When do redundant requests reduce latency ?

Several systems possess the flexibility to serve requests in more than one way. For instance, a distributed storage system storing multiple replicas of the data can serve a request from any of the multiple servers that store the requested data, or a computational task may be performed in a compute-cluster by any one of multiple processors. In such systems, the latency of serving the requests may potentially be reduced by sending redundant requests: a request may be sent to an excess number of servers, and it is deemed served when the requisite number of servers complete service. Such a mechanism trades off the possibility of faster execution of at least one copy of the request with the increase in the delay due to an increased load on the system. Due to this tradeoff, it is unclear when redundant requests may actually help. Several recent works empirically evaluate the latency performance of redundant requests in diverse settings. This work aims at a rigorous analytical study of the latency performance of redundant requests, with the primary goals of characterizing the situations when sending redundant requests will help (and when not), and designing optimal redundant-requesting policies. We first present a model that captures the key features of such systems. We show that when service times are i.i.d. memoryless or “heavy”, and when the additional copies of already-completed jobs can be removed with negligible costs, redundant requests reduce the average latency. On the other hand, when service times are “light” or when service times are memoryless and removal of jobs results in a non-negligible penalty, not having any redundancy in the request is optimal under high loads. Our results hold for arbitrary arrival processes.