Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Case for Sampling Based Learning Techniques in Coflow Scheduling   Coflow scheduling improves data-intensive application performance by
improving their networking performance. State-of-the-art online coflow
schedulers in essence approximate the classic Shortest-Job-First (SJF)
scheduling by learning the coflow size online. In particular, they use multiple
priority queues to simultaneously accomplish two goals: to sieve long coflows
from short coflows, and to schedule short coflows with high priorities. Such a
mechanism pays high overhead in learning the coflow size: moving a large coflow
across the queues delays small and other large coflows, and moving
similar-sized coflows across the queues results in inadvertent round-robin
scheduling. We propose Philae, a new online coflow scheduler that exploits the
spatial dimension of coflows, i.e., a coflow has many flows, to drastically
reduce the overhead of coflow size learning. Philae pre-schedules sampled flows
of each coflow and uses their sizes to estimate the average flow size of the
coflow. It then resorts to Shortest Coflow First, where the notion of shortest
is determined using the learned coflow sizes and coflow contention. We show
that the sampling-based learning is robust to flow size skew and has the added
benefit of much improved scalability from reduced coordinator-local agent
interactions. Our evaluation using an Azure testbed, a publicly available
production cluster trace from Facebook shows that compared to the prior art
Aalo, Philae reduces the coflow completion time (CCT) in average (P90) cases by
1.50x (8.00x) on a 150-node testbed and 2.72x (9.78x) on a 900-node testbed.
Evaluation using additional traces further demonstrates Philae's robustness to
flow size skew.

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The categories of this paper are: quant-ph
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The categories of this paper are: math-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: comp-gas
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-ex
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The categories of this paper are: eess
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The categories of this paper are: cond-mat
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The categories of this paper are: gr-qc
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The categories of this paper are: cmp-lg
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The categories of this paper are: q-bio
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The categories of this paper are: solv-int
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The categories of this paper are: econ
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: nucl-th