ROAR is proposed, a novel architectural solution that implements Deep Reinforcement Learning (DRL) inside P4 programmable switches to perform adaptive routing policies based on network conditions and traffic patterns that show both a throughput and delay improvement in the transmission compared to traditional approaches.
Networks with highly dynamic data transmission demands and network topologies are common in real world. A fundamental problem in such networks is achieving scalable traffic allocation to maximize long-term total throughput under link capacity constraints. However, state-of-the-art (SOTA) works lack scalability. This is...
Zhaoxing Yang, Guiyun Fan, An-Jie Cao et al.· IEEE Transactions on Network...· 0 citations
This paper presents a comprehensive framework for artificial intelligence (AI)-enabled autonomous network slicing optimization in 6G systems and investigates the application of advanced machine learning paradigms specifically deep reinforcement learning, federated learning, and generative AI to orchestrate dynamic reso...
N. J., Jeeva Jothi· International Journal of Com...· 0 citations
This work proposes EAGLE, a Multi-Agent Reinforcement Learning (MARL) system that autonomously orchestrates the scaling of network resources to meet flow demands and reduce power consumption, and shows that the trained model can “zero-shot generalize” to unseen network topologies that share structural or statistical si...
Doriana Monaco, Alessio Sacco, Flavio Esposito et al.· IEEE Transactions on Network...· 0 citations
Future 6G services will require strict performance guarantees, especially in terms of delay, end-to-end (e2e) across multiple network domains including packet and radio segments. While deterministic transport and slice-based capacity allocation can improve segment-level performance, ensuring e2e Network Service (NS) pe...
H. Shakespear-Miles, S. Barzegar, M. Ruiz et al.· IEEE Transactions on Network...· 0 citations
As the modern network infrastructure continue to become more and more complex, massive set of firewall rules have been produced, which causes large package classification latency and poor resource utilization. Firewall rule ordering is an NP-hard mathematical programming problem in which the wrong sequencing of firewal...
Jonnalagadda Syam Babu, K. V. Shilpa, M.Hanish Kumar et al.· 2026 7th International Confe...· 0 citations
The research findings indicate that the key to enhancing real-time cloud network intelligence lies in the architecture based on Deep Reinforcement Learning (DRL), and provide useful guidelines for future engineering projects to ensure that network management infrastructure possesses autonomy, flexibility, and efficienc...
Shuyao Jia· The 2026 International Confe...· 0 citations
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