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DMFD: Non-Intrusive Dependency Inference and Flow Ratio Model for Performance Anomaly Detection in Multi-Tier Cloud Applications

AuthID
P-00R-37M

Author(s)

Fu, SB

Prior, R

Kim, H

Editor(s)

Elisa Bertino; Carl K. Chang; Peter Chen; Ernesto Damiani; Michael Goul; Katsunori Oyama

Document Type

Proceedings Paper

Year published

2019

Published

in 2019 IEEE 12TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (IEEE CLOUD 2019) in IEEE International Conference on Cloud Computing, ISSN: 2159-6182

Volume: 2019-July, Pages: 164-173 (10)

Conference

12Th Ieee International Conference on Cloud Computing (Ieee Cloud) Held as Part of Ieee World Congress on Services (Ieee Services), Date: JUL 08-13, 2019, Location: MIlan, ITALY, Sponsors: IEEE, IEEE Comp Soc, CCF TCSC

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Metadata
Sources

Publication Identifiers

DOI: 10.1109/cloud.2019.00036

Dblp: conf/IEEEcloud/FuPK19

Scopus: 2-s2.0-85072323339

Wos: WOS:000556208000023

Source Identifiers

ISSN: 2159-6182

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