Abstract

With the rapid advancement of 6G technology and the increasing use of smart devices, Deterministic 6G Wireless Networks (D6WN) have emerged to meet the growing network transmission demands. In particular, applications such as autonomous vehicles, remote surgery, and industrial automation require extremely low transmission latency to function effectively, highlighting the critical need for D6WN in supporting these time-sensitive use cases. Yet, the conventional TCP/IP framework lacks effective unified traffic and congestion control scheduling, aggravating latency and uncertainty, posing a challenge to ensuring reliable real-time critical applications. To address the challenges of deterministic transmission in D6WN, this paper integrates Digital Twin (DT) into design and management of D6WN, proposing a DT-assisted Deterministic Optimal Cycle Path mechanism (DOCP) that ensures low packet loss and strict end-to-end (E2E) delay guarantees for Deterministic traffic Flow (DetFlow). Specifically, we have constructed a DT-assisted network framework that integrates the application plane, control plane, and data plane to achieve comprehensive monitoring of network resources and scheduling optimization. During the DetFlow scheduling process, we employ an improved K-shortest path method along with a Cycle Specified Queuing and Forwarding (CSQF) queue scheduling model to select deterministic paths and time-slots. Subsequently, we utilize a hybrid tabu genetic algorithm for joint scheduling of paths and slot queues, enabling the identification of optimal slot paths. The results demonstrate that this approach provides stable E2E delay guarantees and efficient deterministic forwarding.

Department(s)

Computer Science

Publication Status

Full Text Access

Keywords and Phrases

Back-pressure; CSQF; Deterministic 6G Wireless Network; Digital twin; Route scheduling

International Standard Serial Number (ISSN)

1389-1286

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2026 Elsevier, All rights reserved.

Publication Date

01 Jul 2026

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