How to Scale Exponential Backoff

TL;DR

This paper introduces Re-Backoff, a scalable and robust exponential backoff protocol that guarantees constant throughput and polylogarithmic access attempts even under worst-case process arrivals and resource unavailability.

Contribution

The paper presents Re-Backoff, a simple protocol that improves exponential backoff by ensuring constant throughput and robustness in worst-case online scenarios.

Findings

Expected constant throughput with dynamic arrivals

Polylogarithmic expected access attempts per process

Robustness to resource unavailability periods

Abstract

Randomized exponential backoff is a widely deployed technique for coordinating access to a shared resource. A good backoff protocol should, arguably, satisfy three natural properties: (i) it should provide constant throughput, wasting as little time as possible; (ii) it should require few failed access attempts, minimizing the amount of wasted effort; and (iii) it should be robust, continuing to work efficiently even if some of the access attempts fail for spurious reasons. Unfortunately, exponential backoff has some well-known limitations in two of these areas: it provides poor (sub-constant) throughput (in the worst case), and is not robust (to resource acquisition failures). The goal of this paper is to "fix" exponential backoff by making it scalable, particularly focusing on the case where processes arrive in an on-line, worst-case fashion. We present a relatively simple backoff protocol~Re-Backoff~that has, at its heart, a version of exponential backoff. It guarantees expected constant throughput with dynamic process arrivals and requires only an expected polylogarithmic number of access attempts per process. Re-Backoff is also robust to periods where the shared resource is unavailable for a period of time. If it is unavailable for $D$ time slots, Re-Backoff provides the following guarantees. When the number of packets is a finite $n$, the average expected number of access attempts for successfully sending a packet is $O(\log^2( n + D))$. In the infinite case, the average expected number of access attempts for successfully sending a packet is $O( \log^2(\eta) + \log^2(D) )$ where $\eta$ is the maximum number of processes that are ever in the system concurrently.