Evaluating adaptive compression to mitigate the effects of shared I/O in clouds

IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum

Volumn , Issue , 2011, Pages 1042-1051

  Hovestadt, Matthias ^a   Kao, Odej ^a   Kliem, Andreas ^a   Warneke, Daniel ^a  

^a TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

Adaptive compression; Cloud computing; I O performance

Indexed keywords

ADAPTIVE COMPRESSION; AMAZON EC2; APPLICATION DATA; CO-LOCATED; CPU UTILIZATION; DATA-INTENSIVE APPLICATION; DECISION MODELS; DISTRIBUTED SYSTEMS; EXPERIMENTAL EVALUATION; I/O BANDWIDTH; I/O PERFORMANCE; PERFORMANCE DEGRADATION; POTENTIAL LOSS; TRAINING PHASE; VIRTUAL MACHINES; VIRTUALIZATIONS; VIRTUALIZED ENVIRONMENT;

BANDWIDTH; CLOUD COMPUTING; CLOUDS; DISTRIBUTED PARAMETER NETWORKS; ELASTICITY; PARALLEL PROCESSING SYSTEMS; VIRTUAL REALITY;

BANDWIDTH COMPRESSION;

EID: 83455172022     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPDPS.2011.256     Document Type: Conference Paper

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