Title
HARP: predictive transfer optimization based on historical analysis and real-time probing.
Abstract
Increasingly data-intensive scientific and commercial applications require frequent movement of large datasets from one site to the other. Despite the growing capacity of the networking capacity, these data movements rarely achieve the promised data transfer rates of the underlying physical network due to the poorly tuned data transfer protocols. Accurately and efficiently tuning the data transfer protocol parameters in a dynamically changing network environment is a big challenge and still an open research problem. In this paper, we present predictive end-to-end data transfer optimization algorithms based on historical data analysis and real-time background traffic probing, dubbed HARP. Most of the existing work in this area is solely based on real time network probing, which either cause too much sampling overhead or fail to accurately predict the correct transfer parameters. Combining historical data analysis with real time sampling enables our algorithms to tune the application level data transfer parameters accurately and efficiently to achieve close-to-optimal end-to-end data transfer throughput with very low overhead. Our experimental analysis over a variety of network settings shows that HARP outperforms existing solutions by up to 50% in terms of the achieved throughput.
Year
DOI
Venue
2016
10.1109/SC.2016.24
SC
Keywords
Field
DocType
HARP,predictive transfer optimization,historical analysis,real-time probing,data-intensive scientific application,large dataset movement,networking capacity,data transfer rates,physical network,data transfer protocol parameter tuning,dynamically changing network environment,predictive end-to-end data transfer optimization algorithm,historical data analysis,real-time background traffic probing,real time network probing,real time sampling
Open research,Physical network,Data transmission,Computer science,Real-time computing,HARP,Sampling (statistics),Concurrent computing,Throughput,Data compression
Conference
ISBN
Citations 
PageRank 
978-1-4673-8815-3
12
0.55
References 
Authors
25
3
Name
Order
Citations
PageRank
Engin Arslan111612.12
Kemal Guner2142.28
Kosar, Tevfik361448.67