PRS:Predication-Based Replica Selection Algorithm for Key-Value Stores

摘要

The tail latency of end-user requests,which directly impacts the user experience and the revenue,is highly related to its corresponding numerous accesses in key-value stores.The replica selection algorithm is crucial to cut the tail latency of these key-value accesses.Recently,the C3 algorithm,which creatively piggybacks the queue-size of waiting keys from replica servers for the replica selection at clients,is proposed in NSDI 2015.Although C3 improves the tail latency a lot,it suffers from the timeliness issue on the feedback information,which directly influences the replica selection.In this paper,we analysis the evaluation of queuesize of waiting keys of C3,and some findings of queue-size variation were made.It motivate us to propose the Prediction-Based Replica Selection(PRS)algorithm,which predicts the queue-size at replica servers under the poor timeliness condition,instead of utilizing the exponentially weighted moving average of the state piggybacked queue-size as in C3.Consequently,PRS can obtain more accurate queue-size at clients than C3,and thus outperforms C3 in terms of cutting the tail latency.Simulation results confirm the advantage of PRS over C3.