Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network

Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network

Bibliographic Details
Main Author: Zhang, Jielun
Language:English
Published: University of Dayton / OhioLINK 2018
Subjects:
Electrical Engineering
network measurement
machine learning
application-aware
quality-of-experience
smart network
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=dayton1532582833701364
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-dayton15325828337013642021-08-03T07:07:53Z Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network Zhang, Jielun Electrical Engineering network measurement machine learning application-aware quality-of-experience smart network In this thesis, we propose to develop a secure and distributed network quality-of-experience (QoE) measurement for smart networks. Network measurement capability has been updated gradually as the network technology progresses. For example, software-defined network will enable efficient monitoring and control of the core network. However, end-to-end network QoE measurement requires distributed approaches from the user side. In our proposed measurement framework, a traffic measurement agent is deployed in the last-hop gateway. The gateway is equipped with new features, i.e., encrypted packet classifier, traffic prediction, and user quality-of-service (QoS) to QoE mappings. Since all measurement processes are done at the gateway, end user devices are separated from the entire process. Thus security can be provided by the proposed measurement framework. In addition to the framework, we demonstrate an efficient learning approach to develop the traffic prediction scheme and the QoS to QoE mapping scheme. Experiments results are provided to demonstrate that the developed schemes are applicable to a distributed network QoS measurement framework for smart networks. 2018-08-28 English text University of Dayton / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=dayton1532582833701364 http://rave.ohiolink.edu/etdc/view?acc_num=dayton1532582833701364 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Electrical Engineering
network measurement
machine learning
application-aware
quality-of-experience
smart network
spellingShingle Electrical Engineering
network measurement
machine learning
application-aware
quality-of-experience
smart network
Zhang, Jielun
Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network
author Zhang, Jielun
author_facet Zhang, Jielun
author_sort Zhang, Jielun
title Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network
title_short Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network
title_full Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network
title_fullStr Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network
title_full_unstemmed Application-aware Traffic Prediction and User-aware Quality-of-Experience Measurement in Smart Network
title_sort application-aware traffic prediction and user-aware quality-of-experience measurement in smart network
publisher University of Dayton / OhioLINK
publishDate 2018
url http://rave.ohiolink.edu/etdc/view?acc_num=dayton1532582833701364
work_keys_str_mv AT zhangjielun applicationawaretrafficpredictionanduserawarequalityofexperiencemeasurementinsmartnetwork
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