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Providing In-network Support to Coflow Scheduling

Hernandez Benet, Cristian (author)
Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
Kassler, Andreas (author)
Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
Antichi, Gianni (author)
Queen Mary University, United Kingdom
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A. Benson, Theophilus (author)
Brown University, United States
Pongracz, Gergely (author)
Ericsson
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 (creator_code:org_t)
IEEE, 2021
2021
English.
In: Proceedings of the 2021 IEEE Conference on Network Softwarization: Accelerating Network Softwarization in the Cognitive Age, NetSoft 2021. - : IEEE. - 9781665405225 ; , s. 235-243
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Many emerging distributed applications, including big data analytics, generate a number of flows that concurrently transport data across data center networks. To improve their performance, it is required to account for the behavior of a collection of flows, i.e., coflows, rather than individual. State-of-the-art solutions allow for a near-optimal completion time by continuously reordering the unfinished coflows at the end-host, using network priorities. This paper shows that dynamically changing flow priorities at the end host, without taking into account in-flight packets, can cause high-degrees of packet re-ordering, thus imposing pressure on the congestion control and potentially harming network performance in the presence of switches with shallow buffers. We present pCoflow, a new solution that integrates end-host based coflow ordering with in-network scheduling based on packet history. Our evaluation shows that pCoflow improves in CCT upon state-of-the-art solutions by up to 34% for varying load.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

Coflow
Datacenter Networks
P4
Dataplane Programming
Computer Science
Datavetenskap

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