Performance Evaluation of Software Defined Networking vs. Traditional Networks

Authors

  • M.I. Lali University of Gujrat, Gujrat
  • R.U. Mustafa COMSATS Institute of Information Technology, Sahiwal Campus
  • F. Ahsan HITEC University, Taxila
  • M.S. Nawaz School of Mathematical Sciences, Peking University, Beijing, China
  • W. Aslam The Islamia University of Bahawalpur, Bahawalpur

Abstract

 

Emerging mega trends in Information and Communication Technology (ICT) and many Internet applications have offered new challenges to future Internet, of which dynamic management and high bandwidth rank high. High bandwidth needed for transporting huge data cannot be realized with traditional networking methods, wherein configurations of devices are carried out manually and capability of network infrastructure is not fully utilized. Software Defined Networking (SDN) is an emerging solution for such problems. In this article, we analyze the performance of SDN using its standard OpenFlow protocol by considering a scenario of medium enterprise data center. Performances of SDN are executed for parameters such as latency, packet delivery ratio and processing overhead in various topologies using simulations carried out in Mininet. Results indicate significant performance improvements of SDNs over traditional networks.

Author Biographies

M.I. Lali, University of Gujrat, Gujrat

Department of Computer Science

R.U. Mustafa, COMSATS Institute of Information Technology, Sahiwal Campus

Department of Computer Science

F. Ahsan, HITEC University, Taxila

Department of Computer Science and Engineering

M.S. Nawaz, School of Mathematical Sciences, Peking University, Beijing, China

Department of Information Science

W. Aslam, The Islamia University of Bahawalpur, Bahawalpur

Department of Computer Science & IT

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Published

30-03-2017

How to Cite

[1]
M. Lali, R. Mustafa, F. Ahsan, M. Nawaz, and W. Aslam, “Performance Evaluation of Software Defined Networking vs. Traditional Networks”, The Nucleus, vol. 54, no. 1, pp. 16–22, Mar. 2017.

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Articles