Dynamic Entanglement Packet Scheduling for Quantum Networks

2026-05-27

AI Summary

This work addresses the challenge of multi-user entanglement distribution in scalable quantum networks, where static scheduling fails to accommodate the stochastic and asynchronous nature of user requests. The authors propose an online dynamic scheduler based on a time-division multiple access (TDMA) architecture, introducing—for the first time—a real-time decision-making mechanism that dynamically schedules, postpones, retries, or discards entanglement requests according to instantaneous network conditions. This approach replaces conventional periodic static or earliest-deadline-first (EDF) scheduling policies. Simulation results demonstrate that the proposed method significantly reduces task completion time while improving success rate and throughput, and crucially, maintains feasible scheduling with graceful degradation even under network overload conditions.

Abstract

Sharing entanglement among multiple users remains a central challenge for scalable quantum networks. Recent work proposed an on-demand entanglement packet architecture in which a controller uses a Time Division Multiple Access (TDMA) approach to allocate network resources. Quantum nodes are assigned a periodic schedule that probabilistically fulfills application requests for end-to-end entanglements. The schedule is recomputed periodically using well-known algorithms, such as Earliest Deadline First (EDF). However, a static schedule offers limited flexibility when outcomes are stochastic and arrivals are asynchronous. To overcome this limitation, we propose an online scheduler that dynamically schedules, defers, retries, or drops entanglement distribution reservations. In our simulations, the dynamic scheduler achieves lower completion time, higher completion ratio, and higher throughput than the static baseline. Furthermore, when the network is overloaded, the dynamic scheduler continues to construct deadline-feasible schedules and degrades gracefully.

Problem

• quantum networks
• entanglement sharing
• dynamic scheduling
• resource allocation
• stochastic outcomes

Innovation

• Dynamic Scheduling
• Entanglement Distribution
• Quantum Networks
• Online Scheduler
• TDMA