ProRenaTa: Proactive and reactive tuning to scale a distributed storage system

Proceedings - 2015 IEEE/ACM 15th International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015

Volumn , Issue , 2015, Pages 453-464

  Liu, Ying ^a,c   Rameshan, Navaneeth ^a,b   Monte, Enric ^b   Vlassov, Vladimir ^a   Navarro, Leandro ^b  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^c UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

Author keywords

Auto scaling; Elasticity; Resource utilization; SLA; Workload prediction

Indexed keywords

CLUSTER COMPUTING; CONTROLLERS; DIGITAL STORAGE; ELASTICITY; MULTIPROCESSING SYSTEMS; QUALITY OF SERVICE;

AUTO-SCALING; DISTRIBUTED STORAGE SYSTEM; FEED-BACK BASED; PREDICTION-BASED; PRO-ACTIVE APPROACH; RESOURCE UTILIZATIONS; STATE-OF-THE-ART APPROACH; WORKLOAD PREDICTIONS;

GRID COMPUTING;

EID: 84941206623     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCGrid.2015.26     Document Type: Conference Paper

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