Rio
25a98b60ab
Co-authored-by: Rio <rio@agents.livingip.xyz> Co-committed-by: Rio <rio@agents.livingip.xyz>
30 lines
1.9 KiB
Markdown
30 lines
1.9 KiB
Markdown
---
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type: source
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title: "AIMD Scheduling and Resource Allocation in Distributed Computing Systems"
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author: "Vlahakis, Athanasopoulos et al."
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url: https://arxiv.org/abs/2109.02589
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date: 2021-09-06
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domain: internet-finance
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format: paper
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status: unprocessed
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tags: [pipeline-architecture, operations-research, AIMD, distributed-computing, resource-allocation, congestion-control]
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---
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# AIMD Scheduling and Resource Allocation in Distributed Computing Systems
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Applies TCP's AIMD (Additive Increase Multiplicative Decrease) congestion control to distributed computing resource allocation — scheduling incoming requests across computing nodes.
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## Key Content
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- Models distributed system as multi-queue scheme with computing nodes
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- Proposes AIMD-like admission control: stable irrespective of total node count and AIMD parameters
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- Key insight: congestion control in networks and worker scaling in compute pipelines are the same problem — matching producer rate to consumer capacity
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- Decentralized resource allocation using nonlinear state feedback achieves global convergence to bounded set in finite time
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- Connects to QoS via Little's Law: local queuing time calculable from simple formula
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- AIMD is proven optimal for fair allocation of shared resources among competing agents without centralized control
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## Relevance to Teleo Pipeline
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AIMD provides an elegant scaling policy: when queue is shrinking (system healthy), add workers linearly (e.g., +1 per cycle). When queue is growing (system overloaded), cut workers multiplicatively (e.g., halve them). This is self-correcting, proven stable, and doesn't require predicting load — it reacts to observed queue state.
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The TCP analogy is precise: our pipeline "bandwidth" is eval throughput. When extract produces faster than eval can consume, we need backpressure (slow extraction) or scale-up (more eval workers). AIMD handles this naturally.
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