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Starknet Plans to Boost Efficiency and Lower Costs Through Parallel Transactions in 2024

Mar 20, 2024 at 05:10

Starknet, a leading Ethereum scaling protocol, aims to enhance throughput and decrease transaction fees with the integration of parallel transaction processing in 2024.

Following the successful implementation of Ethereum’s Dencun hard fork, Starknet unveiled an updated roadmap on March 20. This upgrade introduced several Ethereum Improvement Proposals (EIPs), with EIP-4844 being the focal point.

EIP-4844 revolutionizes the way rollups add data to blocks by introducing blob space as a cost-effective alternative to using call data for storage. Traditionally, storing cryptographic proofs of off-chain bundled transactions via call data incurred high expenses due to the perpetual on-chain data processing required by all Ethereum nodes.

Promptly after the Dencun hard fork, Starknet and other prominent Ethereum rollups swiftly adopted the blob function, witnessing a significant reduction in users’ transaction fees mere hours later.

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With Starknet’s EIP-4844 compatibility, transaction fees on the protocol averaged $0.017 per transaction. Earlier in 2024, the team had already increased the block size and reduced fees by approximately 25% with the release of Starknet v0.13.0.

The upcoming version update slated for the second quarter of 2024 will introduce transaction parallelization, enabling Starknet to execute multiple independent transactions concurrently. This enhancement is expected to elevate throughput and expedite transaction finality.

Furthermore, Starknet plans to further alleviate fees with the release of version 0.14.0 by the year’s end. This update will focus on data availability, with features like Volition facilitating hybrid data storage on Starknet and application recursion streamlining data storage proofs onto Ethereum.

Moreover, data availability compression aims to minimize Starknet’s data footprint on Ethereum, with the protocol exploring various recursion methods to implement this functionality effectively.

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