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020 ▼a 9780438168046
035 ▼a (MiAaPQ)AAI10812695
035 ▼a (MiAaPQ)ucsd:17380
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 004
1001 ▼a Roy, Arjun.
24510 ▼a Simplifying Datacenter Fault Detection and Localization.
260 ▼a [S.l.] : ▼b University of California, San Diego., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 184 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Advisers: Alex C. Snoeren
5021 ▼a Thesis (Ph.D.)--University of California, San Diego, 2018.
520 ▼a The proliferation of distributed internet services has reaffirmed the need for reliable and high-performance networks, not only in the WAN bringing users to the services, but within the datacenters where services themselves reside. Services cons
520 ▼a In particular, datacenters are susceptible to insidious parasitic performance loss due to a class of network component fault known as partial faults---where a component is nominally healthy, but intermittently drops or delays traffic. These faul
520 ▼a Unfortunately, partial faults can confound existing fault detection methods in several ways, including interactions between the fault itself, application traffic characteristics, and networking hardware. For example, network switches may fail to
520 ▼a However, this work shows that the scale and regular design of contemporary datacenters can simplify partial-fault localization. In particular, the combination of large-scale load-balanced multipath topologies and high-volume datacenter traffic e
590 ▼a School code: 0033.
650 4 ▼a Computer science.
690 ▼a 0984
71020 ▼a University of California, San Diego. ▼b Computer Science.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0033
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998036 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자