An Intelligent Congestion Control Method in Software Defined Networks

Zhao, Jihong; Tong, Mengfei; Qu, Hua; Zhao, Jing

doi:10.1109/iccsn.2019.8905364

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…Network management for SD-IoT: With the increasing use of IoT devices, there is a need for suitable technologies to manage the massive amounts of data generated by these devices. SDN-based technologies can help distribute and monitor network traffic flows for load balancing and network delay minimization [64].…”

Section: Issues and Challenges In Sdn-based Load Balancingmentioning

confidence: 99%

Review of SDN-based load-balancing methods, issues, challenges, and roadmap

Chandra Saxena,

Sabharwal,

Bajaj

2023

Int. j. electr. comput. eng. syst. (Online)

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The development of the Internet and smart end systems, such as smartphones and portable laptops, along with the emergence of cloud computing, social networks, and the Internet of Things, has brought about new network requirements. To meet these requirements, a new architecture called software-defined network (SDN) has been introduced. However, traffic distribution in SDN has raised challenges, especially in terms of uneven load distribution impacting network performance. To address this issue, several SDN load balancing (LB) techniques have been developed to improve efficiency. This article provides an overview of SDN and its effect on load balancing, highlighting key elements and discussing various load-balancing schemes based on existing solutions and research challenges. Additionally, the article outlines performance metrics used to evaluate these algorithms and suggests possible future research directions.

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Section: Issues and Challenges In Sdn-based Load Balancingmentioning

confidence: 99%