Making Every Bit Count in Wide-Area Analytics
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You are not authorized to post comments.Ariel Rabkin, Matvey Arye, Siddhartha Sen, Vivek Pai, and Michael J. Freedman, Princeton University
Many data sets, such as system logs, are generated from widely distributed locations. Current distributed systems often discard this data because they lack the ability to backhaul it efficiently, or to do anything meaningful with it at the distributed sites. This leads to lost functionality, efficiency, and business opportunities. The problem with traditional backhaul approaches is that they are slow and costly, and require analysts to define the data they are interested in up-front. We propose a new architecture that stores data at the edge (i.e., near where it is generated) and supports rich real-time and historical queries on this data, while adjusting data quality to cope with the vagaries of wide-area bandwidth. In essence, this design transforms a distributed data collection system into a distributed data analysis system, where decisions about collection do not preclude decisions about analysis.
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author = {Ariel Rabkin and Matvey Arye and Siddhartha Sen and Vivek Pai and Michael J. Freedman},
title = {Making Every Bit Count in {Wide-Area} Analytics},
booktitle = {14th Workshop on Hot Topics in Operating Systems (HotOS XIV)},
year = {2013},
address = {Santa Ana Pueblo, NM},
url = {https://www.usenix.org/conference/hotos13/session/rabkin},
publisher = {USENIX Association},
month = may
}
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