Measurement and performance issues of transport protocols over 10Gbps high-speed optical networks

Wu, Yixin; Kumar, Suman; Park, Seung-Jong

doi:10.1016/j.comnet.2009.09.017

Cited by 10 publications

(3 citation statements)

References 22 publications

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“…In most cases, congestion is not a concern in dedicated high bandwidth networks. However, the latency wall in data transfers over high bandwidth connections is still an issue [12,13,14]. Enough data should be obtained from the applications and storage layers for high throughput performance.…”

Section: Adaptive Transfer Adjustmentmentioning

confidence: 99%

Adaptive Transfer Adjustment in Efficient Bulk Data Transfer Management for Climate Datasets

Sim¹,

Balman²,

Williams³

et al. 2010

Informatics

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Many scientific applications and experiments, such as high energy and nuclear physics, astrophysics, climate observation and modeling, combustion, nano-scale material sciences, and computational biology, generate extreme volumes of data with a large number of files. These data sources are distributed among national and international data repositories, and are shared by large numbers of geographically distributed scientists. A large portion of the data is frequently accessed, and a large volume of data is moved from one place to another for analysis and storage. A challenging issue in such efforts is the limited network capacity for moving large datasets. A tool that addresses this challenge is the Bulk Data Mover (BDM), a data transfer management tool used in the Earth System Grid (ESG) community. It has been managing massive dataset transfers efficiently in the environment where the network bandwidth is limited. Adaptive transfer adjustment was studied to enhance the BDM to handle significant end-to-end performance changes in the dynamic network environments as well as to control the data transfers for the desired transfer performance. We describe the results from our hands-on data transfer management experience in the climate research community. We study a practical transfer estimation model and state our initial results from the adaptive transfer adjustment methodology.

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Section: Adaptive Transfer Adjustmentmentioning

confidence: 99%

Adaptive Transfer Adjustment in Efficient Bulk Data Transfer Management for Climate Datasets

Sim¹,

Balman²,

Williams³

et al. 2010

Informatics

View full text Add to dashboard Cite

show abstract

“…In most cases, congestion is not a concern in dedicated high bandwidth networks. However, the latency wall in data transfers over high bandwidth connections is still an issue [12,13,14].…”

Section: Dynamic Transfer Adjustmentmentioning

confidence: 99%

Bulk Data Movement for Climate Dataset: Efficient Data Transfer Management with Dynamic Transfer Adjustment

Sim

Balman

Williams

et al. 2010

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Many scientific applications and experiments, such as high energy and nuclear physics, astrophysics, climate observation and modeling, combustion, nano-scale material sciences, and computational biology, generate extreme volumes of data with a large number of files. These data sources are distributed among national and international data repositories, and are shared by large numbers of geographically distributed scientists. A large portion of data is frequently accessed, and a large volume of data is moved from one place to another for analysis and storage. One challenging issue in such efforts is the limited network capacity for moving large datasets to explore and manage. The Bulk Data Mover (BDM), a data transfer management tool in the Earth System Grid (ESG) community, has been managing the massive dataset transfers efficiently with the pre-configured transfer properties in the environment where the network bandwidth is limited. Dynamic transfer adjustment was studied to enhance the BDM to handle significant end-to-end performance changes in the dynamic network environment as well as to control the data transfers for the desired transfer performance. We describe the results from the BDM transfer management for the climate datasets. We also describe the transfer estimation model and results from the dynamic transfer adjustment.

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“…is still an issue [1,2,3]. Enough data should be obtained from the applications and storage layers for high throughput performance.…”

mentioning

confidence: 99%

Dynamic Adaptation for High-Performance Data Transfers

Balman¹

2011

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Measurement and performance issues of transport protocols over 10Gbps high-speed optical networks

Cited by 10 publications

References 22 publications

Adaptive Transfer Adjustment in Efficient Bulk Data Transfer Management for Climate Datasets

Adaptive Transfer Adjustment in Efficient Bulk Data Transfer Management for Climate Datasets

Bulk Data Movement for Climate Dataset: Efficient Data Transfer Management with Dynamic Transfer Adjustment

Dynamic Adaptation for High-Performance Data Transfers

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