Sharded Automated Market Maker (SAMM): Scaling Decentralized Finance through Incentive-Compatible Parallelization

Conceptos Básicos

SAMM, a sharded automated market maker protocol, enables parallel execution of trades to overcome the throughput limitations of existing AMMs, while incentivizing desired behavior of traders and liquidity providers to maintain system stability.

Resumen

The paper presents SAMM, a sharded automated market maker (AMM) protocol, to address the throughput limitations of existing AMMs. Key highlights:

1. Existing AMMs are non-parallelizable, leading to performance bottlenecks as demand grows. The authors quantify this issue, showing that current blockchain systems like Sui and Solana cannot meet the projected AMM demand by 2029.

2. SAMM employs multiple independent AMM shards running in parallel on the same blockchain. To incentivize the desired behavior of traders and liquidity providers, SAMM introduces a novel trading fee function.

3. The authors model the system as a game and analyze the Subgame-Perfect Nash Equilibrium (SPNE). They prove that in SPNE, traders randomly select one of the smallest shards to trade, without splitting transactions, and liquidity providers balance liquidity across shards.

4. The authors implement and deploy SAMM on local testnets of Sui and Solana blockchains. SAMM achieves a 5x throughput increase in Sui and a 16x increase in Solana, compared to a single-contract AMM.

5. Simulations using real-world trade data confirm the effects of SAMM's incentive design, showing significant revenue improvements for liquidity providers with only a slight increase in traders' costs.

Estadísticas

The paper provides the following key metrics:

Existing AMMs are projected to reach over 200 transactions per second (tps) demand by 2029.
A single-contract AMM achieves 214 tps on Sui and 129 tps on Solana.
SAMM achieves a 5x throughput increase in Sui and a 16x increase in Solana, compared to a single-contract AMM.

Citas

"If the current trend continues, by 2029 demand would surpass 200 tps."
"SAMM improves throughput by 5x and 16x, respectively, potentially more with better parallelization of the underlying blockchains."

Ideas clave extraídas de

SAMM: Sharded Automated Market Maker

by Hongyin Chen... a las arxiv.org 09-11-2024

https://arxiv.org/pdf/2406.05568.pdf

Consultas más profundas

How can the SAMM protocol be extended to handle other types of decentralized finance applications beyond automated market makers?

The SAMM protocol, designed to enhance the throughput of Automated Market Makers (AMMs) through sharding and incentive compatibility, can be extended to other decentralized finance (DeFi) applications by adapting its core principles of parallel execution and incentive alignment.

Generalized Sharding Framework: The sharding mechanism employed in SAMM can be generalized to other DeFi applications such as lending platforms, yield farming, and decentralized exchanges. By creating independent shards for each application, the protocol can facilitate parallel processing of transactions, thereby improving overall system throughput.

Incentive Structures: The incentive-based approach used in SAMM can be tailored to different DeFi applications. For instance, in lending protocols, liquidity providers could be incentivized to distribute their assets across multiple shards to maximize their returns while minimizing risks. This could involve dynamic interest rates or rewards based on the liquidity distribution across shards.

Cross-Shard Interactions: To support applications that require interactions between different DeFi services, SAMM can implement cross-shard communication protocols. This would allow for seamless transactions between shards dedicated to different applications, enabling users to leverage multiple DeFi services without incurring significant overhead.

Customizable Fee Structures: The trading fee function in SAMM can be adapted for various DeFi applications. For example, in yield farming, the fee structure could be designed to reward users for locking their assets for longer periods, thus enhancing liquidity stability across shards.

Robust Governance Mechanisms: Extending SAMM to other DeFi applications would also require robust governance mechanisms to manage shard allocation, incentive adjustments, and protocol upgrades. Decentralized governance models could be employed to ensure that stakeholders have a say in the evolution of the protocol.

By leveraging these strategies, the SAMM protocol can effectively support a broader range of decentralized finance applications, enhancing their scalability and efficiency.

What are the potential security implications of the incentive-based approach used in SAMM, and how can they be further mitigated?

The incentive-based approach in SAMM, while designed to promote desired behaviors among liquidity providers and traders, introduces several potential security implications:

Incentive Misalignment: If the incentives are not carefully calibrated, liquidity providers may prioritize short-term gains over long-term stability, leading to imbalances across shards. This could result in some shards becoming underfunded, increasing slippage and reducing overall system efficiency.
Mitigation: Implementing dynamic incentive structures that adjust based on shard performance and liquidity levels can help align the interests of liquidity providers with the health of the entire system. Regular audits and performance reviews can also ensure that incentives remain effective.

Exploitation of Fee Structures: Traders may attempt to exploit the trading fee function by executing trades in a manner that minimizes their costs while maximizing slippage for others, potentially destabilizing the system.
Mitigation: Introducing transaction limits or slippage controls can help prevent such exploitation. Additionally, employing machine learning algorithms to monitor trading patterns and detect anomalies can provide real-time insights into potential manipulative behaviors.

Front-Running and Sandwich Attacks: The design of AMMs inherently exposes them to front-running and sandwich attacks, where malicious actors can exploit transaction ordering to their advantage.
Mitigation: Implementing privacy-preserving techniques, such as zero-knowledge proofs, can obscure transaction details until they are finalized, reducing the risk of front-running. Additionally, employing time-weighted average price (TWAP) mechanisms can help mitigate the impact of such attacks.

Shard Imbalance Attacks: Attackers could intentionally destabilize the system by withdrawing liquidity from certain shards, leading to imbalances that could be exploited.
Mitigation: SAMM can incorporate mechanisms to detect and respond to unusual liquidity withdrawals, such as requiring a minimum liquidity threshold for each shard. Additionally, incentivizing liquidity providers to maintain balanced contributions across shards can help prevent such attacks.

By addressing these security implications through proactive measures, the SAMM protocol can enhance its resilience against potential threats while maintaining its incentive-based framework.

What other blockchain design principles could be leveraged to overcome the serial execution bottleneck for "hot" smart contracts like AMMs?

To overcome the serial execution bottleneck for "hot" smart contracts like AMMs, several blockchain design principles can be leveraged:

Optimistic Concurrency Control: This principle allows multiple transactions to be processed simultaneously with the assumption that conflicts will be rare. If a conflict is detected, only the conflicting transactions are rolled back. This can significantly increase throughput for AMMs by allowing parallel processing of non-conflicting trades.

Layer-2 Solutions: Utilizing layer-2 scaling solutions, such as rollups or state channels, can offload some of the transaction processing from the main blockchain. This can reduce congestion and latency for AMMs, allowing for faster execution of trades without compromising security.

Asynchronous Execution: Implementing asynchronous transaction processing can allow smart contracts to handle multiple requests simultaneously. By decoupling transaction validation from execution, AMMs can process trades in parallel, improving overall throughput.

Dynamic Sharding: Beyond the static sharding approach used in SAMM, dynamic sharding can adaptively allocate resources based on current demand. This allows for more efficient use of blockchain resources, ensuring that "hot" contracts like AMMs have the necessary capacity during peak trading periods.

Transaction Batching: Grouping multiple transactions into a single batch can reduce the overhead associated with processing each transaction individually. This can be particularly effective for AMMs, where multiple trades can be executed in a single transaction, minimizing latency and maximizing throughput.

Cross-Chain Interoperability: Enabling cross-chain interactions can alleviate congestion on a single blockchain by distributing transaction loads across multiple chains. This can enhance the scalability of AMMs by allowing them to tap into liquidity and trading opportunities across different blockchain ecosystems.

By integrating these design principles, blockchain platforms can effectively address the serial execution bottleneck faced by "hot" smart contracts, enhancing their scalability and performance in the rapidly evolving DeFi landscape.