Timothy Morano
November 21, 2024 21:12
Explore innovative solutions that optimize the Ethereum Virtual Machine (EVM) storage layer and address state bloat and high gas costs through advanced data structures and blockchain strategies.
The Ethereum Virtual Machine (EVM) is the cornerstone of blockchain technology responsible for managing persistent data, including smart contracts and accounts. But as blockchain networks scale, EVM’s storage layer faces serious challenges, including high gas costs and state inflation, Sei said.
EVM storage tiers and their limitations
The EVM’s storage layer is responsible for maintaining persistent data that remains after smart contract execution is complete. This layer includes several components such as program code, program storage, and machine state. However, EVM’s reliance on a modified Patricia Merkle Tree (MPT) for data storage increases computational complexity and gas cost, especially for write operations. As the blockchain state grows, nodes require more resources, making it difficult to participate in the network using standard hardware.
Exploring solutions to storage challenges in EVMs
The blockchain community is actively seeking solutions to address these issues. One approach is to use alternative data structures, such as Verkle Trees, which provide smaller proof sizes and faster verification. The Ethereum community is also exploring improvements through Ethereum Improvement Proposals (EIPs), such as EIP-2929 and EIP-2930, which optimize state access patterns and gas calculations.
Additionally, other blockchain platforms are experimenting with innovative storage models. Solana, for example, uses a flat account model that simplifies data access and improves transaction throughput. Reduce latency and optimize read operations by using memory-mapped accounting storage.
Other Blockchain Innovative Approaches
In addition to Ethereum, blockchains such as Solana and Sui are implementing new strategies to manage state efficiently. Solana’s flat account model and memory-mapped storage allows direct access to account data, eliminating the need for complex tree traversal. Meanwhile, Sui leverages an object-centric model using the Move programming language, which facilitates efficient serialization and parallel transaction processing.
Sei proposes to separate state commit and save, use MemIAVL for in-memory operations, and optimize state save for historical queries. This approach aims to reduce disk I/O and increase read speed, especially for consensus-related data.
conclusion
Challenges faced by the storage layer of EVMs, such as high gas costs and state bloat, require innovative solutions. The blockchain community can address these limitations and improve network scalability and efficiency by exploring new data structures, optimizing consensus operations, and implementing efficient storage technologies. As research continues, the potential for more scalable and decentralized blockchain infrastructure grows, promising an even stronger future for blockchain technology.
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