A Heuristic Approach for Optimizing Performance in Software-Defined Networks
P.R.RUPASHINI
, A.SUBASHINI , L.BABITHA , V.BHUVANESWARI
ANN, Evolutionary Optimization, SDN, Genetic Algorithms, ESFLA
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.
"A Heuristic Approach for Optimizing Performance in Software-Defined Networks", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.2, Issue 6, page no.77-80, June-2017, Available :https://ijnrd.org/papers/IJNRD1706013.pdf
Volume 2
Issue 6,
June-2017
Pages : 77-80
Paper Reg. ID: IJNRD_170080
Published Paper Id: IJNRD1706013
Downloads: 000118796
Research Area: Engineering
Country: Coimbatore, Tamil Nadu, India
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
