Project Overview

This project proposes fast heuristic methods for deploying quantum repeaters in large-scale quantum networks.
While Integer Linear Programming (ILP) can find optimal placements, it does not scale. The proposed heuristics achieve near-optimal solutions while reducing computation time from days to seconds.

Key Ideas

• Coverage-driven placement using a maximum entanglement distance \( L_{max} \)
• Heuristic optimization instead of exponential-time ILP
• Scalable and failure-aware deployment for real-world networks

Heuristic Approaches

Two complementary strategies are introduced:

• Multi-Center Approach (MCA): Selects multiple coverage centers and adds intermediate repeaters only when needed
• Single Center Approach (SCA): Gradually expands coverage from one center, jointly ensuring coverage and connectivity

Performance Highlights

• Near-optimal repeater count (often matching ILP)
• Execution time reduced by several orders of magnitude
• Validated on SURFnet and ESnet topologies
• Extended to tolerate node and link failures

Publication

Tasdiqul Islam, Engin Arslan
A Heuristic Approach for Scalable Quantum Repeater Deployment Modeling IEEE Conference on Local Computer Networks (LCN), 2023

BibTeX:

@inproceedings{islam2023heuristic,
  title={A heuristic approach for scalable quantum repeater deployment modeling},
  author={Islam, Tasdiqul and Arslan, Engin},
  booktitle={2023 IEEE 48th Conference on Local Computer Networks (LCN)},
  pages={1--9},
  year={2023},
  organization={IEEE}
}