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Automated Cloud Based File Storage Nodes Balancer

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Executive Summary

In distributed file systems, nodes concurrently work for computing and storage functions; a file is partitioned into a number of chunks allocated in distinct nodes so that Map Reduce tasks can be performed in parallel over the nodes. But in this architecture, storage nodes strongly depend on a central server for chunk reallocation which happens to be a manual and time consuming process. This dependence is clearly inadequate in a large-scale, failure-lying environment since the central load balancer is put under considerable workload as it simultaneously need to handle storage nodes and incoming client connections that is linearly scaled with the system size, and thus turn out the performance bottleneck and the single point of failure.

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