Reimagining EVM Storage: Addressing Key Blockchain Challenges

The Ethereum Virtual Machine (EVM) is the cornerstone of blockchain technology, and is responsible for managing persistent data, including smart contracts and computations. However, as blockchain networks expand, EVM's storage layer faces significant challenges, including rising gas costs and state inflation, according to bad.

EVM storage layer and its limitations

The storage layer of the EVM is tasked with maintaining persistent data, which remains even after the smart contract has finished executing. This layer includes several components such as program code, program storage, and device state. However, EVM's reliance on the Modified Patricia Merkel Tree (MPT) for data storage leads to high computational complexity and gas costs, especially for write operations. As the blockchain state grows, nodes require more resources, making it difficult to participate in the network using standard hardware.

Explore solutions to EVM storage challenges

The blockchain community is actively looking for solutions to address these issues. One approach involves using 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 improve state access patterns and gas calculations.

In addition, other blockchain platforms are experimenting with innovative storage models. Solana, for example, uses a fixed compute model that simplifies data access and enhances transaction throughput. It uses memory-mapped computation storage to reduce access time and improve read operations.

Innovative approaches from other blockchains

Beyond Ethereum, blockchains like Solana and Sui are implementing new strategies for efficient state management. Solana's flat computation model and memory-mapped storage enable direct access to computation data, eliminating the need for complex tree traversals. Meanwhile, Sui leverages an object-centric model with the Move programming language, facilitating efficient serialization and parallel transaction processing.

Sei suggests separating state commit and storage, using MemIAVL for in-memory operations, and optimizing state storage for historical queries. This approach aims to reduce disk I/O and enhance read speeds, especially for consensus-bound data.

conclusion

The challenges faced by the EVM storage layer, such as high gas costs and case bloating, require innovative solutions. By exploring new data structures, improving consensus processes, and implementing efficient storage technologies, the blockchain community can address these limitations and enhance the network's scalability and efficiency. As research continues, the possibility of creating a more scalable and decentralized infrastructure grows, promising a more robust future for blockchain technology.

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