Storage Node Allocation Methods for Erasure Code-based Cloud Storage Systems

Erasure codes, in the recent past, have emerged as an alternative to data replication-based systems for storing big data. Efficient choice of code and data nodes from the numerous available storage nodes is the key to the performance of any storage system. This paper presents the Storage Node Allocation Problem for selecting the suitable set of nodes for holding data and code blocks by representing the storage systems as a complete bipartite graph. Additionally, the paper formally proves that the problem is NP-hard and proposes approximate solutions using greedy, ant colony optimization and clustering-based methods. The solutions accomplish efficient choice of storage nodes by utilizing parameters like bandwidth availability, distance between the nodes, computational load and disk space availability.