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Study and Analysis of Various Load Balancing Techniques for Software-Defined Network (A Systematic Survey)

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Proceedings of International Conference on Big Data, Machine Learning and their Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 150))

Abstract

The interconnections between persons, organizations and various entities are possible only because of information communication technology (ICT). ICT changes the era into digital world. In this digital world, all things are possibly connected to each other through ICT and makes possible the concept of Internet of things (IoT). To implement these concepts, the computer network plays a vital role. But, the traditional IP network is difficult to manage, complex and rigid to configure the network according to the change of the organization’s policies. The traditional computer network is also difficult to handle the fault, load and changes because the data plane and control plane are integrated. Therefore, the idea of software-defined networking (SDN) Fei et al. (IEEE Commun Surv Tutor 16(4):2181–2206, 2014, [1]) is a flourishing field to solve the issues of traditional computer network. SDN vows to change the traditional network by segmenting the planes of networking into two separate planes as data plane and control plane. SDN makes it simpler to create and present abstraction and simplifying in networking. There are different functionalities provided by the SDN, for example, traffic engineering, load balancing, routing, intrusion detection, security and so on. Load balancing is one of them. This paper is analyzing the concept and evolution of SDN and further emphasis on the concept of load balancing. Further, analysis and comparison of various load balancing techniques are also given in this text. This work gives the concept, evolution, analysis of the load balancing in SDN which may help to make it better, efficient and cost effective.

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Correspondence to Darpan Anand .

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Kumar, A., Anand, D. (2021). Study and Analysis of Various Load Balancing Techniques for Software-Defined Network (A Systematic Survey). In: Tiwari, S., Suryani, E., Ng, A.K., Mishra, K.K., Singh, N. (eds) Proceedings of International Conference on Big Data, Machine Learning and their Applications. Lecture Notes in Networks and Systems, vol 150. Springer, Singapore. https://doi.org/10.1007/978-981-15-8377-3_28

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