Investigation of the IoT network of packet loss s long-range dependence and QoE

Joint Event on 5^th World Machine Learning and Deep Learning Congress and World Congress on Computer Science, Machine Learning and Big Data

August 30-31, 2018 Dubai, UAE

Jin Wang and Yi bin Hou

Beijing University of Technology, China

Posters & Accepted Abstracts: J Comput Sci Syst Biol

Abstract :

The Internet of Things includes internet technology, wired and wireless networks. Internet of Things and the internet is the relationship between the parent and the child. In this paper, we aim to study the investigation on the network packet lossâ??s longrange dependence and QOE and gain a good result and conclusion. In order to better establish no-reference video quality assessment model considering the network packet loss and further gain a better QoE evaluation, so we build NS2 ï?« MyEvalvid simulation platform to study the scale characteristic of the network packet loss, scale characteristic of packet loss through the influence of packet loss rate to influence QoE. The experimental results show that, packet loss processes have long-range dependence, the number of superimposed source N, shape parameter, Hurst parameter, the output link speed have impacts on long-range dependence. We came to the conclusion that when superimposed source N is more, the shape parameter is smaller, Hurst parameter is bigger, the output link speed is smaller, packet lossâ??s long range dependence is larger and packet loss rate is high.

Biography :

Jin Wang has completed her Bachelor’s degree in Software Engineering from Beijing University of Chemical Technology, Beijing, China and won the National Scholarship in 2010 and won the National Endeavor Fellowship in 2009. She has completed her Master’s degree in Computer Application Technology from Shijiazhuang Tiedao University. She had published many papers, including ISTP, EI and SCI and has also participated in three national natural science fund project.

E-mail: 805372192@qq.com