Fee Structure

zkSync’s fee structure is designed to optimize costs while ensuring high security and efficiency. The fees are composed of a few components:

1. L1 Data Costs: This cost is associated with the data published on Ethereum Layer 1 (L1). Since zkSync relies on the Ethereum mainnet for data availability and security, the gas cost for publishing calldata on L1 is a significant part of the fee structure. The volatile nature of L1 gas prices means this cost can fluctuate.
2. L2 Gas Costs: These are the computational costs on zkSync’s Layer 2 (L2). Unlike Ethereum, zkSync uses zero-knowledge proofs to validate transactions, which affects the pricing of operations. For example, certain operations like keccak256, which are optimized for CPU performance, are more expensive to prove in zkSync.
3. Proof Generation Costs: Generating zk-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) proofs requires substantial computational resources. These costs are factored into transaction fees to ensure the integrity and security of the zkRollup.
4. Storage Costs: zkSync employs a mechanism similar to Ethereum’s “warm” and “cold” storage slots. Users are initially charged for the maximum (cold) cost, with refunds provided for accessing “warm” slots. This ensures users always have enough gas for worst-case scenarios while optimizing storage costs.

Comparison with Ethereum Mainnet Fees

zkSync offers significant cost savings compared to the Ethereum mainnet. By processing transactions off-chain and submitting only succinct proofs to L1, zkSync reduces the gas required for each transaction. Typically, zkSync users experience fees that are a fraction of those on Ethereum, making it an attractive option for high-frequency and microtransactions.

Cost Efficiency

Mechanisms for Reducing Costs

zkSync employs several mechanisms to reduce transaction costs:

1. Batch Processing: Transactions are aggregated into batches before being processed. This approach minimizes the number of interactions with L1, significantly lowering the associated costs. By submitting a single proof for multiple transactions, zkSync maximizes efficiency and reduces fees.
2. Optimized Data Storage: zkSync utilizes a post-charging model for storage costs, which separates the gas used for execution from the gas used for data availability. This ensures that users are only charged for the actual data published, minimizing unnecessary overhead.
3. Scalable Proof Systems: zkSync uses scalable proof systems like PLONK and RedShift, which are designed to handle high transaction volumes efficiently. These systems help manage the computational costs of generating proofs, keeping fees low even as transaction volumes increase.

Examples of Cost Savings in Real-World Applications

zkSync’s cost efficiency has enabled various applications to operate more economically:

• Decentralized Exchanges (DEXs): Platforms like Uniswap use zkSync to offer lower trading fees, making frequent trading more affordable for users.
• NFT Marketplaces: NFT platforms benefit from reduced minting and transaction fees, allowing artists and collectors to engage in the ecosystem without the high costs of Ethereum mainnet transactions.
• DeFi Protocols: Lending and borrowing platforms utilize zkSync to provide financial services with lower transaction fees, enhancing accessibility and user engagement.

Planned Updates and Changes to the Fee Model

zkSync is continuously evolving its fee model to ensure long-term sustainability and efficiency. Some of the planned updates include:

1. Dynamic Pricing Mechanisms: Future fee models will incorporate dynamic pricing that adjusts based on real-time network conditions and L1 gas prices. This approach aims to maintain fair and predictable fees while balancing cost and performance.
2. Enhanced Decentralization: zkSync plans to decentralize the fee determination process, reducing reliance on centralized operators. This shift will involve community governance and automated systems to set and adjust fees, ensuring a more democratic and resilient ecosystem.
3. Improved Data Compression: Enhancements in data compression techniques are expected to further reduce the amount of data that needs to be published on L1, lowering costs for users.

Long-Term Sustainability

The long-term sustainability of zkSync’s fee model is based on several strategies:

• Efficient Proof Systems: Continuous improvements in proof systems will enable zkSync to handle increasing transaction volumes without proportional increases in costs.
• Incentivized Participation: zkSync’s economic model incentivizes validators and users to participate actively, creating an ecosystem that supports low-cost operations.
• Community Governance: Decentralized governance helps maintain and optimize the fee structure, ensuring it adapts to changing network dynamics and user needs.

zkSync’s fee structure is designed to provide a scalable, cost-efficient solution for Ethereum transactions. Through innovative mechanisms like batch processing and optimized data storage, zkSync offers significant cost savings compared to the Ethereum mainnet. The continuous evolution of the fee model, including plans for dynamic pricing and enhanced decentralization, ensures long-term sustainability and efficiency. By leveraging advanced cryptographic techniques and community governance, zkSync aims to offer low-cost, high-performance blockchain solutions that are sustainable and resilient.

Highlights

• Fee Structure: zkSync’s fees consist of L1 data costs, L2 gas costs, proof generation costs, and storage costs, optimized for lower transaction costs compared to Ethereum mainnet.
• Cost Efficiency: Mechanisms like batch processing, optimized data storage, and scalable proof systems help reduce transaction costs, making frequent and microtransactions more affordable.
• Real-World Savings: Applications like decentralized exchanges, NFT marketplaces, and DeFi protocols benefit from significantly lower fees, enhancing user engagement and accessibility.
• Future Fee Models: Planned updates include dynamic pricing, enhanced decentralization of fee determination, and improved data compression to maintain fair and predictable fees.
• Long-Term Sustainability: Strategies for sustainability include continuous improvement of proof systems, incentivized participation, and community-driven governance to adapt to network dynamics and user needs.