QoE prediction model for multimedia services in intelligent transport system / Oche Michael
Vehicular ad hoc networks (VANETs), present an intriguing platform for applications like Intelligent Transportation System (ITS), Infotainment applications including but not limited to, live video streaming, file sharing, mobile office advertisements and even distributed computer games. These concei...
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2016
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| Online Access: | http://studentsrepo.um.edu.my/6175/4/oche.pdf http://studentsrepo.um.edu.my/6175/ |
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| _version_ | 1831434522686652416 |
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| author | Oche, Michael |
| author_facet | Oche, Michael |
| author_sort | Oche, Michael |
| building | UM Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaya |
| content_source | UM Student Repository |
| continent | Asia |
| country | Malaysia |
| description | Vehicular ad hoc networks (VANETs), present an intriguing platform for applications like Intelligent Transportation System (ITS), Infotainment applications including but not limited to, live video streaming, file sharing, mobile office advertisements and even distributed computer games. These conceivable ITS and infotainment applications aspire to be a prevalent mode of communication among vehicles while on the road. However, Impact of such anticipated increased in communication among vehicles, is bound to have increased contention on communication links resulting in variable service quality for different applications. A mechanism is needed to manipulate the allocation of the network resources to meet these application traffic demands. Before now, the most prominent approach used to differentiate network traffic flow was Quality of Service (QoS). But then, QoS mainly focuses on objective measurement of network parameter such as jitter, throughput, loss and delay, but pay less attention to how users of the network perceived the service delivery quality. Studies have shown that the traditional QoS approach for evaluating network service quality is not sufficient, and so calls for a more exhaustive and comprehensive quality assessment approach that is not entirely based on network parameter measurement, but one that also include the end user perception of service quality. This quality assessment approach is known as Quality of Experience (QoE). Though, absolute QoE assessment requires a subjective approach, however, performing a subjective test to evaluate the quality of real-time multimedia services is expensive in terms of time and resources and hard to carry out in real-time. The process involves in subjective approach requires a controlled environment, such controlled environment is not realistic in a complex network environment such as VANETs. Therefore, the
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only practical solution during service operation is to apply an objective quality assessment model, which produces an estimate of the perceived quality without human involvement. Hence, in this thesis, a QoE prediction model that estimates the QoE of ITS multimedia services over VANETs objectively, was proposed. The proposed model is based on a state space approach and advanced statistics method, in conjunction with ordinal regression analysis, that estimates the perceived ITS multimedia service quality as a function of aggregated QoE influential factors. The multimedia/ITS distribution network was segmented into a theoretical explanation of three quality optimization component, to develop a QoE optimization function, which takes into consideration the service source quality, the network resource constraint and the human and context factors in defining the overall QoE. The result indicates to be promising, as the proposed model exhibits good predictive power that is coherent with the observed data |
| format | Thesis |
| id | my.um.stud-6175 |
| institution | Universiti Malaya |
| publishDate | 2016 |
| record_format | eprints |
| spelling | my.um.stud-61752019-09-09T20:11:19Z QoE prediction model for multimedia services in intelligent transport system / Oche Michael Oche, Michael QA76 Computer software Vehicular ad hoc networks (VANETs), present an intriguing platform for applications like Intelligent Transportation System (ITS), Infotainment applications including but not limited to, live video streaming, file sharing, mobile office advertisements and even distributed computer games. These conceivable ITS and infotainment applications aspire to be a prevalent mode of communication among vehicles while on the road. However, Impact of such anticipated increased in communication among vehicles, is bound to have increased contention on communication links resulting in variable service quality for different applications. A mechanism is needed to manipulate the allocation of the network resources to meet these application traffic demands. Before now, the most prominent approach used to differentiate network traffic flow was Quality of Service (QoS). But then, QoS mainly focuses on objective measurement of network parameter such as jitter, throughput, loss and delay, but pay less attention to how users of the network perceived the service delivery quality. Studies have shown that the traditional QoS approach for evaluating network service quality is not sufficient, and so calls for a more exhaustive and comprehensive quality assessment approach that is not entirely based on network parameter measurement, but one that also include the end user perception of service quality. This quality assessment approach is known as Quality of Experience (QoE). Though, absolute QoE assessment requires a subjective approach, however, performing a subjective test to evaluate the quality of real-time multimedia services is expensive in terms of time and resources and hard to carry out in real-time. The process involves in subjective approach requires a controlled environment, such controlled environment is not realistic in a complex network environment such as VANETs. Therefore, the iv only practical solution during service operation is to apply an objective quality assessment model, which produces an estimate of the perceived quality without human involvement. Hence, in this thesis, a QoE prediction model that estimates the QoE of ITS multimedia services over VANETs objectively, was proposed. The proposed model is based on a state space approach and advanced statistics method, in conjunction with ordinal regression analysis, that estimates the perceived ITS multimedia service quality as a function of aggregated QoE influential factors. The multimedia/ITS distribution network was segmented into a theoretical explanation of three quality optimization component, to develop a QoE optimization function, which takes into consideration the service source quality, the network resource constraint and the human and context factors in defining the overall QoE. The result indicates to be promising, as the proposed model exhibits good predictive power that is coherent with the observed data 2016 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/6175/4/oche.pdf Oche, Michael (2016) QoE prediction model for multimedia services in intelligent transport system / Oche Michael. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/6175/ |
| spellingShingle | QA76 Computer software Oche, Michael QoE prediction model for multimedia services in intelligent transport system / Oche Michael |
| title | QoE prediction model for multimedia services in intelligent transport system / Oche Michael |
| title_full | QoE prediction model for multimedia services in intelligent transport system / Oche Michael |
| title_fullStr | QoE prediction model for multimedia services in intelligent transport system / Oche Michael |
| title_full_unstemmed | QoE prediction model for multimedia services in intelligent transport system / Oche Michael |
| title_short | QoE prediction model for multimedia services in intelligent transport system / Oche Michael |
| title_sort | qoe prediction model for multimedia services in intelligent transport system / oche michael |
| topic | QA76 Computer software |
| url | http://studentsrepo.um.edu.my/6175/4/oche.pdf http://studentsrepo.um.edu.my/6175/ |
| url_provider | http://studentsrepo.um.edu.my/ |