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Load balancing strategy in software defined network by improved whale optimization algorithm.

Authors :
Darade, Santosh Ashokrao
Akkalakshmi, M.
Source :
Journal of High Speed Networks; 2021, Vol. 27 Issue 2, p151-167, 17p
Publication Year :
2021

Abstract

From the recent study, it is observed that even though cloud computing grants the greatest performance in the case of storage, computing, and networking services, the Internet of Things (IoT) still suffers from high processing latency, awareness of location, and least mobility support. To address these issues, this paper integrates fog computing and Software-Defined Networking (SDN). Importantly, fog computing does the extension of computing and storing to the network edge that could minimize the latency along with mobility support. Further, this paper aims to incorporate a new optimization strategy to address the "Load balancing" problem in terms of latency minimization. A new Thresholded-Whale Optimization Algorithm (T-WOA) is introduced for the optimal selection of load distribution coefficient (time allocation for doing a task). Finally, the performance of the proposed model is compared with other conventional models concerning latency. The simulation results prove that the SDN based T-WOA algorithm could efficiently minimize the latency and improve the Quality of Service (QoS) in Software Defined Cloud/Fog architecture. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09266801
Volume :
27
Issue :
2
Database :
Complementary Index
Journal :
Journal of High Speed Networks
Publication Type :
Academic Journal
Accession number :
151802814
Full Text :
https://doi.org/10.3233/JHS-210657