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We develop an adaptive load distribution protocol for logical volume I/O workload in clustered storage systems. It exploits data redundancy among decentralized storage servers to dynamically route I/O workload on a per-request basis, offering short-term load balancing and improved I/O performance. Our protocol builds on tunable hashing techniques and is(More)
Hash-based randomization is a powerful technique used in clusters and distributed systems for load management. It offers uniform distribution, efficient addressing, little shared state, and scalability. However, simple hash-based randomization is unable to deal with skew and heterogeneity and, therefore, cannot achieve load balance in many environments.(More)
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