• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2419-2426
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• 2015

Named Data Networking (NDN) is one of the powerfully evolving future internet architectures. In this paper installation, configuration and several tests are addressed to show how well and properly our NDN testbed have been prepared and established using NDN platform, in order to have interoperability with global NDN testbed. Global NDN testbed status with our NDN node participation was addressed. To verify one reachability on the NDN connection to global NDN testbed, a latency result is presented using NDN ping test.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.904-913
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• 2020

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.780-784
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• 2017

Data discovery and distribution application that is utilized by climate, high energy physics, and other scientific communities are experiencing performance and large scale data managing problems, that are rooted from the shortcomings of IP architecture. To solve this problem, newly developed data managing applications based on NDN architecture were introduced. In this letter, we present the federated NDN testbed with an NDN-based climate science application and the set of experiments that reflect the performance of NDN based climate application in general with determined and applied optimization.