Incentive Distribution Logic
🎯 Incentive Distribution Logic
A decentralized system is only as strong as its incentives. SZNP introduces a modular, performance-based incentive model to fairly distribute $SZNP tokens across the ecosystem — rewarding actual contribution, uptime, accuracy, and utility, not just passive participation.
⚙️ Incentive Participants
🗄 Node Operators
Store & retrieve fragmented data
Storage + retrieval rewards
🤖 AI Agents
Perform analysis, tagging, inference
Task-based rewards
📡 DePIN Devices
Upload real-world sensor or compute data
Streaming micropayments
👥 Governance Voters
Propose, audit, or vote on proposals
Governance incentives
🧪 Builders / Devs
Build tools, dApps, or integrations
Grants + ecosystem bonuses
🧠 Dynamic Reward Allocation (DRA)
SZNP uses a Dynamic Reward Allocation (DRA) system that adjusts rewards based on:
📈 Performance metrics (latency, accuracy, uptime)
📊 Data utility scores (measured via usage frequency or AI classification)
🧠 Task complexity (e.g., a multi-label ML task gets more than a binary tag)
🔒 Staking weight (stakers earn multiplier bonuses based on locked duration)
All reward calculations are executed on-chain via verifiable logic, with automatic settlement every epoch (e.g., daily or weekly).
🔄 Reward Flow & Token Sink Model
SZNP’s incentive cycle avoids inflationary leakage by incorporating:
🧾 Usage-based token burn: A % of storage & retrieval fees are burned
🌀 Restaking loops: Rewards must be restaked for full bonus eligibility
⚖️ Slashing & penalties: Poor-performing nodes lose a portion of rewards
🧰 Dev grant pool: A fixed % goes to community-funded innovation
🧬 Example Flow
A user uploads a 1GB AI training dataset →
4 storage nodes shard & store it →
An AI agent classifies its domain for tagging →
Retrieval occurs 20x in a week from DeSci labs →
All parties are rewarded based on measured impact
SZNP’s reward engine doesn’t just pay for uptime — it funds a living, intelligent, decentralized ecosystem.
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