Title :
Executing Data-Intensive Workloads in a Cloud
Author :
Mian, Rizwan ; Martin, Patrick
Author_Institution :
Database Syst. Lab. (DSL), Queen´´s Univ., Kingston, ON, Canada
Abstract :
The promise of "infinite" resources given by the cloud computing paradigm has led to recent interest in exploiting clouds for large-scale data-intensive computing. Given this supposedly infinite resource set, we need a management function that regulates application workload on these resources. This doctoral research focuses on two aspects of workload management, namely scheduling and provisioning. We propose a novel framework for workload execution and resource provisioning, and associated models, algorithms, and protocols.
Keywords :
cloud computing; processor scheduling; resource allocation; associated models; cloud computing paradigm; data-intensive workload execution; large-scale data-intensive computing; management function; resource provisioning; workload management; Adaptation models; Cloud computing; Elasticity; Prediction algorithms; Predictive models; Processor scheduling; Search problems; cloud computing; data-intensive computing; workload management;
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4673-1395-7
DOI :
10.1109/CCGrid.2012.18