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Simulation: model validator gas costs to size ETH network fee for model trainers

Aperta
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#78 3 commenti 1 reazione 0 assegnatari Vedi su GitHub

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Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
25/100
Tipo di issue
Funzionalità
Chiarezza
Specificata chiaramente
Stato di attività
Attiva
Stack tecnologico
solidity
Ambito
blockchain, fintech-quant

Direzione di ricerca

The issue names the P3-5.2 simulation requirement and MECHANISM_DESIGN §5; start by reading those to find the existing validator income model and its assumptions. Model aggregation, evaluation, and worst-case dispute gas across the listed participation variables, using current Optimism gas prices. Report low, mid, and high scenario costs in ETH, the fee floor, sensitivity at 10× and 0.1× participation, and any unprofitable scenario.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Context

Discussed with @abrahamnash (Aug 2026). The resolved fee model is:

  • All protocol fees in ETH — DIN is staking/utility only, no fee denomination migration
  • Network fee (model trainer → validators, paid per-GI) must be sized from real gas data, not assumed
  • Current design has no hard numbers; this simulation is the prerequisite for setting the fee

The network fee is essentially gas recovery for validators: model trainers pay it upfront, validators get reimbursed for the on-chain work they do per GI. Getting this wrong in either direction (too low = validators lose money, too high = model owners won't participate) blocks the validator economics from being viable at scale.

Scope

Three scenarios to model, covering the full on-chain surface validators touch per GI:

1. Aggregation submissions
  • T1 sub-batch CID submission gas cost (per aggregator, per batch)
  • T2 combined CID submission gas cost
  • Baseline: aggregation logic is off-chain — only the final CID goes on-chain (per Abraham's design intent)
  • Variables: number of T1 batches, number of aggregators per batch
2. Evaluation submissions (batched vs per-round)
  • Gas cost of a single auditor submitting scores on-chain (setAuditScorenEligibility)
  • Batched final-round evaluation: all submissions in one round vs spread across rounds
  • Variables: number of clients per auditor, number of auditors per batch, pass/fail ratio
3. Dispute scenarios (worst-case)
  • Full dispute chain gas cost: dispute open → bond post → fresh subgroup reassignment → re-evaluation submissions → resolution
  • Disputes are rare by design (random assignment + >50% consensus threshold) — but worst-case must be bounded so it does not make the network fee unworkable
  • Variables: dispute window length, subgroup size

Expected output

  • Gas cost range (low/mid/high participation) for each scenario in ETH at current Optimism gas prices
  • Recommended ETH network fee floor that covers validator gas at target participation level
  • Sensitivity table: what happens to validator economics at 10× and 0.1× participation
  • Flag any scenario where gas costs alone make validator participation unprofitable at the proposed fee floor

Notes

  • Aligns with the existing P3-5.2 simulation requirement (validator income stability at target/10×/0.1× participation) — this scopes the gas input to that model
  • Builds on the mitigations already in the design: aggregation off-chain, evaluations batched to final round, disputes rare — the simulation should validate those mitigations hold under load
  • Reward split (clients/validators/treasury %) is a separate open item and out of scope here — see MECHANISM_DESIGN §5

cc @abrahamnash

Lingua principale
Python
Stelle
4
Fork
7
Merge medio
3g 58m
PR unite (30g)
39

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