Fair Sequencing

The core function of an FSS is to receive transactions from users and output a canonical order for the underlying blockchain (e.g., Ethereum). This order is determined by objective rules, not by a validator's ability to reorder for profit. Common ordering rules include:

• First-Come, First-Served (FCFS): Orders by the time the service receives the transaction.
• Pessimistic Time: Uses a conservative timestamp to prevent manipulation.
• Priority Gas Auction (PGA) Prevention: Explicitly prevents ordering by the highest gas bid.

A robust FSS must be credibly neutral and cannot arbitrarily exclude valid transactions. This is achieved through mechanisms like:

• Permissionless Participation: Anyone can submit transactions to the service.
• Economic Guarantees: Operators are slashed or penalized for censorship.
• Decentralized Operator Sets: A network of independent nodes prevents a single point of control. Without strong censorship resistance, the sequencer becomes a centralized gatekeeper.

Fair sequencers are designed to mitigate Maximal Extractable Value (MEV) by removing the ability for block producers to reorder transactions for profit. They protect users from:

• Front-running: A later transaction with a higher fee being placed before yours.
• Sandwich Attacks: A malicious actor placing orders around a victim's trade to profit from the price impact. By providing a fair order, the sequencer ensures the execution outcome matches the user's expectation based on the public state when they submitted.

The service must guarantee liveness (transactions are eventually ordered) and provide strong assurances of finality (the order won't change). Key properties include:

• High Throughput & Low Latency: Processes transactions quickly to maintain user experience.
• Cryptographic Commitments: The service publishes a commitment (e.g., a hash) to the proposed order, making it binding.
• Data Availability: The transaction data must be made available so users can verify the correctness of the order and execution.

The security model defines who users must trust. Architectures vary:

• Single Sequencer: Simple but requires trust in one operator (common in rollups).
• Decentralized Sequencer Set: A Proof-of-Stake network where operators stake collateral and can be slashed for misbehavior.
• Threshold Cryptography: Orders require signatures from a majority of a committee. The goal is to minimize trust assumptions and approach the security of the underlying L1.

The fair sequence must be reliably delivered to the execution environment (e.g., an L2 rollup or L1 block builder). This involves:

• Binding Submission: The sequencer or a designated party is forced to submit the exact ordered batch to the chain.
• Verification & Fraud Proofs: Observers can verify the execution matches the order and submit fraud proofs if not.
• Fallback Mechanisms: If the primary sequencer fails, users or a decentralized set can force-include transactions via the L1.

A first-come, first-served (FCFS) policy where transactions are ordered strictly by the time they are received by the sequencer, as measured by a trusted timestamp. This is a foundational concept for fairness.

• Challenge: Requires a reliable, decentralized time source to prevent manipulation.
• Use Case: Often a baseline property in Fair Sequencing Services (FSS) to counter temporal attacks.

Rollups, as centralized sequencers, are primary candidates for implementing fair ordering rules. They can enforce policies on their mempool before batches are submitted to L1.

• Example: Arbitrum's BOLD (Bounded Liquidity Delay) mechanism introduces a challenge period for fair state transitions.
• Future: Many L2s are researching decentralized sequencer sets with built-in fair ordering protocols to enhance censorship resistance.

A conceptual framework where an independent, decentralized network provides a verifiably fair transaction order as a service to one or more blockchains. The FSS acts as a trusted third party for ordering, not execution.

• Key Property: Order-Fairness guarantees, such as receiving a transaction's relative position in the output order.
• Analogy: Functions like a decentralized, tamper-proof ticketing system for blockchain transactions.

Most FSS implementations rely on a single, designated sequencer to order transactions. This creates a central point of failure and trust. A malicious or compromised sequencer can:

• Censor transactions by excluding them from blocks.
• Extract MEV by reordering transactions for its own profit, defeating the service's purpose.
• Fail entirely, halting the chain's liveness. Decentralizing the sequencer role is a core challenge.

FSS depends on a cryptoeconomic clock or timing oracle to attest to when transactions were first seen. The security model shifts from trusting miners/validators with ordering to trusting these attestation providers.

• If attestations are collusive or faulty, the fair ordering guarantee breaks.
• Attackers may attempt to spoof timestamps or delay network propagation to manipulate perceived arrival times.

Fair ordering is vulnerable to manipulation at the peer-to-peer network layer before transactions reach the sequencer.

• Time-bandit attacks: An adversary with a superior network position can delay competitors' transactions while submitting their own, creating an unfair arrival time advantage.
• Eclipse attacks: Isolating a user or the sequencer to control which transactions are seen and when. These attacks challenge the very definition of 'arrival time' in a decentralized network.

Introducing fair sequencing alters miner/validator incentives, potentially creating new attack vectors.

• Revenue Displacement: If MEV extraction is reduced, sequencers may require alternative fee models (e.g., priority fees), which could be gamed.
• Bribery Attacks: Users might bribe the timing attestation service or network relays to falsify timestamps.
• Convergence to MEV: Without strong cryptographic guarantees, rational sequencers may still be economically incentivized to revert to profit-maximizing (unfair) ordering.

FSS protocols like Themis or Aequitas introduce complex cryptographic constructs (e.g., threshold signatures, verifiable delay functions).

• Bugs in this new code can lead to catastrophic failures or exploited loopholes.
• Rigorous formal verification and security audits are essential but non-trivial.
• Integration risks with existing blockchain clients and infrastructure can create unexpected vulnerabilities.

A sequencer must reliably publish transaction data to a base layer (e.g., Ethereum) for data availability and dispute resolution.

• If the sequencer withholds data, users cannot prove their transaction existed, breaking the chain's security.
• Forced inclusion mechanisms (like Ethereum's forceInclusionPeriod) are required but add latency and complexity.
• This creates a trade-off between liveness (fast sequencing) and censorship resistance.

Miner Extractable Value (MEV) is the profit a block producer can earn by strategically including, excluding, or reordering transactions within a block. It arises from arbitrage opportunities, liquidations, and other on-chain activities. Fair Sequencing Services (FSS) are designed to mitigate MEV by enforcing a canonical transaction order, reducing the ability of validators to manipulate sequencing for profit.

• Sources: Arbitrage, front-running, sandwich attacks.
• Impact: Can lead to network congestion and increased costs for users.

Time-Boost is a specific transaction ordering rule used in some Fair Sequencing Services. It is a hybrid model that combines a first-come, first-served basis with a priority fee auction. Transactions are primarily ordered by the time they are received by the sequencer, but users can pay a priority fee to improve their position in the queue, creating a fair and transparent market for ordering.

A Decentralized Sequencer is a network of nodes that collectively determines the order of transactions before they are submitted to a base layer (like Ethereum). This contrasts with a single, centralized sequencer. Decentralization aims to enhance liveness (resistance to censorship) and security (reducing single points of failure) within a Fair Sequencing Service, making the ordering process more robust and trust-minimized.

First-Come, First-Served (FCFS) is the simplest transaction ordering policy, where transactions are processed in the exact order they are received by a network node. It is a foundational concept for fairness but is vulnerable to network latency advantages, where geographically closer users or those with better connections can consistently submit transactions faster, creating a form of centralization.

Transaction Ordering is the fundamental process of determining the sequence in which submitted transactions are executed on a blockchain. It is a critical component of consensus. In permissionless systems like Ethereum, ordering is typically determined by the block proposer, leading to MEV. Fair Sequencing introduces pre-consensus rules to make this ordering objective and resistant to manipulation.

A Consensus Mechanism is the protocol that enables distributed network nodes to agree on the state of the blockchain, including the canonical order of transactions. Fair Sequencing often operates as a pre-consensus layer, establishing a fair order before transactions are batched and finalized by the underlying chain's consensus (e.g., Proof-of-Stake). It directly interacts with the liveness and safety guarantees of the base layer.