A Model-Based Algorithm for Optimizing I/O Intensive Applications in Clouds Using VM-Based Migration
Cluster Computing and the Grid, IEEE International Symposium on (2009)
May 18, 2009 to May 21, 2009
Federated storage resources in geographically distributed environments are becoming viable platforms for data-intensive cloud and grid applications. To improveI /O performance in such environments, we propose a novel model-based I/O performance optimization algorithm for data-intensive applications running on a virtual cluster, which determines virtual machine (VM) migration strategies,i.e., when and where a VM should be migrated, while minimizing the expected value of file access time. We solve this problem as a shortest path problem of a weighted direct acyclic graph (DAG), where the weighted vertex represents a location of a VM and expected file access time from the location, and the weighted edge represents a migration of a VM and time. We construct the DAG from our markov model which represents the dependency of files. Our simulation-based studies suggest that our proposed algorithm can achieve higher performance than simple techniques, such as ones that never migrate VMs: 38% or always migrate VMs onto the locations that hold target files: 47%.
Cloud computing, Data-intensive applications, Virtual cluster, Virtual machine migration
K. Sato, H. Sato and S. Matsuoka, "A Model-Based Algorithm for Optimizing I/O Intensive Applications in Clouds Using VM-Based Migration," Cluster Computing and the Grid, IEEE International Symposium on(CCGRID), Shanghai, China, 2009, pp. 466-471.