Low latency via redundancy

TLDR

Low latency is essential for interactive networked applications, yet reducing the tail of the latency distribution remains challenging even when capacity is scaled. The authors propose that redundancy can convert spare capacity into lower latency and analyze when full replication reduces mean latency. Redundancy is implemented by launching parallel operations on diverse resources and accepting the first completion, thereby improving latency even under extreme conditions. Empirical results show that full replication significantly lowers both mean and tail latency in DNS queries, database servers, and network packet forwarding.

Abstract

Low latency is critical for interactive networked applications. But while we know how to scale systems to increase capacity, reducing latency --- especially the tail of the latency distribution --- can be much more difficult. In this paper, we argue that the use of redundancy is an effective way to convert extra capacity into reduced latency. By initiating redundant operations across diverse resources and using the first result which completes, redundancy improves a system's latency even under exceptional conditions. We study the tradeoff with added system utilization, characterizing the situations in which replicating all tasks reduces mean latency. We then demonstrate empirically that replicating all operations can result in significant mean and tail latency reduction in real-world systems including DNS queries, database servers, and packet forwarding within networks.