A data placement algorithm with binary weighted tree on PC cluster-based cloud storage system

Abstract

The need and use of scalable storage on cloud has rapidly increased in last few years. Organizations need large amount of storage for their operational data and backups. To address this need, high performance storage servers for cloud computing are the ultimate solution, but they are very expensive. Therefore we propose efficient cloud storage system by using inexpensive and commodity computer nodes. These computer nodes are organized into PC cluster as datacenter. Data objects are distributed and replicated in a cluster of commodity nodes located in the cloud. In the proposed cloud storage system, a data placement algorithm which provides a highly available and reliable storage is proposed. The proposed algorithm applies binary tree to search storage nodes. It supports the weighted allocation of data objects, balancing load on PC cluster with minimum cost. The proposed system is implemented with HDFS and experimental results prove that the proposed algorithm can balance storage load depending on the disk space, expected availability and failure probability of each node in PC cluster.