QKD Resource Allocation in Optical Networks

How can a QKD-enabled optical network provision competing connection requests when quantum channels, wavelengths, and time slots are limited, and key negotiation is degraded by noise and eavesdropping? My MS thesis evaluated this by coupling the QKD protocol layer with the network-allocation layer, treating them as an interdependent system.

At the protocol layer, I built hybrid Qiskit simulations for BB84 and E91 protocols to analyze QBER and secure key yields under noise. At the network layer, I built a Python simulation on the 14-node NSFNET topology, allocating wavelengths, time-slots, and dedicated quantum channels to connection requests based on dynamic security tiers.

I implemented three Quantum Key Resource Allocation (QKRA) policies: Specific Security Level (SSL), Adaptive Strong Security Level (ASSL), and Adaptive Weak Security Level (AWSL). A priority queue processes high-security requests first. ASSL elevates a request when stronger-security resources have capacity, while AWSL lowers the assigned security tier to maintain connection success when the requested pool is saturated. The comparison tracked allocation success, time-slot utilization, and security-weighted provisioning under increasing traffic.

After correcting early indexing logic defects, I analyzed routing and security policies across increasing connection loads. Allocation success stayed near 1.0 under light load and declined predictably as requests exceeded available resources. Time-slot Utilization Ratio (TUR) rose toward saturation, and Network Security Performance (NSP) scaled with provisioned, security-weighted requests. At the protocol layer, escalating noise and eavesdropping validated the transition boundary between Hamming correction and Cascade reconciliation as QBER increased and secure-key yield dropped. In the final MS Thesis, I delivered the complete system architecture and benchmarks.

The linked public repository is a tested, maintainable extraction of the broader thesis. It exposes the full 14-node NSFNET allocation study with priority scheduling, k-shortest paths, first-fit allocation, and performance metrics (SRCR, TUR, NSP), alongside selected BB84 and Hamming utilities. Raw experimental sandboxes, E91 implementations, and Cascade reconciliation experiments remain in the complete thesis archive. This project represents a controlled numerical simulation of QKD network behavior, not a hardware deployment or a production cryptographic stack.