Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/52878

TitleResource usage prediction in distributed key-value datastores
Author(s)Cruz, Francisco
Maia, Francisco
Matos, Miguel Ângelo Marques
Oliveira, Rui Carlos Mendes de
Paulo, João
Pereira, José
Vilaça, Ricardo Manuel Pereira
Issue date2016
PublisherSpringer International Publishing AG
JournalLecture Notes in Computer Science
Abstract(s)In order to attain the promises of the Cloud Computing paradigm, systems need to be able to transparently adapt to environment changes. Such behavior benefits from the ability to predict those changes in order to handle them seamlessly. In this paper, we present a mechanism to accurately predict the resource usage of distributed key-value datastores. Our mechanism requires offline training but, in contrast with other approaches, it is sufficient to run it only once per hardware configuration and subsequently use it for online prediction of database performance under any circumstance. The mechanism accurately estimates the database resource usage for any request distribution with an average accuracy of 94 %, only by knowing two parameters: (i) cache hit ratio; and (ii) incoming throughput. Both input values can be observed in real time or synthesized for request allocation decisions. This novel approach is sufficiently simple and generic, while simultaneously being suitable for other practical applications.
TypeConference paper
URIhttp://hdl.handle.net/1822/52878
ISBN9783319395760
DOI10.1007/978-3-319-39577-7_12
ISSN0302-9743
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:HASLab - Artigos em atas de conferências internacionais (texto completo)

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