[Paper] Breaking the Storage-Bandwidth Tradeoff in Distributed Storage with Quantum Entanglement

Source: arXiv - 2601.10676v1

Overview

The paper explores how quantum entanglement can be leveraged to overhaul the classic storage‑bandwidth trade‑off that governs distributed storage systems (think cloud‑based file replication). By allowing surviving nodes to exchange quantum‑enhanced information during repair, the authors demonstrate that both the amount of data each node must store and the bandwidth needed to rebuild a failed node can be simultaneously minimized—a feat impossible in purely classical architectures.

Key Contributions

• Quantum‑augmented repair model: Introduces a repair protocol where helper nodes send classical data over quantum channels and the newcomer performs measurements on the received quantum states.
• Exact trade‑off characterization: Derives the fundamental storage‑repair bandwidth curve for the quantum‑enabled system, showing it strictly dominates the classical counterpart.
• Breakthrough at the Minimum‑Storage Regenerating (MSR) point: Proves that when the number of helpers (d \ge 2k-2), there exists an operating point where both storage per node and repair bandwidth achieve their theoretical minima simultaneously.
• Entanglement‑only among survivors: The improvement relies solely on pre‑shared entanglement among the surviving nodes—no quantum memory is required at the newcomer.
• Analytical proofs and constructive schemes: Provides explicit coding constructions that attain the optimal points, together with rigorous converse arguments.

Methodology

1. System Model Extension – The classic ((n,k,d)) distributed storage framework is extended to include quantum channels between the (d) helper nodes and the newcomer. The helpers still hold classical fragments of the file but can encode these fragments into quantum states using shared entanglement.
2. Information‑Theoretic Analysis – The authors apply entropy‑based arguments (both classical and quantum) to derive lower bounds on the total amount of information that must flow during repair.
3. Achievability via Quantum Network Coding – They construct explicit repair schemes that use quantum teleportation‑style operations: each helper measures its entangled qubits together with its stored data, sending the measurement outcomes (classical bits) to the newcomer, which then performs a joint measurement to reconstruct the missing fragment.
4. Trade‑off Curve Derivation – By balancing the storage per node ((\alpha)) against the total repair bandwidth ((\gamma)), they obtain a closed‑form expression for the optimal curve and identify the special point where (\alpha) and (\gamma) are both minimized.

Results & Findings

The standout finding is the simultaneous minimization of storage and repair bandwidth at the MSR point when enough helpers are available. In practical terms, a system can store the minimal amount of redundancy and repair a failed node by transmitting only the minimal amount of data—something classical regenerating codes cannot achieve.

Practical Implications

• Reduced Cloud‑Repair Costs: Data centers could cut network traffic during node repair, translating into lower operational expenses and faster recovery times.
• Energy Efficiency: Less bandwidth means lower power consumption for inter‑node communication, aligning with sustainability goals.
• Scalable Quantum‑Ready Storage: The protocol only requires entanglement among existing nodes; no quantum hardware is needed at the newcomer, making incremental adoption feasible as quantum networking matures.
• Enhanced Reliability for Edge/IoT Networks: In environments where bandwidth is scarce (e.g., edge clusters, satellite constellations), quantum‑assisted repair could keep data highly available without over‑provisioning storage.
• Foundation for Hybrid Classical‑Quantum Systems: The work provides a concrete blueprint for integrating quantum communication primitives into existing distributed storage stacks, paving the way for future services that blend classical storage with quantum networking.

Limitations & Future Work

• Entanglement Distribution Overhead: The analysis assumes pre‑shared entanglement among surviving nodes; establishing and maintaining this entanglement in a large, dynamic cluster remains an engineering challenge.
• Quantum Channel Fidelity: Real‑world quantum channels suffer from loss and noise; the paper’s theoretical results assume ideal channels, so practical performance may degrade.
• Hardware Constraints: Current quantum networking hardware is limited in range and node count, restricting immediate large‑scale deployment.
• Future Directions: The authors suggest exploring fault‑tolerant entanglement distribution protocols, extending the model to heterogeneous storage nodes, and investigating the impact of partial quantum assistance (e.g., only a subset of helpers equipped with quantum links).

Bottom line: By marrying quantum entanglement with distributed storage, this research shatters the long‑standing storage‑bandwidth trade‑off, opening a path toward ultra‑efficient, highly resilient cloud and edge storage systems—provided we can tame the practical hurdles of quantum networking.

Authors

• Lei Hu
• Mohamed Nomeir
• Alptug Aytekin
• Sennur Ulukus

Paper Information

• arXiv ID: 2601.10676v1
• Categories: cs.IT, cs.DC, cs.NI, eess.SP, quant-ph
• Published: January 15, 2026
• PDF: Download PDF