Data Placement Strategy of Scientific Workflow Based on Fuzzy Theory in Hybrid Cloud

Abstract

A reasonable data placement strategy is essential to the efficient execution of scientific workflow in hybrid cloud environment.The traditional data placement strategy mainly focuses on the deterministic environment,but the data transmission time is uncertain due to the different load,bandwidth fluctuation and network congestion between different data centers and computer characteristics in the actual network environment.To solve this problem,a fuzzy adaptive discrete particle swarm optimization algorithm based on the fuzzy theory and genetic algorithm operator (FGA-DPSO) is proposed to minimize the fuzzy transmission time of data,place the scientific workflow data reasonably and meet the privacy requirements of the data set and the capacity limit of the data center.The experimental results show that the algorithm can effectively reduce the fuzzy data transmission time of scientific workflow in hybrid cloud environment.

Keywords

• hybrid cloud|scientific workflow|data placement|fuzzy theory|time optimization