Resource Usage Prediction in Distributed Key-Value Datastores - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Resource Usage Prediction in Distributed Key-Value Datastores

Résumé

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.
Fichier principal
Vignette du fichier
416479_1_En_12_Chapter.pdf (1.6 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01434791 , version 1 (13-01-2017)

Licence

Paternité

Identifiants

Citer

Francisco Cruz, Francisco Maia, Miguel Matos, Rui Oliveira, João Paulo, et al.. Resource Usage Prediction in Distributed Key-Value Datastores. 16th IFIP WG 6.1 International Conference on Distributed Applications and Interoperable Systems (DAIS), Jun 2016, Heraklion, Crete, Greece. pp.144-159, ⟨10.1007/978-3-319-39577-7_12⟩. ⟨hal-01434791⟩
50 Consultations
50 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More