Please use this identifier to cite or link to this item:

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
AccessRestricted access (UMinho)
Appears in Collections:HASLab - Artigos em atas de conferências internacionais (texto completo)

Files in This Item:
File Description SizeFormat 
  Restricted access
1,64 MBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID