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Intelligent load balancing techniques in software defined networks: A systematic review
Proc. - IEEE Int. Symp. Sustain. Energy, Signal Process. Cyber Secur., iSSSC ; 2020.
Article in English | Scopus | ID: covidwho-1142839
ABSTRACT
In the current era of technology, the number of users connecting to the internet has increased rapidly. If the situation is like Pandemic (COVID-19), the demand of the data services is much higher than the expectation. The major problem of this situation is load management. SDN plays an important role in this regard. Being a programmable network, it is widely admirable for its network intelligence. In this paper, we discuss SDN architecture, its components, various applications and major challenges. The unique architecture differentiates SDN from traditional network. It makes it possible to take routing decision without depending upon the underlying architecture. We also present a systematic review on the study of the different load balancing approaches, existing solutions and various load balancing techniques in SDN. With the network intelligence, SDN is able to take the load balancing decision. We categorize the load balancing techniques based on controller, server, communication path selection and cloud-based environment. Finally, we present different research challenges, existing solutions under each technique. © 2020 IEEE.

Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Reviews / Systematic review/Meta Analysis Language: English Journal: Proc. - IEEE Int. Symp. Sustain. Energy, Signal Process. Cyber Secur., iSSSC Year: 2020 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Reviews / Systematic review/Meta Analysis Language: English Journal: Proc. - IEEE Int. Symp. Sustain. Energy, Signal Process. Cyber Secur., iSSSC Year: 2020 Document Type: Article