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 …

A Review of blockchain technology in knowledge-defined networking, its application, benefits, and challenges

PADSN Wijesekara, S Gunawardena - Network, 2023 - mdpi.com
Knowledge-Defined Networking (KDN) necessarily consists of a knowledge plane for the
generation of knowledge, typically using machine learning techniques, and the …

[HTML][HTML] Knowledge-defined networking: Applications, challenges and future work

S Ashtari, I Zhou, M Abolhasan, N Shariati, J Lipman… - Array, 2022 - Elsevier
Future 6G wireless communication systems are expected to feature intelligence and
automation. Knowledge-defined networking (KDN) is an evolutionary step toward …

Fine-grained flow classification using deep learning for software defined data center networks

WX Liu, J Cai, Y Wang, QC Chen, JQ Zeng - Journal of Network and …, 2020 - Elsevier
Abstract in a data center network, accurately classifying flow is the key to optimal schedule
flow. However, the existing classification methods cannot meet the demand of real networks …

Knowledge-defined edge computing networks assisted long-term optimization of computation offloading and resource allocation strategy

K Yang, X Wang, Q He, L Zhao, Y Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the proliferation of devices connected to the Internet of Things (IoT), the complexity of
network management has increased. To intelligently manage large-scale networks, we …

Rethinking data center networks: Machine learning enables network intelligence

B Li, T Wang, P Yang, M Chen… - … of Communications and …, 2022 - ieeexplore.ieee.org
To support the needs of ever-growing cloud-based services, the number of servers and
network devices in data centers is increasing exponentially, which in turn results in high …

Boundaries of flow table usage reduction algorithms based on elephant flow detection

P Jurkiewicz - 2021 IFIP Networking Conference (IFIP …, 2021 - ieeexplore.ieee.org
The majority of Internet traffic is caused by a relatively small number of flows (so-called
elephant flows). This phenomenon can be exploited to facilitate traffic engineering: resource …

[PDF][PDF] FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management.

NA Alkhalidi, FA Yaseen - … Journal of Intelligent Engineering & Systems, 2021 - inass.org
Traffic classification is referred to as the task of categorizing traffic flows into application-
aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic …

Machine learning empowered intelligent data center networking: A survey

B Li, T Wang, P Yang, M Chen, S Yu… - arXiv preprint arXiv …, 2022 - arxiv.org
To support the needs of ever-growing cloud-based services, the number of servers and
network devices in data centers is increasing exponentially, which in turn results in high …

Towards threshold‐agnostic heavy‐hitter classification

A Pekar, A Duque‐Torres, WKG Seah… - … Journal of Network …, 2022 - Wiley Online Library
A heavy‐hitter (HH) network traffic flow consumes considerably more network resources
than other flows combined. The classification of HHs is critical to provide, among others, the …