Concept Proposal: Dynamic Fee Adjustment on Algorand via Oracles
1. Introduction
1.1 Problem Summary
Currently, the Algorand blockchain uses a fixed transaction fee of 0.001 ALGO. This fee does not adjust based on ALGO’s market price. If ALGO’s price were to skyrocket (e.g., $1,000+), transaction costs could become prohibitively high.
1.2 Proposal Goal
We propose implementing a dynamic fee model that automatically adjusts transaction costs based on ALGO’s real-time value, ensuring efficiency and decentralization.
2. Proposed Solution
2.1 Utilizing Oracles
Instead of a fixed fee, Algorand would use Oracle price feeds to determine the average market price of ALGO based on data from DEX and CEX sources.
2.1.1 Data Sources
- Decentralized Exchanges (DEX): Tinyman, Pact, HumbleSwap, AlgoFi DEX.
- Centralized Exchanges (CEX): Binance, Coinbase, Kraken, OKX, KuCoin.
- Market Aggregators: CoinGecko, CoinMarketCap, Messari.
- Algorand-based Oracles: Algoracle, TEAL ALGO Oracle (currently supported on Algorand), potentially Chainlink (if integrated).
2.2 Dynamic Fee Calculation
Transaction fees would automatically adjust based on a moving average price of ALGO:
- ALGO < $10 → Fee remains 0.001 ALGO.
- ALGO $10 - $999 → Fee gradually decreases.
- ALGO $1000+ → Fee drops to 0.00001 ALGO.
- ALGO $70,000+ → Fee drops to 0.0000001 ALGO.
2.3 Transparency & Decentralization
- Fee calculations occur on-chain in a smart contract.
- Data is publicly available and verifiable.
- Utilizing multiple Oracle sources prevents price manipulation.
3. Implementation Details
3.1 Protocol Requirements
- Integration of Oracles into Algorand smart contracts.
- Algorand SDK must support dynamic fee adjustments.
- Utilization of TEAL ALGO Oracle, which already exists on Algorand, for connecting with price feeds.
3.2 Security Considerations
- Use of average pricing to prevent manipulation.
- Cross-checking data from multiple exchanges.
4. Conclusion
This mechanism ensures that Algorand remains efficient and affordable even as ALGO’s price surges, without requiring manual intervention.