UGC approved journal IJNRD Research Journal

An International Open Access Journal |   ISSN: 2456-4184  

Call For Paper

Issue: February 2021

Volume 6 | Issue 2

Submit Paper Online

Click Here For more Details

For Authors

Forms / Download

Editorial Board

Subscribe IJNRD

Visitor Counter

Published Paper Details
Paper Title: A Heuristic Approach for Optimizing Performance in Software-Defined Networks
Author Reg. ID:
Published Paper Id: IJNRD1706013
Published In: Volume 2 Issue 6, June-2017
Abstract: Another half breed clever approach for enhancing the execution of Software-Defined Networks (SDN), in light of heuristic advancement techniques coordinated with Artificial Neural Network (ANN) worldview is exhibited. Evolutionary Optimization techniques, such as Shuffled Frog Leap Algorithm (SFLA) and Genetic Algorithms (GA) are employed to find the best set of inputs that give the maximum performance of an SDN. The Neural Network model is trained and applied as an approximator of SDN behavior. An analytical investigation has been conducted to distinguish the optimal optimization approach based on SDN performance as an objective function as well as the computational time. After getting the general model of the Neural Network through testing it with unseen data, this model has been implemented with SFLA and GA to find the best performance of SDN. The SFLA approach combined with SDN, represented by ANN, is identified as a comparatively better configuration regarding its performance index as well as its computational efficiency.
Keywords: ANN, Evolutionary Optimization, SDN, Genetic Algorithms, ESFLA
Cite Article: "A Heuristic Approach for Optimizing Performance in Software-Defined Networks", International Journal of Novel Research and Development (, ISSN:2456-4184, Vol.2, Issue 6, page no.77-80, June-2017, Available :
Downloads: 00041206
Share Article:

Click Here to Download This Article

Article Preview

ISSN Details

DOI (A digital object identifier)

Providing A digital object identifier by DOI

Conference Proposal

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media