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Failure Diagnosis for Datacenter Applications
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Zhang, Qiao. |
| 단체저자명 | University of Washington. Computer Science and Engineering. |
| 서명/저자사항 | Failure Diagnosis for Datacenter Applications. |
| 발행사항 | [S.l.] : University of Washington., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 99 p. |
| 소장본 주기 | School code: 0250. |
| ISBN | 9780438174061 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Advisers: Thomas E. Anderson |
| 요약 | Fast and accurate failure diagnosis remains a major challenge for datacenter operators. Current datacenter applications are increasingly architected around loosely-coupled modular components: each component can scale and evolve independently. Ho |
| 요약 | My thesis is that fast and accurate failure diagnosis for datacenter applications is possible using three key ideas: (1) a global view of component interactions and dependencies, (2) a penalized-regression-based failure localization algorithm th |
| 요약 | I present two complementary systems to demonstrate this. The first, Deepview, is a system that can localize virtual hard disk (VHD) failures in Infrastructure-as-a-Service clouds. I show that Deepview localizes VHD failures accurately and quickl |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-12B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14998549 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00024123 | DP 004 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출불가(별치) |
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