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Large-scale storage cluster systems need to manage a vast amount of datalocations. A naive data locations management maintains pairs of data ID andnodes storing the data in tables. However, it is not practical when the numberof pairs is too large. To solve this problem, management using datadistribution algorithms, rather than management using tables, has been proposedin recent research. It can distribute data by determining the node for storingthe data based on the datum ID. Such data distribution algorithms require theability to handle the addition or removal of nodes, short calculation time anduniform data distribution in the capacity of each node. This paper proposes adata distribution algorithm called ASURA (Advanced Scalable and Uniform storageby Random number Algorithm) that satisfies these requirements. It achievesfollowing four characteristics: 1) minimum data movement to maintain datadistribution according to node capacity when nodes are added or removed, evenif data are replicated, 2) roughly sub-micro-seconds calculation time, 3) muchlower than 1% maximum variability between nodes in data distribution, and 4)data distribution according to the capacity of each node. The evaluationresults show that ASURA is qualitatively and quantitatively competitive againstmajor data distribution algorithms such as Consistent Hashing, WeightedRendezvous Hashing and Random Slicing. The comparison results show benefits ofeach algorithm; they show that ASURA has advantage in large scale-out storageclusters.

ASURA: Scalable and Uniform Data Distribution Algorithm for Storage Clusters