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              <p>Distributed storage systems such as Hadoop  File System or Google File System (GFS) ensure data availability and durability using replication. Persistence is achieved by replicating the same data block on several nodes, and ensuring that a minimum number of copies are available on the system at any time. Whenever the contents of a node are lost, for instance due to a hard disk crash, the system regenerates the data blocks stored before the failure by transferring them from the remaining replicas.  This paper is focused on the analysis of the efficiency of replication mechanism  that determines  the location of the copies of a given file at some server. The variability of the loads of the nodes of the network is investigated for several policies. Three  replication mechanisms are tested against simulations in the context of a  real implementation of a such a system: Random, Least Loaded and Power of Choice.The simulations show that some of these policies  may lead to quite unbalanced situations: if $\beta$ is the average number of copies per node it turns out that, at equilibrium, the load of  the nodes may exhibit a high variability. It is shown in this paper that a simple variant of a power of choice type algorithm has a striking effect on the loads of the nodes: at equilibrium, the distribution of the load of a node has a bounded support,  most of nodes have a load less than $2\beta$ which is an interesting property for the design of the storage space of these systems.Mathematical models are introduced and investigated  to explain this  interesting phenomenon.  The analysis of these systems turns out to be quite complicated mainly because of the large dimensionality of the state spaces involved. Our study relies on probabilistic methods, mean-field analysis,  to analyze the asymptotic behavior of an arbitrary node of the network when the total number of nodes gets large. An additional ingredient is the use of stochastic calculus with marked Poisson point processes to establish some of our results.</p>
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