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A Prediction Based Replica Selection Strategy for Reducing Tail Latency in Distributed Systems

In the distributed system, applications often suffer from unexpectedly high response time fluctuation which is a consequence of long-tail latency. One efficient way of reducing tail latency is to use an appropriate replica selection strategy. In this paper, through extensive experiments, we analyze and evaluate two popular state-of-the-art replica selection strategies of key-value store systems: Cassandra dynamic snitch and C3. After analyzing all the experimental results we develop a prediction based replica selection strategy and implement it on Cassandra 3.0. Our proposed algorithm outperforms both C3 and Cassandra dynamic snitch. For evaluation, we test Cassandra dynamic snitch, C3, and our proposed algorithm on a 15 nodes Cassandra cluster. For generating test datasets and workloads we use industry-standard Yahoo Cloud Serving Benchmark (YCSB).