on a fork system call in the proposed algorithm. In addition, we especially focus on the local copy process between a cloud controller and DTNs and improve data transfer performance through the well-tuned mount techniques in Network File System (NFS)-based connections. Several experiments have been performed considering the combination of synchronous/asynchronous modes and the network buffer size. We show the results of throughput in all the experiment cases and compare them. Consequently, the best throughput in write operations has been obtained in the case of an NFS server in a DTN and an NFS client in a cloud controller running entirely in the asynchronous mode.
Highlights
As scientific research is performed on the basis of collaboration with other organizations, the storing, transferring, and sharing of massive data are considered to be very important components of efficient collaborative research [1,2]
Deployments, we focus on the external storage use case and propose a way in which to establish the connection between a Data Transfer Nodes (DTNs) and a cloud controller based on Network File System (NFS)
Multiple processes are kept separate while virtual machine (VM) images are transferred to a destination owing to the proposed algorithm based on a fork system call
Summary
As scientific research is performed on the basis of collaboration with other organizations, the storing, transferring, and sharing of massive data are considered to be very important components of efficient collaborative research [1,2]. The DYNES (DYnamic NEtwork Systems) project is aimed at providing novel cyberinfrastructure to support data-intensive science communities such as high-energy physics and astronomy, utilizing dynamic circuit provisioning services. In these challenges, because science big data should be transferred rapidly and reliably, advanced research based on global collaboration requires high-bandwidth networks instead of normal internet for business applications. Symmetry 2018, 10, 110 optimization techniques for transmission, sharing, and storing of science big data It offers an optimized data transmission environment based on DTNs (Data Transfer Nodes), which are high-performance Linux servers with an optimized system kernel and well-tuned TCP
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