Current Transaction Processing Capacity of the Ethereum Blockchain: The Ethereum blockchain currently processes approximately 20 transactions per second for regular transactions and can reach up to 60 transactions per second for very small and minimally sized transactions. Calculating the annual capacity based on this, the blockchain can support around 630 million transactions per year.
Importance of Increasing Scalability: Scalability is crucial for Ethereum to handle mainstream applications, such as payments and gaming, which require a much higher transaction processing capacity. Current transaction rates are sufficient for limited use cases, such as registering and updating domain names, but not for broader adoption. Payment processors often have TPS (transactions per second) numbers ranging from 1,000 to 100,000, and some even reach up to a million. Non-financial applications and gaming also demand higher TPS rates.
Scaling Ethereum: Vitalik Buterin emphasizes the importance of scaling Ethereum to reduce transaction fees, enabling broader applications beyond large-scale financial use cases.
Rollup-Centric Roadmap: The Ethereum Rollup-Centric Roadmap proposes a separation of layers, where the base layer provides secure data storage space, and layer two projects build on top for scalability and speed.
Base Layer’s Role: The base layer’s primary focus is to provide open, decentralized, censorship-resistant, and secure storage space for transactions and roll-up data.
Layer Two Projects: Layer two projects, such as roll-ups, utilize the base layer’s data space to process a larger volume of transactions, providing scalability and faster transaction processing.
Availability Guarantees: The base chain offers availability guarantees, ensuring that transactions and data stored on the chain remain accessible and verifiable over time.
Optimizing Data Space: Optimizing the data space involves increasing the base chain’s capacity for storing and processing data and minimizing the data size of each transaction.
00:05:54 Understanding and Optimizing Rollup Data Efficiency on the Ethereum Blockchain
Roll-up Data Competition and Space Constraints: Roll-ups compete with existing transactions and applications for block space. Limited space availability for roll-ups leads to high costs and small data portions on-chain.
Proto-Dank Sharding (EIP-4844): Introduces a new transaction type for storing large blobs of data (128 kilobytes). Enables roll-ups to include data for numerous transactions in each blob. Future iterations aim to increase data capacity beyond 16 megabytes.
Full-Dank Sharding: Expands proto-dank sharding to allow for a much larger amount of data on-chain. Utilizes cryptographic mechanisms to minimize individual node storage requirements.
Reducing Data per Transaction: Uncompressed ERC-20 token transfers require 180 bytes of on-chain data. Roll-ups copying Ethereum’s logic need 180 bytes per transaction. Gain in efficiency compared to Ethereum directly is significant but insufficient long-term.
Compression Techniques: Zero-byte compression reduces ERC-20 token transfer data to 154 bytes. Mainstream compression algorithms further reduce data size.
Signature Aggregation: Signatures are cryptographic random data and not easily compressible. Signature aggregation replaces individual signatures with a single cryptographic proof. BLS aggregation and “making a snark” are two methods for signature aggregation.
Potential Data Reduction: Signature aggregation can reduce data to 128 bytes. Theoretically optimal, ideal, stateless compression can further reduce data size.
00:12:07 Advanced Compression Techniques for Improving Rollup Efficiency
Special Purpose Compression: Vitalik Buterin emphasizes that the compression algorithm used for Ethereum ERC20 transfers is not general-purpose but specifically designed for this use case. The algorithm employs various tricks to minimize the size of the compressed data. For example, it might have a specific representation for whole numbers of guay, reducing the size of the fee field.
Ideal Stateful Compression: Ideal stateful compression goes beyond regular compression by incorporating the history of the blockchain. It replaces addresses with pointers to their last occurrence, further reducing the size of the compressed data. This approach can reduce the size of Ethereum transactions by a factor of eight, improving rollups’ efficiency from 20x to 160x.
Special Purpose ZK Roll-ups: Special purpose ZK roll-ups, like Loopring, have had ideal stateful compression for over a year, resulting in 16-byte transactions. However, the challenge lies in combining the benefits of special purpose roll-ups with the existing general-purpose EVM.
Challenges in Scaling: Vitalik Buterin highlights that the technical problems in scaling have already been solved. The current focus is on the hard work of making fancy scaling and the existing EVM work together.
00:14:32 Ethereum Scalability Solutions: Data Availability Sampling and Its Limits
Protodink Sharding: Protodink sharding introduces data transactions, which contain an additional object called a data blob. Data blobs can store various types of data, such as application data, images, or transaction data used by rollups.
Full Dink Sharding: Full dink sharding involves data availability sampling, where nodes randomly verify a few chunks of every data blob instead of downloading all the data. This cryptographic self-repair property ensures that if more than half of the blob is available, the entire blob can be reconstructed.
Limits to Data Availability Sampling: Data availability sampling is a collaborative verification protocol that depends on multiple participants to ensure data availability. The number of clients required for safe data availability sampling increases with the amount of data being transmitted. With larger block sizes, the number of clients required for sampling becomes impractical.
Network Congestion: Network congestion can occur when many clients simultaneously request data from a single source. This can lead to delays in data retrieval and potential network instability.
Scalability Challenges: Achieving scalability requires addressing both data availability and network congestion issues. Finding a balance between security and scalability remains a significant challenge.
Ongoing Research and Development: Research is ongoing to develop new sharding techniques and data availability sampling methods to improve scalability. The Ethereum community is actively working on solutions to address these challenges and enhance the network’s scalability.
EIP-4444 and Long-Term Storage Limits: EIP-4444 aims to separate the role of a consensus node from the responsibility of storing the blockchain’s history. This allows for more efficient storage solutions while ensuring that the blockchain’s history remains accessible. Storing the entire blockchain history becomes increasingly challenging as scalability increases, requiring significant storage capacity and potentially becoming impractical for individual hobbyists.
Scalability Limits: Ethereum faces two primary limits to scalability: Consensus node requirements: As the number of transactions per second increases, more validators are needed to maintain network security, requiring increased computational resources. Long-term storage: Maintaining the blockchain’s history requires significant storage space, becoming a challenge as the blockchain grows.
Post-Rollup World Considerations: After implementing rollups, different blockchain operations will have varying costs: Reading and writing to the state will become more affordable. Computation on-chain will become less expensive, especially if data is not costly. ZK rollups will make snark-unfriendly computations more expensive, while computation itself will be cheaper. Application design may need to adapt to these changes in resource costs.
Key EIPs for Scaling: EIP-4844: Proto-DANK sharding, introducing more space on-chain. ERC-4337: Account abstraction, allowing Ethereum accounts on roll-ups and Layer 1 to benefit from data-saving techniques like BLS aggregation. EIP-4444: Separates consensus node responsibilities from history storage, enabling more efficient storage solutions.
Scalability Improvements: To enhance scalability, the blockchain is being designed to accommodate additional data without burdening regular nodes.
Ongoing Progress: Dedicated teams are actively working to implement these scalability improvements.
Expected Outcomes: The blockchain will become more accessible, scalable, and cost-effective.
Abstract
Scalability as the Crucial Frontier for Ethereum’s Future
Ethereum’s Race to Scalability: Innovations and Challenges in Blockchain Expansion
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In the dynamic landscape of blockchain technology, Ethereum stands at a pivotal crossroads, where enhancing scalability emerges as its top priority. Faced with a transaction processing capacity significantly lower than mainstream payment processors and the increasing demands of diverse applications, Ethereum’s quest for scalability is characterized by a series of ambitious strategies and technological innovations. These include advanced compression techniques, the proto-dank sharding (EIP-4844), and a rollup-centric roadmap, all aimed at accommodating a broader range of use cases, from regular payments to gaming, while ensuring security and efficiency. This article delves into the intricacies of Ethereum’s scalability efforts, highlighting key developments, their benefits, limitations, and the ongoing quest to integrate these advancements with the Ethereum Virtual Machine (EVM).
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Scalability as Top Priority
Post-merge, Ethereum is concentrating on improving its blockchain scalability. Presently, it manages up to 20 transactions per second (TPS) for standard transactions, and this can increase to 60 TPS for smaller transactions, culminating in an annual capacity of around 630 million transactions. While this capacity serves specific applications such as yearly domain name registrations, it falls short compared to mainstream payment processors handling 1,000 to 10,000 TPS, with some reaching up to a million. This significant discrepancy highlights Ethereum’s pressing need to boost its scalability to support a wider array of applications, including payment processing and gaming. Despite being adequate for certain limited use cases like domain name registrations, the current transaction rates are insufficient for broader adoption. Payment processors and non-financial applications like gaming demand much higher TPS rates, thus underscoring the importance of Ethereum enhancing its scalability.
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Scaling Ethereum: Strategies and Roadmaps
Vitalik Buterin, a prominent figure in Ethereum, is focusing on scaling the platform to lower transaction fees and foster broader adoption, especially for small payments and daily use. Ethereum’s scaling approach involves a rollup-centric roadmap that allocates scaling responsibilities between its base layer and layer two projects. The base layer is tasked with providing a secure data space for transactions and roll-ups, maintaining decentralization and security, whereas layer two projects utilize this data space to achieve scalability. Rollups, acting as a secondary chain within the main chain, leverage the base chain’s data space to store transaction data, thus increasing transaction capacity.
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Proto-Dank Sharding and Compression Techniques
Proto-dank sharding, or EIP-4844, is introducing a novel transaction type that can store large data blobs, each up to 128 kilobytes, enabling the processing of numerous transactions within a single blob. This method is a precursor to full-dank sharding, which aims to handle up to 16 megabytes of data per blob. Compression techniques are vital in this process, including zero-byte compression, BLS signature aggregation, and stateless compression, all of which are designed to reduce on-chain data requirements. However, these techniques add complexity and potential security risks, necessitating a careful balance between efficiency and security.
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Specialized Compression and EVM Compatibility
Ethereum is exploring special purpose compression algorithms, specifically designed for Ethereum ERC20 transfers, and ideal stateful compression that uses historical blockchain data. These techniques greatly reduce the size of compressed data but pose challenges in compatibility with the Ethereum Virtual Machine (EVM). Efforts are ongoing to harmonize the efficiency of these specialized compression methods with the versatility of the EVM.
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Ongoing Developments and Data Transactions
Ethereum’s current focus is on integrating advanced techniques with the EVM to offer scalable solutions without compromising user and developer needs. The introduction of protodink sharding and its data transactions, which include data blobs capable of holding various types of data, is a critical aspect of this integration. Challenges like data availability and network congestion need to be addressed to achieve true scalability. Research continues on developing new sharding techniques and data availability sampling methods to enhance the network’s scalability, with the Ethereum community actively seeking solutions.
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Scalability Limits and EIP4444
As blockchain technology scales, the need for more consensus nodes creates practical limits on scalability. EIP4444 addresses these challenges by distinguishing the roles of consensus and storage nodes, enabling validators to forgo storing the entire blockchain history. This separation, along with decentralized storage protocols, lightens the load on individual nodes. Ethereum faces scalability limits due to the requirements of consensus nodes and the challenges of long-term storage. The post-rollup world will see varying costs for different blockchain operations, and application design may need to adapt to these changing resource costs. Key EIPs for scaling include EIP-4844 for Proto-DANK sharding, ERC-4337 for account abstraction, and EIP-4444 for separating consensus node responsibilities from history storage.
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Conclusion
Ethereum’s journey towards enhanced scalability is marked by a complex mix of technological innovations, strategic planning, and practical considerations. Its ability to adapt and evolve will be critical in determining its role and relevance in the ever-expanding blockchain technology landscape. The blockchain is being designed to handle additional data efficiently, and dedicated teams are actively working on implementing these scalability improvements. The expected outcomes are a more accessible, scalable, and cost-effective blockchain.
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