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Cluster Computing

, Volume 22, Supplement 1, pp 241–254 | Cite as

Hybrid evolutionary computing algorithms and statistical methods based optimal fragmentation in smart cloud networks

  • K. Sasi Kala Rani
  • S. N. DeepaEmail author
Article

Abstract

A swift improvement in the development of technologies in this communication era has created an enormous traffic comprising of multimedia data to cloud networks. The multimedia applications are very sensitive to quality of service (QoS) parameters. The throughput of packets is proportionate to the quality of the received multimedia data. The aim of this paper is to improve the throughput of multimedia data particularly for the smart cloud networks by fragmenting the packets into optimal size. The optimal fragment size for standard encoding rates is calculated using soft computing algorithms and other encoding rates are calculated by regression using least squares method. An improvement in the throughput of packets and decrease in calculation time is demonstrated using experimental results and simulation.

Keywords

QoS Cloud networks Genetic algorithm Differential evolution Optimal fragmentation Least Squares method 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Hindusthan Institute of TechnologyCoimbatoreIndia
  2. 2.Anna University Regional CampusCoimbatoreIndia

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