• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.327-346
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• 2013

Researchers as well as network providers are increasingly interested in understanding how a network user's experience changes in relation to different quality of service (QoS) parameters, with many attempts being made to identify the general relationship between quality of experience (QoE) and QoS. Several relations in different function forms have been proposed. There are instances when this variety of proposed functions potentially results in one problem having completely dissimilar solutions at the same time. The question then is which function form is the one that can better explain this relationship. In this paper, three major existing quantitative relationships between QoE and QoS are investigated. After conducting a comprehensive comparative analysis between them, a new definition of QoE-QoS dependency appears. It then results in identifying a new mutual relationship between QoE and QoS. The newly proposed relationship improves the deficiency of previous QoE-QoS relationships along with solving the problem of diversity of simultaneous solutions for one problem.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.229-234
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• 2021

The explosive growth of video-based services is considered as the dominant contributor to Internet traffic. Hence it is very important for video service providers to meet the quality expectations of end-users. In the past, the Quality of Service (QoS) was the key performance of networks but it considers only the network performances (e.g., bandwidth, delay, packet loss rate) which fail to give an indication of the satisfaction of users. Therefore, Quality of Experience (QoE) may allow content servers to be smarter and more efficient. This work is motivated by the inherent relationship between the QoE and the QoS. We present a no-reference (NR) prediction model based on Deep Neural Network (DNN) to predict video QoE. The DNN-based model shows a high correlation between the objective QoE measurement and QoE prediction. The performance of the proposed model was also evaluated and compared with other types of neural network architectures, and three known machine learning methodologies, the performance comparison shows that the proposed model appears as a promising way to solve the problems.

• Korean Management Science Review
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• v.33 no.3
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• pp.19-30
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• 2016

This study provides a framework to assess network design under the regime of QoE (Quality of Experience). Our approach is expected to reveal the necessity of developing the QoE measures and applying this notion to network design, particularly in the mobile environment. Furthermore, our model shows the ample potential that both users and network providers are able to attain a win-win case by shifting the focus on network design and service operations from QoS (Quality of Service) to QoE. Since the former considers only relevant technological specifications, it may fail in capturing critical factors surrounding users, such as a context where the corresponding user is working on. For example, according to one study [13], the bit-rate, a widely employed QoS measure, shows inferior performance in provisioning network resources to the MOS (Mean Opinion Score), a representative QoE measure. Our framework develops the idea and construct a prototype to systematically assess network design and operations in terms of QoE. The proposed prototype aims at achieving a higher level of efficiency without severely deteriorating users' satisfaction level. We also provide some simulation results which support our idea. That is, reducing the chance of over-provisioning on the basis of the QoE paradigm results in a great flexibility. It may give price cut for users or postponement of network investment for providers or both. Our simulation results also seem robust irrespective of the forms of the QoS-QoE relationship.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11B
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• pp.698-706
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• 2005

In this paper, we investigate the parameters of the IEEE 802.11e MAC protocol, CWmin and AIFS, in terms of their capability of QoS control. The delay and the bandwidth performances are selected as the QoS medics to examine the characteristics of those parameters. A policy on MAC parameters usage, thereby, is proposed. We regard the MAC-level traffic classification as the differentiation in the channel accessibility, and thus the delay differentiation is referred to a main issue of the class-level QoS control. Realizing the tight relationship between the delay performance and the parameter AIFS, we derive an analytical expression of their relationship through an analysis of the MAC mechanism. Various simulations are examined which show the validity of our assertions, and a policy on the parameters usage is proposed based on those observations.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.4
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• pp.491-498
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• 2014

As internet services are being provided through a wireless access, the importance of quality of experience (QoE) is stressed that is defined as the quality that indicates user's actual feeling when a service is provided. Unlike quality of service (QoS) that can be expressed as a numerical value, it is difficult to represent QoE in an objective way. If an internet service is serviced over a wireless channel, its QoE can be affected by a number of factors such as fading, mobility and so on. This paper, therefore, attempts to specify the relationship between QoE and QoS by conducting practical measurements for the voice service through 3G high speed packet access (HSPA) access network. Analysing the measured results, it has been shown that received signal strength indicator (RSSI) has a great influence on mean opinion score (MOS) through transmission delay.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.86-89
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• 1998

Multiple types of information in a multimedia service are delivered though multiple virtual connections on ATM network, while each virtual connection may be controlled independently. A multimedia service requires an associative relationship among multiple information streams to provide required harmonization. There may be required additional traffic descriptors to guarantee the required harmonization among multiple information streams in a multimedia service. For buffering of large bandwidth information stream(e.g., video), extremely large buffer size is necessary, but this approach should not be efficient way to compensate a severely delayed cells/blocks experienced at network. The best way to solve this problem will be minimization of relative-delayed-transfer of cells/blocks to application processes through ATM network control. To minimize a delayed transfer the mapping between relative delay parameter(i.e., associative Group QoS parameters) and per-VC traffic descriptor will be necessary. This paper is present additional functions and parameters to interpret the mapping between relative delay parameters(i.e., associative Group QoS parameters) and per-VC traffic descriptors in ATM API for multimedia application services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2513-2530
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• 2021

With the fast development of information and communication technologies, video streaming services and applications are increasing rapidly. However, the network condition is volatile. In order to provide users with better quality of service, it is necessary to develop an accurate and low-complexity model for Quality of Experience (QoE) prediction of time-varying video. Memory effects refer to the psychological influence factor of historical experience, which can be taken into account to improve the accuracy of QoE evaluation. In this paper, we design subjective experiments to explore the impact of Short-Term Memory (STM) on QoE. The experimental results show that the user's real-time QoE is influenced by the duration of previous viewing experience and the expectations generated by STM. Furthermore, we propose analytical models to determine the relationship between intrinsic video quality, expectation and real-time QoE. The proposed models have better performance for real-time QoE prediction when the video is transmitted in a fluctuate network. The models are capable of providing more accurate guidance for improving the quality of video streaming services.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.717-724
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• 2009

The most important issue for successful deployment of IPTV service is the service quality. In this paper, we first choose critical quality metrics belonging to each layer of IPTV service transmission architecture and then analyze the relation between the quality parameters. For this purpose, we implement a test network that emulates the most practical environment in which IPTV service is provided and repeat measurements on the test network for the chosen metrics. Based on the analysis result, it is shown that packet losses have greater effect on the video quality of IPTV service comparing to delay and jitter.