Computer Science Department
School of Computer Science, Carnegie Mellon University


A Better Model for Job Redundancy:
Decoupling Server Slowdown and Job Size

Kristen Gardner, Mor Harchol-Balter, Alan Scheller-Wolf*, Benny Van Houdt**

October 2016


Keywords: Redundancy, Replication, Parallel servers, Server Slowdown, Task Assignment, RIQ, Redundant-to-Idle-Queue, Redundancy-d

Recent computer systems research has proposed using redundant requests to reduce latency. The idea is to replicate a request so that it joins the queue at multiple servers. The request is considered complete as soon as any one of its copies completes. Redundancy allows us to overcome serverside variability – the fact that a server might be temporarily slow due to factors such as background load, network interrupts, and garbage collection – to reduce response time.

In the past few years, queueing theorists have begun to study redundancy, first via approximations, and, more recently, via exact analysis. Unfortunately, for analytical tractability, most existing theoretical analysis has assumed an Independent Runtimes (IR) model, wherein the replicas of a job each experience independent runtimes (service times) at different servers. The IR model is unrealistic and has led to theoretical results which can be at odds with computer systems implementation results.

This paper introduces a much more realistic model of redundancy. Our model decouples the inherent job size (X) from the server-side slowdown (S), where we track both S and X for each job. Analysis within the S&X model is, of course, much more difficult. Nevertheless, we design a dispatching policy, Redundant-to-Idle-Queue (RIQ), which is both analytically tractable within the S&X model and has provably excellent performance.

32 pages

*Tepper School of Business, Carnegie Mellon University
**Mathematics and Computer Science Department, University of Antwerp, Belgium

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