Comparison and Performance Evaluation of Software-Defined Networking Controllers

Bhardwaj, Shanu; Panda, S. N.; Muskaan,; Datta, Priyanka

doi:10.1109/esci48226.2020.9167554

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…The DL approach, in this case, refers (and is not limited) to architectures discussed in Section 5. SDN architectures, in this case, refer to the controller paradigm, whether it is distributed or centralized (Bhardwaj et al ., 2020). These parameters are critical in an SDN environment as they dictate the stability and scalability of the Network (Hamdan et al ., 2021).…”

Section: Resultsmentioning

confidence: 99%

“…One key characteristic that differentiates SDN from traditional networks is the centralization of network control, for which all control functionalities are abstracted and implemented in the SDN controller sitting in the control plane for operational decision-making (Bhardwaj et al , 2020). The data plane, which consists of SDN switches, only executes the instructions received from the control plane.…”

Section: Key Technologies and Architecturesmentioning

confidence: 99%

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Deep learning for SDN-enabled campus networks: proposed solutions, challenges and future directions

Chanhemo

Mohsini

Mjahidi

et al. 2023

IJICC

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PurposeThis study explores challenges facing the applicability of deep learning (DL) in software-defined networks (SDN) based campus networks. The study intensively explains the automation problem that exists in traditional campus networks and how SDN and DL can provide mitigating solutions. It further highlights some challenges which need to be addressed in order to successfully implement SDN and DL in campus networks to make them better than traditional networks.Design/methodology/approachThe study uses a systematic literature review. Studies on DL relevant to campus networks have been presented for different use cases. Their limitations are given out for further research.FindingsFollowing the analysis of the selected studies, it showed that the availability of specific training datasets for campus networks, SDN and DL interfacing and integration in production networks are key issues that must be addressed to successfully deploy DL in SDN-enabled campus networks.Originality/valueThis study reports on challenges associated with implementation of SDN and DL models in campus networks. It contributes towards further thinking and architecting of proposed SDN-based DL solutions for campus networks. It highlights that single problem-based solutions are harder to implement and unlikely to be adopted in production networks.

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Section: Resultsmentioning

confidence: 99%

Section: Key Technologies and Architecturesmentioning

confidence: 99%

Deep learning for SDN-enabled campus networks: proposed solutions, challenges and future directions

Chanhemo

Mohsini

Mjahidi

et al. 2023

IJICC

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“…To connect to Mininet vm via ssh, you must first obtain the IP address of Mininet vm using the command-line interface. [14] $ sudo dhclient eth1 $ sudo ifconfig eth1…”

Section: Mininetmentioning

confidence: 99%

Performance Comparison of the Proposed OpenFlow Network with the Pox Controller and the Traditional Network in Software Defined Networks (SDN)

Gautam¹,

Jha²,

Yadav³

2022

Artificial Intelligence and Communication Technologies

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The dynamic structure of today's networking system, in which the control plane is fully dispersed throughout the network and networking equipment (e.g., switches, routers) have their own local control-plane and data-plane, makes networking system management more complicated. Networking paradigm that can be programmed by separating the management function from the networking elements and putting it in a logically centralised control plane, SDN makes it simple to administer and operate this dynamic networking system. The forwarding devices are made easier by the separation of the control and data planes. A logically centralised control-plane is in charge of the control, management, and configuration of these simple forwarding devices.. SDN's control plane is frequently referred to as the network operating system. The purpose of this dissertation is to evaluate the performance of an OpenFlow enabled software defined network model with a POX controller to that of a traditional network. Mininet is a tool that is used to design and analyse traditional and programmable networks. Latency, throughput, packet loss, and jitter characteristics are used to evaluate performance.

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A Review of e‐Healthcare System of India and Thailand

Bhardwaj

Panda

Datta

et al. 2022

IoT‐Enabled Smart Healthcare Systems, Services and Applications

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Comparison and Performance Evaluation of Software-Defined Networking Controllers

Cited by 9 publications

References 17 publications

Deep learning for SDN-enabled campus networks: proposed solutions, challenges and future directions

Deep learning for SDN-enabled campus networks: proposed solutions, challenges and future directions

Performance Comparison of the Proposed OpenFlow Network with the Pox Controller and the Traditional Network in Software Defined Networks (SDN)

A Review of e‐Healthcare System of India and Thailand

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