Adaptable and data-driven softwarized networks: Review, opportunities, and challenges

W Kellerer, P Kalmbach, A Blenk, A Basta… - Proceedings of the …, 2019 - ieeexplore.ieee.org
Communication networks are the key enabling technology for our digital society. In order to
sustain their critical services in the future, communication networks need to flexibly …

A comprehensive survey on knowledge-defined networking

PADSN Wijesekara, S Gunawardena - Telecom, 2023 - mdpi.com
Traditional networking is hardware-based, having the control plane coupled with the data
plane. Software-Defined Networking (SDN), which has a logically centralized control plane …

In-band network telemetry: A survey

L Tan, W Su, W Zhang, J Lv, Z Zhang, J Miao, X Liu… - Computer Networks, 2021 - Elsevier
With the development of software-defined network and programmable data-plane
technology, in-band network telemetry has emerged. In-band network telemetry technology …

RL-routing: An SDN routing algorithm based on deep reinforcement learning

YR Chen, A Rezapour, WG Tzeng… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Communication networks are difficult to model and predict because they have become very
sophisticated and dynamic. We develop a reinforcement learning routing algorithm …

Networking Integrated Cloud–Edge–End in IoT: A Blockchain-Assisted Collective Q-Learning Approach

C Qiu, X Wang, H Yao, J Du, FR Yu… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Recently, the term “Internet of Things”(IoT) has elicited escalating attention. The flexibility,
agility, and ubiquitous accessibility have encouraged the integration between machine …

Networking systems of AI: On the convergence of computing and communications

L Song, X Hu, G Zhang, P Spachos… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Artificial intelligence (AI) and 5G system have been two hot technical areas that are
changing the world. On the deep convergence of computing and communication, networking …

DRL-R: Deep reinforcement learning approach for intelligent routing in software-defined data-center networks

W Liu, J Cai, QC Chen, Y Wang - Journal of Network and Computer …, 2021 - Elsevier
Data-center networks (DCN) possess multiple new features: coexistence of elephant
flow/mice flow/coflow, and coexistence of multiple network resources (bandwidth, cache and …

Intelligent sensing, communication, computation and caching for satellite-ground integrated networks

Y Gong, H Yao, A Nallanathan - IEEE Network, 2024 - ieeexplore.ieee.org
Satellite-ground integrated networks (SGINs) are regarded as promising architectures for
sensing heterogenous measurements, reducing network congestion and for providing …

QR-SDN: Towards reinforcement learning states, actions, and rewards for direct flow routing in software-defined networks

J Rischke, P Sossalla, H Salah, FHP Fitzek… - IEEE …, 2020 - ieeexplore.ieee.org
Flow routing can achieve fine-grained network performance optimizations by routing distinct
packet traffic flows over different network paths. While the centralized control of Software …

Improving the software-defined wireless sensor networks routing performance using reinforcement learning

MU Younus, MK Khan, AR Bhatti - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Software-defined networking (SDN) is an emerging architecture used in many applications
because of its flexible architecture. It is expected to become an essential enabler for the …