Cloud Data Migration Method Based on PSO Algorithm

Cloud storage system can play an important role in large-scale, and it supports high-performance cloud applications. To cloud storage systems, data migration is key technology to realize the nodes dynamically extensible and elastic load balancing. How to reduce migration cost of time is the problem that cloud service providers need to solve. Existing research efforts were focused on the data migration issues under the non-virtualized environments, which often do not applicable to cloud storage systems. In response to these challenges, we put data migration issues into the load-balancing scenarios to solve. We propose an algorithm based on particle swarm optimization algorithm which can reduces the cost of time. In the experiment, we can use Yahoo services benchmarking YCSB tool which could verify the validity of the method. It is a test framework designed to help users understand the different cloud computing, database performance.