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Efficient Data Management for IPFS dApps

Vero Estrada-Galiñanes, Ahmad ElRouby, Léo Marc-André Theytaz

TL;DR

This work tackles the data management bottleneck in IPFS-based dApps by introducing a two-component off-chain storage layer: the IPFS Community, which encodes data with alpha entanglement (AE) codes to reduce storage overhead, and a collaborativeRepair/Monitoring module that distributes repair tasks across peers. The core idea is to replace costly, unbounded replication with AE-coded entangled Merkle DAGs (eDAGs) and to organize distributed repairs via a stateful daemon that coordinates across IPFS and IPFS Cluster. The authors implement these components as pluggable modules, validate the approach with a 20-node evaluation featuring AE parameters α=3, s=5, p=5, and demonstrate potential space savings and improved repair efficiency through collaborative repairs. The results indicate meaningful practical impact for scalable, reliable off-chain storage in IPFS-enabled ecosystems, with broader applicability to other distributed file systems.

Abstract

Inefficient data management has been the Achilles heel of blockchain-based decentralized applications (dApps). An off-chain storage layer, which lies between the application and the blockchain layers, can improve space efficiency and data availability with erasure codes and decentralized maintenance. This paper presents two fundamental components of such storage layer designed and implemented for the IPFS network. The IPFS Community is a component built on top of the IPFS network that encodes and decodes data before uploading to the network. Since data is encoded with alpha entanglement codes, the solution requires less storage space than the native IPFS solution which replicates data by pinning content with the IPFS Cluster. To detect and repair failures in a timely manner, we introduce the monitoring and repair component. This novel component is activated by any node and distributes the load of repairs among various nodes. These two components are implemented as pluggable modules, and can, therefore, be easily migrated to other distributed file systems by adjusting the connector component.

Efficient Data Management for IPFS dApps

TL;DR

This work tackles the data management bottleneck in IPFS-based dApps by introducing a two-component off-chain storage layer: the IPFS Community, which encodes data with alpha entanglement (AE) codes to reduce storage overhead, and a collaborativeRepair/Monitoring module that distributes repair tasks across peers. The core idea is to replace costly, unbounded replication with AE-coded entangled Merkle DAGs (eDAGs) and to organize distributed repairs via a stateful daemon that coordinates across IPFS and IPFS Cluster. The authors implement these components as pluggable modules, validate the approach with a 20-node evaluation featuring AE parameters α=3, s=5, p=5, and demonstrate potential space savings and improved repair efficiency through collaborative repairs. The results indicate meaningful practical impact for scalable, reliable off-chain storage in IPFS-enabled ecosystems, with broader applicability to other distributed file systems.

Abstract

Inefficient data management has been the Achilles heel of blockchain-based decentralized applications (dApps). An off-chain storage layer, which lies between the application and the blockchain layers, can improve space efficiency and data availability with erasure codes and decentralized maintenance. This paper presents two fundamental components of such storage layer designed and implemented for the IPFS network. The IPFS Community is a component built on top of the IPFS network that encodes and decodes data before uploading to the network. Since data is encoded with alpha entanglement codes, the solution requires less storage space than the native IPFS solution which replicates data by pinning content with the IPFS Cluster. To detect and repair failures in a timely manner, we introduce the monitoring and repair component. This novel component is activated by any node and distributes the load of repairs among various nodes. These two components are implemented as pluggable modules, and can, therefore, be easily migrated to other distributed file systems by adjusting the connector component.
Paper Structure (31 sections, 1 equation, 9 figures)

This paper contains 31 sections, 1 equation, 9 figures.

Table of Contents

  1. Introduction
  2. IPFS: A Primer on its Reliability
  3. Reliability
  4. Content Persistence via Pinning
  5. Replication
  6. IPFS Cluster
  7. Proposed IPFS Community
  8. Strawman
  9. Challenges
  10. Design Overview
  11. Key Algorithm: AE Codes
  12. Key Data Structure: Entangled Merkle DAGs
  13. IPFS Community Implementation
  14. Upload: File Entanglement
  15. Download: File Repairs
  16. ...and 16 more sections

Figures (9)

  • Figure 1: Strawman IPFS Community Architecture.
  • Figure 2: Design Architecture: IPFS Community Node
  • Figure 3: Collaborative Repair
  • Figure 4: Average percentage of recovered blocks given a percentage of peer failure
  • Figure 5: High level monitoring set-up
  • ...and 4 more figures