Design: TollGate capacity advertisement vs client measurement + reputation model
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Valutazione
- Difficoltà
- 5/5
- Tempo stimato
- Più di una settimana
- Idoneità per principianti
- 25/100
- Tipo di issue
- Funzionalità
- Chiarezza
- Da chiarire
- Stato di attività
- Tranquilla
- Stack tecnologico
- go
- Ambito
- backend-api-design, networking
Direzione di ricerca
Start by reading the UpstreamManager, which the issue says already tracks bytes transferred during active sessions, and review #312 for the related discovery logger work. The issue leaves key decisions open about capacity measurement, reputation signals, and storage, so first clarify and agree on those choices. Done means an agreed design for how measurements and reputation will be collected and used.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Descrizione
Open Questions
1. Self-advertised capacity vs client-measured
Should a TollGate self-report its uplink speed, or should the client measure it?
Self-advertised (push model):
- TollGate includes
uplink_speed_mbpsin itsGET /advertisement response - Pro: client knows before committing to a connection
- Con: nothing prevents lying — a TollGate could claim 100 Mbps on a 5 Mbps DSL line
- Mitigation: client verifies after connecting and adjusts trust
Client-measured (pull model):
- Client does a timed download from the TollGate backend after connecting
- Pro: ground truth, can't be faked
- Con: only available AFTER connection (too late for pre-connection scoring)
- Con: small downloads are inaccurate for high-bandwidth links
Hybrid (likely best):
- TollGate advertises expected capacity (from config or self-test)
- Client measures actual throughput after connecting
- Discrepancy logged → feeds reputation score
- Future scoring weights measured > advertised
2. TollGate reputation
How do we track whether a TollGate is trustworthy and performs well?
Signals to collect:
- Price accuracy: advertised price vs actual charge per step
- Throughput delivery: advertised speed vs measured speed (ratio)
- Uptime: what fraction of probes succeeded over time?
- Payment reliability: did Cashu tokens work? Any meltdowns/errors?
- Session stability: did sessions get cut prematurely?
Storage options:
- Local JSONL per-TollGate (by npub) — simple, no infrastructure
- Nostr reputation event (kind 1984 or custom) — shared across the network
- Stake-based: TollGates lock sats as collateral, slashed for bad behavior
Trust bootstrapping:
- New TollGate starts at neutral reputation (score 0)
- Reputation accrues from client measurements over time
- Social trust: follow npubs of known operators (profit_share identities)
- Network effects: TollGates recommended by trusted TollGates get a boost
3. Measurement methodology
If we measure throughput from the client side:
- HTTP GET to
/: Already exists, returns advertisement (~500 bytes). Too small for throughput estimation. - Timed file download: Would need a dedicated endpoint serving a known-size payload (e.g.,
/speedtest?size=1000000). More accurate but adds backend complexity. - iperf3: Most accurate but requires installation on every TollGate.
- Ongoing session throughput: The UpstreamManager already tracks bytes transferred during active sessions. This is "free" data — no extra probes needed. The session manager knows exactly how many bytes flowed through per second.
Proposal: Use ongoing session bytes/second as the primary throughput signal. The session manager already measures this for data-metered sessions. We just need to log it alongside the TollGate identity.
Related
- #311 — WiFi AP selection algorithm roadmap
- #312 — Discovery logger (Phase 1-2 implementation)
- Lingua principale
- Go
- Stelle
- 12
- Fork
- 14
- Merge medio
- 1g 6h
- PR unite (30g)
- 217
Preparare l'ambiente
- Nessun Dockerfile né file Docker Compose
- Nessun modello di pull request
- Leggi la guida per i contributori
Come iniziare
- Leggi tutta la issue e poi la guida ai contributi del progetto.
- Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
- Fai un fork del repository e lavora su un branch.
- Apri una pull request che faccia riferimento al numero della issue.
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