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Carbyne: An Ultra-Lightweight DoS-Resilient Mempool for Bitcoin

Hina Binte Haq, Syed Taha Ali, Asad Salman, Patrick McCorry, Siamak F. Shahandashti

TL;DR

Carbyne tackles the RAM bottleneck of Bitcoin full nodes by rearchitecting the mempool with two counting Bloom filters that store fingerprints instead of full transactions. This design decouples transaction forwarding from inventory tracking, enabling ultra-lightweight operation while maintaining high fidelity, DoS-resilience, and near-real-time processing. Through a large, real-world 90-day dataset, Carbyne achieves memory reductions from hundreds of megabytes to a few megabytes with accuracy exceeding 99.9%, and can handle congestion scenarios far beyond historical Bitcoin traffic. The approach is compatible with existing Bitcoin Protocol semantics (no fork) and extensible to other currencies (e.g., CarbEth), with concrete pathways to dynamic scalability and future Ethereum adaptations. Overall, Carbyne significantly lowers participation costs for full-node operators, enhancing decentralization and network security under high transaction loads.

Abstract

The increasing adoption of cryptocurrencies has significantly amplified the resource requirements for operating full nodes, creating substantial barriers to entry. Unlike miners, who are financially incentivized through block rewards and transaction fees, full nodes lack direct economic compensation for their critical role in maintaining the network. A key resource burden is the transaction pool, which is particularly memory-intensive as it temporarily stores unconfirmed transactions awaiting verification and propagation across the network. We present Neonpool, a novel optimization for transaction pool leveraging bloom filter variants to drastically reduce memory consumption by up to 200 (e.g., 400 MB to 2 MB) while maintaining over 99.99% transaction processing accuracy. Implemented in C++ and evaluated on unique Bitcoin and Ethereum datasets, Neonpool enables efficient operation on lightweight clients, such as smartphones, IoT devices, and systems-on-a-chip, without requiring a hard fork. By lowering the cost of node participation, Neonpool enhances decentralization and strengthens the overall security and robustness of cryptocurrency networks.

Carbyne: An Ultra-Lightweight DoS-Resilient Mempool for Bitcoin

TL;DR

Carbyne tackles the RAM bottleneck of Bitcoin full nodes by rearchitecting the mempool with two counting Bloom filters that store fingerprints instead of full transactions. This design decouples transaction forwarding from inventory tracking, enabling ultra-lightweight operation while maintaining high fidelity, DoS-resilience, and near-real-time processing. Through a large, real-world 90-day dataset, Carbyne achieves memory reductions from hundreds of megabytes to a few megabytes with accuracy exceeding 99.9%, and can handle congestion scenarios far beyond historical Bitcoin traffic. The approach is compatible with existing Bitcoin Protocol semantics (no fork) and extensible to other currencies (e.g., CarbEth), with concrete pathways to dynamic scalability and future Ethereum adaptations. Overall, Carbyne significantly lowers participation costs for full-node operators, enhancing decentralization and network security under high transaction loads.

Abstract

The increasing adoption of cryptocurrencies has significantly amplified the resource requirements for operating full nodes, creating substantial barriers to entry. Unlike miners, who are financially incentivized through block rewards and transaction fees, full nodes lack direct economic compensation for their critical role in maintaining the network. A key resource burden is the transaction pool, which is particularly memory-intensive as it temporarily stores unconfirmed transactions awaiting verification and propagation across the network. We present Neonpool, a novel optimization for transaction pool leveraging bloom filter variants to drastically reduce memory consumption by up to 200 (e.g., 400 MB to 2 MB) while maintaining over 99.99% transaction processing accuracy. Implemented in C++ and evaluated on unique Bitcoin and Ethereum datasets, Neonpool enables efficient operation on lightweight clients, such as smartphones, IoT devices, and systems-on-a-chip, without requiring a hard fork. By lowering the cost of node participation, Neonpool enhances decentralization and strengthens the overall security and robustness of cryptocurrency networks.

Paper Structure

This paper contains 33 sections, 3 equations, 12 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Background
  3. Spam, Stress Tests, and Dust Attacks
  4. Prior Work
  5. Threat Model
  6. Bitcoin Mempool and Structure
  7. Building Blocks: Counting Bloom Filters
  8. Proposed Solution: Carbyne
  9. Entry
  10. Exit
  11. Methodology
  12. The MempoolState Dataset
  13. Experiments and Results
  14. Implementation and Methodology
  15. Performance Metrics
  16. ...and 18 more sections

Figures (12)

  • Figure 1: Bitcoin mempool & transaction fee trends mempool-size
  • Figure 2: Memory and Disk Schematic
  • Figure 3: Bloom filters example $(m=16, k=3, n=3)$
  • Figure 4: Entry and Inventory Processes
  • Figure 5: Mempool Exit for Bitcoin Core and Carbyne
  • ...and 7 more figures