TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic

Research article (Future Generation Computer Systems, 2024) · cited 16× · AI/ML
Press Enter · cited answer in seconds

TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic

Summary

TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic is a scholarly article[1].

Key Facts

  • TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic's instance of is recorded as scholarly article[2].

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic. Retrieved May 24, 2026, from https://4ort.xyz/entity/tite-a-transformer-based-deep-reinforcement-learning-approach-for-traffic-engineering-in-hybrid-sdn-with-dynamic-traffic
MLA “TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/tite-a-transformer-based-deep-reinforcement-learning-approach-for-traffic-engineering-in-hybrid-sdn-with-dynamic-traffic.
BibTeX @misc{4ortxyz_tite-a-transformer-based-deep-reinforcement-learning-approach-for-traffic-engineering-in-hybrid-sdn-with-dynamic-traffic_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic}}, year = {2026}, url = {https://4ort.xyz/entity/tite-a-transformer-based-deep-reinforcement-learning-approach-for-traffic-engineering-in-hybrid-sdn-with-dynamic-traffic}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): TITE: A transformer-based deep reinforcement learning approach for traffic engineering in hybrid SDN with dynamic traffic — https://4ort.xyz/entity/tite-a-transformer-based-deep-reinforcement-learning-approach-for-traffic-engineering-in-hybrid-sdn-with-dynamic-traffic (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/tite-a-transformer-based-deep-reinforcement-learning-approach-for-traffic-engineering-in-hybrid-sdn-with-dynamic-traffic · Last refreshed: