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Hybrid evolutionary computing algorithms and statistical methods based optimal fragmentation in smart cloud networks
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DOI：10.1007/s10586-017-1547-3.png)
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Abstract
En 中文
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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