Title
How to Scale Exponential Backoff: Constant Throughput, Polylog Access Attempts, and Robustness.
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: it provides poor (sub-constant) throughput (in the worst case), and is not robust (to adversarial disruption). 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(log2(n + D)). In the infinite case, the average expected number of access attempts for successfully sending a packet is O(log2(η + D)) where η is the maximum number of processes that are ever in the system concurrently.
Year
DOI
Venue
2016
10.5555/2884435.2884482
SODA '16: Symposium on Discrete Algorithms Arlington Virginia January, 2016
Field
DocType
ISBN
Consensus,Exponential backoff,Discrete mathematics,Computer science,Network packet,Markov chain,Computer network,Robustness (computer science),Throughput,Shared resource,Distributed computing,Scalability
Conference
978-1-61197-433-1
Citations 
PageRank 
References 
12
0.47
36
Authors
4
Name
Order
Citations
PageRank
Michael A. Bender12144138.24
Jeremy T. Fineman258736.10
Seth Gilbert3141394.72
Maxwell Young421017.86