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@chainsafe/libp2p-gossipsub

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export function computeScoreWeights(peer, pstats, params, peerIPs, topicStrToLabel) { let score = 0; const byTopic = new Map(); // topic stores Object.entries(pstats.topics).forEach(([topic, tstats]) => { // the topic parameters // Aggregate by known topicLabel or throw to 'unknown'. This prevent too high cardinality const topicLabel = topicStrToLabel.get(topic) ?? 'unknown'; const topicParams = params.topics[topic]; if (topicParams === undefined) { // we are not scoring this topic return; } let topicScores = byTopic.get(topicLabel); if (topicScores == null) { topicScores = { p1w: 0, p2w: 0, p3w: 0, p3bw: 0, p4w: 0 }; byTopic.set(topicLabel, topicScores); } let p1w = 0; let p2w = 0; let p3w = 0; let p3bw = 0; let p4w = 0; // P1: time in Mesh if (tstats.inMesh) { const p1 = Math.max(tstats.meshTime / topicParams.timeInMeshQuantum, topicParams.timeInMeshCap); p1w += p1 * topicParams.timeInMeshWeight; } // P2: first message deliveries let p2 = tstats.firstMessageDeliveries; if (p2 > topicParams.firstMessageDeliveriesCap) { p2 = topicParams.firstMessageDeliveriesCap; } p2w += p2 * topicParams.firstMessageDeliveriesWeight; // P3: mesh message deliveries if (tstats.meshMessageDeliveriesActive && tstats.meshMessageDeliveries < topicParams.meshMessageDeliveriesThreshold) { const deficit = topicParams.meshMessageDeliveriesThreshold - tstats.meshMessageDeliveries; const p3 = deficit * deficit; p3w += p3 * topicParams.meshMessageDeliveriesWeight; } // P3b: // NOTE: the weight of P3b is negative (validated in validateTopicScoreParams) so this detracts const p3b = tstats.meshFailurePenalty; p3bw += p3b * topicParams.meshFailurePenaltyWeight; // P4: invalid messages // NOTE: the weight of P4 is negative (validated in validateTopicScoreParams) so this detracts const p4 = tstats.invalidMessageDeliveries * tstats.invalidMessageDeliveries; p4w += p4 * topicParams.invalidMessageDeliveriesWeight; // update score, mixing with topic weight score += (p1w + p2w + p3w + p3bw + p4w) * topicParams.topicWeight; topicScores.p1w += p1w; topicScores.p2w += p2w; topicScores.p3w += p3w; topicScores.p3bw += p3bw; topicScores.p4w += p4w; }); // apply the topic score cap, if any if (params.topicScoreCap > 0 && score > params.topicScoreCap) { score = params.topicScoreCap; // Proportionally apply cap to all individual contributions const capF = params.topicScoreCap / score; for (const ws of byTopic.values()) { ws.p1w *= capF; ws.p2w *= capF; ws.p3w *= capF; ws.p3bw *= capF; ws.p4w *= capF; } } let p5w = 0; let p6w = 0; let p7w = 0; // P5: application-specific score const p5 = params.appSpecificScore(peer); p5w += p5 * params.appSpecificWeight; // P6: IP colocation factor pstats.knownIPs.forEach((ip) => { if (params.IPColocationFactorWhitelist.has(ip)) { return; } // P6 has a cliff (IPColocationFactorThreshold) // It's only applied if at least that many peers are connected to us from that source IP addr. // It is quadratic, and the weight is negative (validated in validatePeerScoreParams) const peersInIP = peerIPs.get(ip); const numPeersInIP = (peersInIP != null) ? peersInIP.size : 0; if (numPeersInIP > params.IPColocationFactorThreshold) { const surplus = numPeersInIP - params.IPColocationFactorThreshold; const p6 = surplus * surplus; p6w += p6 * params.IPColocationFactorWeight; } }); // P7: behavioural pattern penalty const p7 = pstats.behaviourPenalty * pstats.behaviourPenalty; p7w += p7 * params.behaviourPenaltyWeight; score += p5w + p6w + p7w; return { byTopic, p5w, p6w, p7w, score }; } export function computeAllPeersScoreWeights(peerIdStrs, peerStats, params, peerIPs, topicStrToLabel) { const sw = { byTopic: new Map(), p5w: [], p6w: [], p7w: [], score: [] }; for (const peerIdStr of peerIdStrs) { const pstats = peerStats.get(peerIdStr); if (pstats != null) { const swPeer = computeScoreWeights(peerIdStr, pstats, params, peerIPs, topicStrToLabel); for (const [topic, swPeerTopic] of swPeer.byTopic) { let swTopic = sw.byTopic.get(topic); if (swTopic == null) { swTopic = { p1w: [], p2w: [], p3w: [], p3bw: [], p4w: [] }; sw.byTopic.set(topic, swTopic); } swTopic.p1w.push(swPeerTopic.p1w); swTopic.p2w.push(swPeerTopic.p2w); swTopic.p3w.push(swPeerTopic.p3w); swTopic.p3bw.push(swPeerTopic.p3bw); swTopic.p4w.push(swPeerTopic.p4w); } sw.p5w.push(swPeer.p5w); sw.p6w.push(swPeer.p6w); sw.p7w.push(swPeer.p7w); sw.score.push(swPeer.score); } else { sw.p5w.push(0); sw.p6w.push(0); sw.p7w.push(0); sw.score.push(0); } } return sw; } //# sourceMappingURL=scoreMetrics.js.map