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Software Defined Network: Load Balancing Algorithm Design and Analysis
        
        Software Defined Network (SDN) cut down the monopolies of producing network  devices and their applications. It 
allows  the  use  of  an  omniscient  controller  that manages  the  overall network  and promises for  simplifying  the  configuration 
and  management  burden  of  the  traditional Internet  Protocol (IP) network. The  use  of  hardware  load  balancer  is a critical 
issue  in conventional  IP networks  that  creates many  negative  impacts  such  as  the  cost  affordability,  features  customization, 
and  availability.  Also,  the  existing  load  balancing algorithm does  not  consider  the  flow  size  generated  by  the  client  nodes. 
Further,  flows are  not  classified  based  on the threshold  value  of the dynamic  flow  size. The  paper  proposes  to  compare  the 
performance  of  two  load  balancing  algorithms  such  as  flow-based  load balancing  algorithm  and  traffic  pattern-based  load 
balancing algorithm  with distributed controllers' architecture. The  result shows that the flow-based load balancing algorithm 
minimizes response  time  by  94%, enhances transaction rate  by  14% and  Traffic  pattern-based  load  balancing  algorithm  has 
improved availability by 2.69%.    
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[30] Zhong H., Fang Y., and Cui J., “LBBSRT: an Efficient SDN Load Balancing Scheme Based on Server Response Time,” Future Generation Computer Systems, vol. 68, pp. 183-190, 2017. 318 The International Arab Journal of Information Technology, Vol. 18, No. 3, May 2021 Senthil Prabakaran was born at Dindigul, India, in 1987. He graduated in Electronics and Communication Engineering from Anna University affiliated college and post graduated in Network Engineering from Kalasalingam Academy of Research and Education, Krishnankoil, India. He is pursuing his PhD in Electronics and Communication Engineering (Software Defined Networking) from Kalasalingam Academy of Research and Education. His research interest includes Computer Networks, Software Defined Networks, Cloud Computing, Network Function Virtualization and Network Security. Ramalakshmi Ramar received her Doctoral degree and Master of Engineering degree in Computer Science and Engineering. She has been working in the department of Computer Science and Engineering at Kalasalingam Academy of Research and Education (Previously known as Arulmigu Kalasalingam College of Engineering) since 2001. She has more than 20 years of teaching experience. She is a member of CSI, ISTE and Network Technology group of TIFAC- CORE in Network Engineering. She has published more than 25 research articles in reputed Journals and International Conferences. She has received Young Scientist Fellowship from Tamilnadu State Council for Science and Technology and Award of Excellence from SAP India Pvt. Limited. Her areas of research include Software Defined Networking, Cognitive Science, Internet of Things, Big Data Analytics and Social Network Analysis.