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2022 ◽  
Author(s):  
Doğanalp Ergenç ◽  
Ertan Onur

AbstractControl and user (data) plane separation (CUPS) is a concept applied in various networking areas to scale network resources independently, increase the quality of service, and facilitate the autonomy of networks. In this study, we leverage this concept to design a plane-separated routing algorithm, CUPS-based hierarchical routing algorithm (CHRA), as an energy-efficient and low-latency end-to-end communication scheme for clustered ad-hoc networks. In CHRA, while cluster heads constitute the control plane to conduct network discovery and routing, ordinary nodes residing in the user plane forward packets according to the routing decisions taken by the control plane. Exploiting the CUPS, we avoid exhausting cluster heads by offloading packet-forwarding to ordinary nodes and improve the quality of service by utilizing alternative paths other than the backbone of cluster heads. Our simulation results show that CHRA offers a better quality of service in terms of end-to-end latency and data-to-all ratio, and promotes fairness in energy-consumption in both stationary and mobile scenarios.


Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 349
Author(s):  
Mohammad Al Shinwan ◽  
Laith Abualigah ◽  
Trong-Dinh Huy ◽  
Ahmed Younes Shdefat ◽  
Maryam Altalhi ◽  
...  

Reaching a flat network is the main target of future evolved packet core for the 5G mobile networks. The current 4th generation core network is centralized architecture, including Serving Gateway and Packet-data-network Gateway; both act as mobility and IP anchors. However, this architecture suffers from non-optimal routing and intolerable latency due to many control messages. To overcome these challenges, we propose a partially distributed architecture for 5th generation networks, such that the control plane and data plane are fully decoupled. The proposed architecture is based on including a node Multi-session Gateway to merge the mobility and IP anchor gateway functionality. This work presented a control entity with the full implementation of the control plane to achieve an optimal flat network architecture. The impact of the proposed evolved packet Core structure in attachment, data delivery, and mobility procedures is validated through simulation. Several experiments were carried out by using NS-3 simulation to validate the results of the proposed architecture. The Numerical analysis is evaluated in terms of total transmission delay, inter and intra handover delay, queuing delay, and total attachment time. Simulation results show that the proposed architecture performance-enhanced end-to-end latency over the legacy architecture.


2022 ◽  
Author(s):  
Yunfeng Lu ◽  
Huaxi Gu ◽  
Xiaoshan Yu ◽  
Peng Li

2021 ◽  
Author(s):  
Md. Rayhan Ahmed ◽  
salekul Islam ◽  
Swakkhar Shatabda ◽  
A. K. M. Muzahidul Islam ◽  
Md. Towhidul Islam Robin

<div>At present, the Internet is facing numerous attacks of different kinds that put its data at risk. The safety of information within the network is, therefore, a significant concern. In order to prevent the loss of incredibly valuable information, the Intrusion Detection System (IDS) was developed to recognize the outbreak of a stream of attacks and notify the network system administrator providing network security. IDS is an extrapolative model used to detect network traffic as routine or attack. Software-Defined Networks (SDN) is a revolutionary paradigm that isolates the control plane from the data plane, transforming the concept of a software-driven network. Through this data and control plane separation, SDN provides us the opportunity to create a manageable and programmable network, allowing applications in the top plane to access physical devices via the controller. The controller functioning inside the control plane executes network modules and establishes flow rules to forward packets in the switches residing in the data plane. Cyber attackers target the SDN controller to subdue the control plane, which is considered the brain of the SDN, providing a plethora of functionalities such as regulating flow control to switches or routers in the data plane below via southbound Application Programming Interfaces (APIs) and business and application logic in the application plane above via northbound APIs to implement sophisticated networks. However, the control plane becomes a tempting prospect for security attacks from adversaries because of its centralization feature. This paper includes an in-depth overview of the notable published articles from 2015 to 2021 that used Machine Learning (ML) and Deep Learning (DL) techniques to construct an IDS solution to provide security for SDN. We also present two detailed taxonomic studies regarding IDS, and ML-DL techniques based on their learning categories, exploring various IDS solutions to secure the SDN paradigm. We have also conducted brief research on a few benchmark datasets used to construct IDS in the SDN paradigm. To conclude the survey, we provide a discussion that sheds light on continuous challenges and IDS issues for SDN security.</div>


2021 ◽  
Author(s):  
Md. Rayhan Ahmed ◽  
salekul Islam ◽  
Swakkhar Shatabda ◽  
A. K. M. Muzahidul Islam ◽  
Md. Towhidul Islam Robin

<div>At present, the Internet is facing numerous attacks of different kinds that put its data at risk. The safety of information within the network is, therefore, a significant concern. In order to prevent the loss of incredibly valuable information, the Intrusion Detection System (IDS) was developed to recognize the outbreak of a stream of attacks and notify the network system administrator providing network security. IDS is an extrapolative model used to detect network traffic as routine or attack. Software-Defined Networks (SDN) is a revolutionary paradigm that isolates the control plane from the data plane, transforming the concept of a software-driven network. Through this data and control plane separation, SDN provides us the opportunity to create a manageable and programmable network, allowing applications in the top plane to access physical devices via the controller. The controller functioning inside the control plane executes network modules and establishes flow rules to forward packets in the switches residing in the data plane. Cyber attackers target the SDN controller to subdue the control plane, which is considered the brain of the SDN, providing a plethora of functionalities such as regulating flow control to switches or routers in the data plane below via southbound Application Programming Interfaces (APIs) and business and application logic in the application plane above via northbound APIs to implement sophisticated networks. However, the control plane becomes a tempting prospect for security attacks from adversaries because of its centralization feature. This paper includes an in-depth overview of the notable published articles from 2015 to 2021 that used Machine Learning (ML) and Deep Learning (DL) techniques to construct an IDS solution to provide security for SDN. We also present two detailed taxonomic studies regarding IDS, and ML-DL techniques based on their learning categories, exploring various IDS solutions to secure the SDN paradigm. We have also conducted brief research on a few benchmark datasets used to construct IDS in the SDN paradigm. To conclude the survey, we provide a discussion that sheds light on continuous challenges and IDS issues for SDN security.</div>


2021 ◽  
Author(s):  
Leonard Becker ◽  
Oliver Hohlfeld ◽  
Georgios Smaragdakis
Keyword(s):  

2021 ◽  
Author(s):  
Muhammad Taqi Raza ◽  
Yunqi Guo ◽  
Songwu Lu ◽  
Fatima Muhammad Anwar
Keyword(s):  

2021 ◽  
Author(s):  
Gereltsetseg Altangerel

By programming both the data plane and the control plane, network operators can customize their networks based on their needs, regardless of the hardware manufacturer. Control plane programming, a major component of the SDN (Software Defined Network) concept, has been developed for more than 10 years and successfully implemented in real networks. Efforts to develop reconfigurable data planes and high-level network programming languages make it truly possible to program data planes. Therefore, the programmable data planes and SDNs offer great flexibility in network customization, allowing many innovations to be introduced on the network. The general focus of research on the data plane is data-plane abstractions, languages and compilers, data plane algorithms, and applications. This paper outlines some emerging applications on the data plane and offers opportunities for further improvement and optimization.


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