Table of Links Abstract and 1. Introduction 1.1 Research Questions and Contributions Related Work


Background


Inscriptions and ordinals
4.1 Operation Types
4.2 Comparison with NFTs and ERC-20s


Data Collection


Empirical Analysis and 6.1 Overall Transactions
6.2 Inscriptions Characterization
6.3 Inscription Trading
6.4 Impact on Gas Fees


Discussion


Conclusion and References 3 Background Scalability challenges and gas price fluctuations in blockchain networks are typically addressed through two primary approaches: Layer-1 (L1) and Layer-2 (L2). Layer-1 is the foundational layer for blockchains, while Layer-2 is a secondary layer that provides scalability and relies on Layer-1 for security. This also introduces rollups, a type of non-custodial Layer-2 blockchain, and provides the necessary background for this paper. Layer-1 scaling (L1). This approach involves creating an entirely new blockchain with unique consensus mechanisms and dedicated physical infrastructure to maintain network consensus. Notable L1 blockchains include Bitcoin, Ethereum, Solana, Avalanche, and Polkadot. L1 blockchains typically prioritize decentralization and security, often at the expense of scalability. To address this limitation, L2-rollup solutions were proposed to help scale L1 blockchains. Layer-2 scaling (L2). In contrast, L2 scaling adopts a different strategy. It involves executing computations outside the main (L1) blockchain and then recording the results or final state on the underlying chain. Major types of L2 solutions include state (payment) channels, plasma, and rollups. Plasma and state channels focus on moving both data and computation off-chain. Rollups, on the other hand, move computation and state storage off-chain while retaining compressed data for each transaction on the underlying chain. Rollups. They function as a form of L2 scaling by conducting computations off-chain and storing the results on the main chain. Essentially, they operate like blockchains, generating blocks and then recording batches of these blocks on the primary chain. However, in the rollup environment, operators are not inherently trusted. This lack of trust means that operators could potentially behave maliciously by halting block production, generating invalid blocks, withholding data, or engaging in other adversarial activities. To mitigate these risks, rollups typically implement robust security measures to ensure the integrity and security of the system. In that regard, ensuring the correctness of the state in rollups involves two main approaches: optimistic and zero-knowledge proofs (ZKP). Some rollups, such as zkSync Era, employ ZKP, which involve computing cryptographic proofs to validate the correctness of the computations. On the other hand, rollups like Arbitrum and Optimism adopt an optimistic approach, which assumes all statements are true unless someone in the network contests them. Figure 1 illustrates a rollup architecture, highlighting key components such as sequencers and verifiers. Sequencers. These entities are responsible for aggregating transactions and rolling them up to the L1 chain. By bundling transactions, rollups effectively achieve cost savings in terms of gas fees. Verifiers. Operating as smart contracts on the L1 chain, verifiers play a crucial role in validating the transactions stored by the sequencer. They ensure the correctness of the transactions, thereby maintaining the integrity of the overall system [31, 41, 14]. Authors:
(1) Johnnatan Messias, Matter Labs;
(2) Krzysztof Gogol, Matter Labs, University of Zurich;
(3) Maria Inês, Silva Matter Labs;
(4) Benjamin Livshits, Matter Labs, Imperial College London. This paper is available on arxiv under CC BY 4.0 DEED license. Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 1.1 Research Questions and Contributions 1.1 Research Questions and Contributions Related Work Background Inscriptions and ordinals
4.1 Operation Types
4.2 Comparison with NFTs and ERC-20s Data Collection Empirical Analysis and 6.1 Overall Transactions
6.2 Inscriptions Characterization
6.3 Inscription Trading
6.4 Impact on Gas Fees Discussion Conclusion and References Related Work Related Work Related Work Background Background Background Inscriptions and ordinals 4.1 Operation Types 4.2 Comparison with NFTs and ERC-20s Inscriptions and ordinals Inscriptions and ordinals 4.1 Operation Types 4.1 Operation Types 4.2 Comparison with NFTs and ERC-20s 4.2 Comparison with NFTs and ERC-20s Data Collection Data Collection Data Collection Empirical Analysis and 6.1 Overall Transactions 6.2 Inscriptions Characterization 6.3 Inscription Trading 6.4 Impact on Gas Fees Empirical Analysis and 6.1 Overall Transactions Empirical Analysis and 6.1 Overall Transactions 6.2 Inscriptions Characterization 6.2 Inscriptions Characterization 6.3 Inscription Trading 6.3 Inscription Trading 6.4 Impact on Gas Fees 6.4 Impact on Gas Fees Discussion Discussion Discussion Conclusion and References Conclusion and References Conclusion and References 3 Background Scalability challenges and gas price fluctuations in blockchain networks are typically addressed through two primary approaches: Layer-1 (L1) and Layer-2 (L2). Layer-1 is the foundational layer for blockchains, while Layer-2 is a secondary layer that provides scalability and relies on Layer-1 for security. This also introduces rollups, a type of non-custodial Layer-2 blockchain, and provides the necessary background for this paper. Layer-1 scaling (L1). This approach involves creating an entirely new blockchain with unique consensus mechanisms and dedicated physical infrastructure to maintain network consensus. Notable L1 blockchains include Bitcoin, Ethereum, Solana, Avalanche, and Polkadot. L1 blockchains typically prioritize decentralization and security, often at the expense of scalability. To address this limitation, L2-rollup solutions were proposed to help scale L1 blockchains. Layer-1 scaling (L1). Layer-1 scaling (L1). Layer-2 scaling (L2). In contrast, L2 scaling adopts a different strategy. It involves executing computations outside the main (L1) blockchain and then recording the results or final state on the underlying chain. Major types of L2 solutions include state (payment) channels, plasma, and rollups. Plasma and state channels focus on moving both data and computation off-chain. Rollups, on the other hand, move computation and state storage off-chain while retaining compressed data for each transaction on the underlying chain. Layer-2 scaling (L2). Layer-2 scaling (L2). Rollups . They function as a form of L2 scaling by conducting computations off-chain and storing the results on the main chain. Essentially, they operate like blockchains, generating blocks and then recording batches of these blocks on the primary chain. However, in the Rollups Rollups rollup environment, operators are not inherently trusted. This lack of trust means that operators could potentially behave maliciously by halting block production, generating invalid blocks, withholding data, or engaging in other adversarial activities. To mitigate these risks, rollups typically implement robust security measures to ensure the integrity and security of the system. In that regard, ensuring the correctness of the state in rollups involves two main approaches: optimistic and zero-knowledge proofs (ZKP). Some rollups, such as zkSync Era, employ ZKP, which involve computing cryptographic proofs to validate the correctness of the computations. On the other hand, rollups like Arbitrum and Optimism adopt an optimistic approach, which assumes all statements are true unless someone in the network contests them. Figure 1 illustrates a rollup architecture, highlighting key components such as sequencers and verifiers . sequencers verifiers Sequencers . These entities are responsible for aggregating transactions and rolling them up to the L1 chain. By bundling transactions, rollups effectively achieve cost savings in terms of gas fees. Sequencers Sequencers Verifiers . Operating as smart contracts on the L1 chain, verifiers play a crucial role in validating the transactions stored by the sequencer. They ensure the correctness of the transactions, thereby maintaining the integrity of the overall system [31, 41, 14]. Verifiers Verifiers Authors: (1) Johnnatan Messias, Matter Labs; (2) Krzysztof Gogol, Matter Labs, University of Zurich; (3) Maria Inês, Silva Matter Labs; (4) Benjamin Livshits, Matter Labs, Imperial College London. Authors : Authors (1) Johnnatan Messias, Matter Labs; (2) Krzysztof Gogol, Matter Labs, University of Zurich; (3) Maria Inês, Silva Matter Labs; (4) Benjamin Livshits, Matter Labs, Imperial College London. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv

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