I/O Traffic Management on PC-Cluster based Cloud Storage System

Abstract

Cloud storage system architecture and design plays a vital role in the cloud computing infrastructure. Cloud storage system provides users to efficient storage space with elasticity feature. One of the challenges of cloud storage server is difficult to balance the providing huge elastic capacity of storage and investment of expensive cost for it. In order to solve this issue, we propose the low cost PC cluster based storage system architecture which can be activated to store a large amount of data and provide cost-effective for cloud storage user and present FP-growth algorithm for metadata prefetching method and Least Recently Used (LRU) replacement policy for caching to improve performance by reducing response time. According to the experimental testing, the storage can be utilized more than 90% of storage space and can significantly reduce the average response time.