Bitcoin Mempool Linearization

[2607.23787] Bitcoin Mempool Linearization Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Data Structures and Algorithms arXiv:2607.23787 (cs) [Submitted on 26 Jul 2026 ( v1 ), last revised 15 Aug 2026 (this version, v2)] Title: Bitcoin Mempool Linearization Authors: Arman Mollakhani , Pieter Wuille , Dongning Guo View a PDF of the paper titled Bitcoin Mempool Linearization, by Arman Mollakhani and 2 other authors View PDF HTML (experimental) Abstract: In the Bitcoin system, transactions arrive continuously at miners' mempools and await inclusion in future blocks. Every non-coinbase transaction must spend one or more unspent outputs created by previous transactions, inducing dependency constraints among transactions in the mempool. At the same time, miners are economically incentivized to prioritize transactions with higher fee rates, measured as transaction fee per unit size. This paper formulates the mempool linearization problem: given a set of transactions with associated fees, sizes, and dependency relationships, compute a dependency-respecting transaction ordering that maximizes fee-rate efficiency while supporting efficient updates as the mempool evolves dynamically. The problem is characterized through a partition of transactions into disjoint dependency-respecting subsets ordered by decreasing aggregate fee rate, together with an equivalent linear programming formulation. Motivated by structural properties of basic feasible solutions in the simplex method, a new algorithm called spanning forest linearization (SFL) is developed. Operating directly on the transaction dependency graph, SFL iteratively merges and splits chunks of transactions to refine a global ordering, and is guaranteed to terminate at an optimal solution. Evaluation on both synthetic and real-world Bitcoin mempool data shows that SFL consistently computes optimal linearizations with substantially lower runtime than competing approaches, including a method based on the parametric preflow algorithm of Gallo, Grigoriadis, and Tarjan. These results indicate that SFL provides a practical and scalable framework for transaction prioritization by decentralized miners in large and rapidly evolving mempools. SFL has also been incorporated into the Bitcoin Core codebase for transaction cluster linearization. Subjects: Data Structures and Algorithms (cs.DS) ; Cryptography and Security (cs.CR) Cite as: arXiv:2607.23787 [cs.DS] (or arXiv:2607.23787v2 [cs.DS] for this version) https://doi.org/10.48550/arXiv.2607.23787 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Arman Mollakhani [ view email ] [v1] Sun, 26 Jul 2026 18:04:28 UTC (98 KB) [v2] Sat, 15 Aug 2026 01:20:01 UTC (98 KB) Full-text links: Access Paper: View a PDF of the paper titled Bitcoin Mempool Linearization, by Arman Mollakhani and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.DS < prev | next > new | recent | 2026-07 Change to browse by: cs cs.CR References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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