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Path Persistence in the Cloud: A Study of the Effects of Inter-Region Traffic Engineering in a Large Cloud Provider's Network
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS, Network Systems Laboratory (NS Lab).ORCID iD: 0000-0001-5890-9629
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS, Network Systems Laboratory (NS Lab).ORCID iD: 0000-0001-7642-6591
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS, Network Systems Laboratory (NS Lab).
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS, Network Systems Laboratory (NS Lab).
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2020 (English)In: Computer communication review, ISSN 0146-4833, E-ISSN 1943-5819, Vol. 50, no 2, p. 11-23Article in journal, Editorial material (Refereed) Published
Abstract [en]

A commonly held belief is that traffic engineering and routing changes are infrequent. However, based on our measurements over a number of years of traffic between data centers in one of the largest cloud provider's networks, we found that it is common for flows to change paths at ten-second intervals or even faster. These frequent path and, consequently, latency variations can negatively impact the performance of cloud applications, specifically, latency-sensitive and geo-distributed applications.

Our recent measurements and analysis focused on observing path changes and latency variations between different Amazon aws regions. To this end, we devised a path change detector that we validated using both ad hoc experiments and feedback from cloud networking experts. The results provide three main insights: (1) Traffic Engineering (TE) frequently moves (TCP and UDP) flows among network paths of different latency, (2) Flows experience unfair performance, where a subset of flows between two machines can suffer large latency penalties (up to 32% at the 95th percentile) or excessive number of latency changes, and (3) Tenants may have incentives to selfishly move traffic to low latency classes (to boost the performance of their applications). We showcase this third insight with an example using rsync synchronization.

To the best of our knowledge, this is the first paper to reveal the high frequency of TE activity within a large cloud provider's network. Based on these observations, we expect our paper to spur discussions and future research on how cloud providers and their tenants can ultimately reconcile their independent and possibly conflicting objectives. Our data is publicly available for reproducibility and further analysis at http://goo.gl/25BKte.

Place, publisher, year, edition, pages
New York, NY, United States: Association for Computing Machinery (ACM), 2020. Vol. 50, no 2, p. 11-23
Keywords [en]
Traffic engineering, Cloud provider networks, Inter-datacenter traffic, Latency
National Category
Communication Systems Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-273758DOI: 10.1145/3402413.3402416ISI: 000582604500005Scopus ID: 2-s2.0-85086379414OAI: oai:DiVA.org:kth-273758DiVA, id: diva2:1432918
Funder
Swedish Foundation for Strategic Research , TCCEU, European Research Council, 770889
Note

QC 20200602

Available from: 2020-05-28 Created: 2020-05-28 Last updated: 2024-03-18Bibliographically approved

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Reda, WaleedBogdanov, KirillMilolidakis, AlexandrosGhasemirahni, HamidChiesa, MarcoMaguire Jr., Gerald Q.Kostic, Dejan

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Reda, WaleedBogdanov, KirillMilolidakis, AlexandrosGhasemirahni, HamidChiesa, MarcoMaguire Jr., Gerald Q.Kostic, Dejan
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