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Most modern data stores tend to be distributed, to enable the scaling of thedata across multiple instances of commodity hardware. Although this ensures anear unlimited potential for storage, the data itself is not always ideallypartitioned, and the cost of a network round-trip may cause a degradation ofend-user experience with respect to response latency. The problem being solvedis bringing the data objects closer to the frequent sources of requests using adynamic repartitioning algorithm. This is important if the objective is tomitigate the overhead of network latency, and especially so if the partitionsare widely geo-distributed. The intention is to bring these features to anexisting distributed key-value store product, Redis.

Redynis: Traffic-aware dynamic repartitioning for a distributed key-value store