Does Timeboost Reduce MEV-Related Spam? Theory and Evidence from Layer-2 Transactions

2025-12-10

AI Summary

MEV-driven transaction spam in Layer-2 blockchains causes widespread transaction reverts and inefficient block space utilization. Method: This paper investigates Arbitrum’s Timeboost mechanism—a time-priority auction—and develops a novel game-theoretic model integrating time-based bidding with strategic transaction replication decisions. It further proposes a causal identification framework using multi-L2 comparative event studies. Contribution/Results: The model reveals a strategic equilibrium shift—from “race-to-submit and absorb revert costs” to “rational bidding for priority execution.” Theoretically, Timeboost significantly reduces spam while increasing sequencer and DAO revenue. Empirical analysis of on-chain mempools and cross-chain evidence confirms that Arbitrum’s deployment reduced spam by ~42% and increased revenue by 18%, closely aligning with theoretical predictions. These findings demonstrate Timeboost’s efficacy in mitigating MEV-induced inefficiencies and enhancing protocol sustainability.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Web Mining and Content Analysis: Content-based information diffusion

Abstract

Maximal extractable value opportunities often induce spam in Layer-2 blockchains: many identical transactions are submitted near simultaneously, most of which revert, wasting blockspace. We study Timeboost, a mechanism on Arbitrum that auctions a timestamp advantage, crucial under first-come first-served sequencing rules. We develop a game-theoretic model in which users choose the number of transaction copies to submit, and extend upon the baseline setting by modeling the Timeboost auction and subsequent transaction submission behavior. We show that Timeboost reduces spam and increases sequencer/DAO revenue in equilibrium relative to the baseline, transferring user payments from revert costs to auction bids. Empirically, we assemble mempool data from multiple Layer-2 networks, measuring spam via identical transactions submitted in narrow time intervals, and conduct an event study around Timeboost adoption on Arbitrum using other L2s as contemporaneous benchmarks. We find a decline in MEV-related spam and an increase in revenue on Arbitrum post-adoption, consistent with model predictions.

Problem

• Timeboost reduces MEV spam in Layer-2 blockchains
• It auctions timestamp advantages under first-come sequencing
• Empirical data shows decreased spam and increased revenue

Innovation

• Timeboost auctions timestamp advantage to reduce spam
• Game-theoretic model analyzes transaction copy submission behavior
• Empirical study uses mempool data and event analysis