Throughput Analytics of Data Transfer Infrastructures

Nageswara S.V. Rao, Qiang Liu, Zhengchun Liu, Rajkumar Kettimuthu, Ian Foster

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

To support increasingly distributed scientific and big-data applications, powerful data transfer infrastructures are being built with dedicated networks and software frameworks customized to distributed file systems and data transfer nodes. The data transfer performance of such infrastructures critically depends on the combined choices of file, disk, and host systems as well as network protocols and file transfer software, all of which may vary across sites. The randomness of throughput measurements makes it challenging to assess the impact of these choices on the performance of infrastructure or its parts. We propose regression-based throughput profiles by aggregating measurements from sites of the infrastructure, with RTT as the independent variable. The peak values and convex-concave shape of a profile together determine the overall throughput performance of memory and file transfers, and its variations show the performance differences among the sites. We then present projection and difference operators, and coefficients of throughput profiles to characterize the performance of infrastructure and its parts, including sites and file transfer tools. In particular, the utilization-concavity coefficient provides a value in the range [0, 1] that reflects overall transfer effectiveness. We present results of measurements collected using (i) testbed experiments over dedicated 0–366 ms 10 Gbps connections with combinations of TCP versions, file systems, host systems and transfer tools, and (ii) Globus GridFTP transfers over production infrastructure with varying site configurations.

Original languageEnglish
Title of host publicationTestbeds and Research Infrastructures for the Development of Networks and Communities - 13th EAI International Conference, TridentCom 2018, Proceedings
EditorsHonghao Gao, Huaikou Miao, Xiaoxian Yang, Yuyu Yin
PublisherSpringer Verlag
Pages20-40
Number of pages21
ISBN (Print)9783030129705
DOIs
StatePublished - 2019
Event13th EAI International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, TridentCom 2018 - Shanghai, China
Duration: Dec 1 2018Dec 3 2018

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume270
ISSN (Print)1867-8211

Conference

Conference13th EAI International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, TridentCom 2018
Country/TerritoryChina
CityShanghai
Period12/1/1812/3/18

Funding

This work is funded by RAMSES project and the Applied Mathematics Program, Office of Advanced Computing Research, U.S. Department of Energy, and by Extreme Scale Systems Center, sponsored by U. S. Department of Defense, and performed at Oak Ridge National Laboratory managed by UT-Battelle, LLC for U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

FundersFunder number
Office of Advanced Computing Research
U. S. Department of Defense
UT-Battelle
U.S. Department of EnergyDE-AC05-00OR22725
Oak Ridge National Laboratory

    Keywords

    • Data transfer
    • Infrastructure
    • Throughput profile

    Fingerprint

    Dive into the research topics of 'Throughput Analytics of Data Transfer Infrastructures'. Together they form a unique fingerprint.

    Cite this