Adaptable and data-driven softwarized networks: Review, opportunities, and challenges
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 …
sustain their critical services in the future, communication networks need to flexibly …
A comprehensive survey on knowledge-defined networking
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 …
plane. Software-Defined Networking (SDN), which has a logically centralized control plane …
In-band network telemetry: A survey
With the development of software-defined network and programmable data-plane
technology, in-band network telemetry has emerged. In-band network telemetry technology …
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 …
sophisticated and dynamic. We develop a reinforcement learning routing algorithm …
Networking Integrated Cloud–Edge–End in IoT: A Blockchain-Assisted Collective Q-Learning Approach
Recently, the term “Internet of Things”(IoT) has elicited escalating attention. The flexibility,
agility, and ubiquitous accessibility have encouraged the integration between machine …
agility, and ubiquitous accessibility have encouraged the integration between machine …
Networking systems of AI: On the convergence of computing and communications
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 …
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
Data-center networks (DCN) possess multiple new features: coexistence of elephant
flow/mice flow/coflow, and coexistence of multiple network resources (bandwidth, cache and …
flow/mice flow/coflow, and coexistence of multiple network resources (bandwidth, cache and …
Intelligent sensing, communication, computation and caching for satellite-ground integrated networks
Satellite-ground integrated networks (SGINs) are regarded as promising architectures for
sensing heterogenous measurements, reducing network congestion and for providing …
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
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 …
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
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 …
because of its flexible architecture. It is expected to become an essential enabler for the …