---
type: source
title: "AIMD Dynamics and Distributed Resource Allocation"
author: "Martin J. Corless, C. King, R. Shorten, F. Wirth (SIAM)"
url: https://epubs.siam.org/doi/book/10.1137/1.9781611974225
date: 2016-01-01
domain: internet-finance
format: paper
status: processed
tags: [pipeline-architecture, operations-research, AIMD, distributed-resource-allocation, congestion-control, fairness]
processed_by: rio
processed_date: 2026-03-11
claims_extracted: ["aimd-converges-to-fair-resource-allocation-without-global-coordination-through-local-congestion-signals.md", "aimd-scaling-solves-variable-load-expensive-compute-coordination-without-prediction.md"]
extraction_model: "anthropic/claude-sonnet-4.5"
extraction_notes: "Extracted two claims: (1) general AIMD mechanism properties as proven coordination algorithm, (2) specific application to Teleo pipeline architecture. The source is a formal mathematical treatment (SIAM monograph) providing rigorous proofs, making the first claim 'proven' confidence. The second claim is an application proposal with theoretical justification but no empirical validation, hence 'experimental'. No entities to extract—this is pure mechanism theory. No enrichments—AIMD is not currently referenced in the KB."
---

# AIMD Dynamics and Distributed Resource Allocation

SIAM monograph on AIMD (Additive Increase Multiplicative Decrease) as a general-purpose distributed resource allocation mechanism. Extends the TCP congestion control principle to resource allocation in computing, energy, and other domains.

## Key Content

- AIMD is the most widely used method for allocating limited resources among competing agents without centralized control
- Core algorithm: additive increase when no congestion (rate += α), multiplicative decrease when congestion detected (rate *= β, where 0 < β < 1)
- Provably fair: converges to equal sharing of available bandwidth/capacity
- Provably stable: system converges regardless of number of agents or parameter values
- Three sample applications: internet congestion control, smart grid energy allocation, distributed computing
- Key property: no global information needed — each agent only needs to observe local congestion signals

## Relevance to Teleo Pipeline

AIMD provides a principled, proven scaling algorithm: when eval queue is shrinking (no congestion), increase extraction workers by 1 per cycle. When eval queue is growing (congestion), halve extraction workers. This doesn't require predicting load, modeling arrivals, or solving optimization problems — it reacts to observed system state and is mathematically guaranteed to converge. Perfect for our "expensive compute, variable load" setting.


## Key Facts
- AIMD algorithm: additive increase (rate += α) when no congestion, multiplicative decrease (rate *= β, 0 < β < 1) when congestion detected
- AIMD is the foundation of TCP congestion control
- AIMD has been applied to internet congestion control, smart grid energy allocation, and distributed computing
- AIMD convergence is mathematically proven regardless of number of agents or parameter values
