[go: up one dir, main page]

Xiao et al., 2024 - Google Patents

Adaptive joint routing and caching in knowledge-defined networking: An actor-critic deep reinforcement learning approach

Xiao et al., 2024

Document ID
15689120069428127561
Author
Xiao Y
Yu H
Yang Y
Wang Y
Liu J
Ansari N
Publication year
Publication venue
IEEE Transactions on Mobile Computing

External Links

Snippet

By integrating the software-defined networking (SDN) architecture with the machine learning- based knowledge plane, knowledge-defined networking (KDN) is revolutionizing established traffic engineering (TE) methodologies. This paper investigates the challenging …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/54Store-and-forward switching systems
    • H04L12/56Packet switching systems
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/10Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network
    • H04L67/1002Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers, e.g. load balancing
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/02Details
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance or administration or management of packet switching networks
    • H04L41/50Network service management, i.e. ensuring proper service fulfillment according to an agreement or contract between two parties, e.g. between an IT-provider and a customer
    • H04L41/5041Service implementation
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00Routing or path finding of packets in data switching networks
    • H04L45/12Shortest path evaluation
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00Traffic regulation in packet switching networks
    • H04L47/10Flow control or congestion control
    • H04L47/24Flow control or congestion control depending on the type of traffic, e.g. priority or quality of service [QoS]
    • H04L47/2441Flow classification
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00Routing or path finding of packets in data switching networks
    • H04L45/04Interdomain routing, e.g. hierarchical routing
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00Routing or path finding of packets in data switching networks
    • H04L45/02Topology update or discovery
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/32Network-specific arrangements or communication protocols supporting networked applications for scheduling or organising the servicing of application requests, e.g. requests for application data transmissions involving the analysis and optimisation of the required network resources
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00Routing or path finding of packets in data switching networks
    • H04L45/30Special provisions for routing multiclass traffic
    • H04L45/302Route determination based on requested QoS
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L69/00Application independent communication protocol aspects or techniques in packet data networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L49/00Packet switching elements

Similar Documents

Publication Publication Date Title
Wei et al. Network slice reconfiguration by exploiting deep reinforcement learning with large action space
Liu et al. DRL-OR: Deep reinforcement learning-based online routing for multi-type service requirements
Sun et al. Cooperative computation offloading for multi-access edge computing in 6G mobile networks via soft actor critic
Sun et al. Autonomous resource slicing for virtualized vehicular networks with D2D communications based on deep reinforcement learning
Zhou et al. Learning from peers: Deep transfer reinforcement learning for joint radio and cache resource allocation in 5G RAN slicing
Chen et al. Joint resource allocation for software-defined networking, caching, and computing
Chen et al. Reinforcement learning–based QoS/QoE‐aware service function chaining in software‐driven 5G slices
Chen et al. ALBRL: Automatic Load‐Balancing Architecture Based on Reinforcement Learning in Software‐Defined Networking
Ghosh et al. A cognitive routing framework for reliable communication in IoT for industry 5.0
Suzuki et al. Multi-agent deep reinforcement learning for cooperative computing offloading and route optimization in multi cloud-edge networks
Mai et al. Multi-agent actor-critic reinforcement learning based in-network load balance
Ye et al. Mitigating routing update overhead for traffic engineering by combining destination-based routing with reinforcement learning
Xiao et al. Adaptive joint routing and caching in knowledge-defined networking: An actor-critic deep reinforcement learning approach
Xiao et al. Scalable QoS-aware multipath routing in hybrid knowledge-defined networking with multiagent deep reinforcement learning
Ye et al. FlexDATE: Flexible and disturbance-aware traffic engineering with reinforcement learning in software-defined networks
Wei et al. GRL-PS: Graph embedding-based DRL approach for adaptive path selection
He et al. RTHop: Real-time hop-by-hop mobile network routing by decentralized learning with semantic attention
Chen et al. Fault tolerance oriented SFC optimization in SDN/NFV-enabled cloud environment based on deep reinforcement learning
Chiu et al. Reinforcement Learning‐Based Service‐Oriented Dynamic Multipath Routing in SDN
Guo et al. Intelligent edge network routing architecture with blockchain for the IoT
Khoramnejad et al. Distributed multi-agent learning for service function chain partial offloading at the edge
Wei et al. An adaptive service function chains mapping with multi-task deep reinforcement learning
Han et al. Multi-SP network slicing parallel relieving edge network conflict
Feng et al. CaRCS: Joint optimization of computing-aware routing and collaborative scheduling in computing power networks
Li et al. Online coordinated NFV resource allocation via novel machine learning techniques