# Is Our Model for Contention Resolution Wrong?

## TL;DR

This paper challenges the effectiveness of modern contention-resolution algorithms inspired by binary exponential backoff (BEB), revealing that they underperform in practice due to flawed collision cost assumptions, and emphasizes the importance of collision metrics.

## Contribution

The study demonstrates that newer algorithms inspired by BEB perform worse in practice and identifies flawed collision cost abstractions as a key issue, suggesting a need to reconsider algorithm design.

## Key findings

- New algorithms underperform compared to BEB in practical simulations.
- Flawed collision cost assumptions impact algorithm performance.
- Collision count is an important metric alongside makespan.

## Abstract

Randomized binary exponential backoff (BEB) is a popular algorithm for coordinating access to a shared channel. With an operational history exceeding four decades, BEB is currently an important component of several wireless standards. Despite this track record, prior theoretical results indicate that under bursty traffic (1) BEB yields poor makespan and (2) superior algorithms are possible. To date, the degree to which these findings manifest in practice has not been resolved. To address this issue, we examine one of the strongest cases against BEB: $n$ packets that simultaneously begin contending for the wireless channel. Using Network Simulator 3, we compare against more recent algorithms that are inspired by BEB, but whose makespan guarantees are superior. Surprisingly, we discover that these newer algorithms significantly underperform. Through further investigation, we identify as the culprit a flawed but common abstraction regarding the cost of collisions. Our experimental results are complemented by analytical arguments that the number of collisions -- and not solely makespan -- is an important metric to optimize. We believe that these findings have implications for the design of contention-resolution algorithms.