QoS analysis and evaluations: Improving cellular-based distance education

Voice over IP (VoIP) is nowadays a common component of multimedia converged networks. In this paper, Quality of Service (QoS) analysis of VoIP traffic is presented in a multimedia network having other types of network traffic also deployed i.e. video, database and web. In such traffic occupied network, VoIP is configured with different codecs and frame counts per packet to observe the effect of these variations on the QoS of VoIP in terms of queuing delay, jitter, packet end-to-end delay and packet delay variation (end-to-end jitter) metrics. The significance of this paper is the emphasis on QoS evaluations in a VoIP deployment while observing the effects of variations in voice codecs and packet lengths. Many previous research papers focus on the perceived speech quality and packet losses; whereas queuing delays and end-to-end latency are usually not considered when analysis is done for different codecs and packet lengths at a time. We consider three main voice codecs (G.711, G.729 and G.723.1) and three frame counts per packet values (10, 25 and 50 voice frames per packet) under each codec. The simulation results show that G.723.1 voice encoding experiences higher queuing delays and queue delay variations (jitter) for higher numbers of frames per packet. However, the least packet end-to-end delay is observed in voice packets encoded with G.729 codec for all configured values of frames per packet.

The quality of service (QoS) is an important factor for networks; guarantee the QoS in network is then very important for the network performance. Anyway, the research on the accurately evaluation on QoS is still lacked. In this paper, we employ the computational learning theory to study this problem and present the QoS evaluation model. Then the QoS evaluation scheme base on support vector machine (SVM) is proposed. Simulation results show that our propose scheme is more effective and improve the performance of the QoS evaluation.

The paper aims at exploring the shoppers’ evaluation of service quality and its impact on shopping centre management. For shopping centre management team, understanding their customers’ perceptions of the centre’s service quality is an important issue as shoppers’ evaluations and perceptions is believed to be highly related to their patronage behaviors and purchase intention. Through a case study of a shopping centre, this research will try to offer some insights on the relationships between evaluations of service quality and the shoppers’ patronage behaviors which may derive some implications for contemporary shopping centre management.
\n
\nLiteratures tell us that people elicit behavior after cognitive processing and formation of emotions. Adopting similar concept, marketing scholars found that customer behaviors are affected by their evaluations of service quality and satisfaction level through their perceptions on product or service attributes in cognitive processing. This study will follow the direction with reference to this model of behavior formation.
\n
\nIn the case study, personal interviews had been conducted with selected shoppers at a shopping centre. They were asked to rate the performance of 36 sub-attributes of the shopping centre under 5 shopping centre attributes, namely “accessibility”, “merchandise”, “retail environment & design”, “services of centre’s staff” and “promotions”. They were also asked about their patronage behaviors at the shopping centre such as frequency of visits, duration of visits, amount of spending etc.
\n
\nIt was found that the shoppers generally had positive evaluations on the centre’s performance on the 5 shopping centre attributes as a whole, especially had high evaluations on “accessibility”, “merchandise” and “services of centre’s staff”. Importance-performance analysis (IPA) was conducted to evaluate the service quality of 36 sub-attributes by comparing shoppers’ perceived actual performance and the importance level. It was found that only 8 sub-attributes, such as “access by public transportation”, “variety of stores” and “quality of stores” were found with high perceived service quality with high perceived actual performance and high importance level to the shoppers compared with other sub-attributes.
\n
\nThese sub-attributes with high perceived service quality were tested with occurrence tendency of patronage behaviors in the correlation analysis. It was found that high perceived service quality on merchandises, facility management and organization of promotion activities to certain extend had influence on manipulating patronage behaviors. However, some results showed that sub-attributes with high perceived service quality showed minimal or even no correlation on any measure patronage behavior parameters.
\n
\nWith reference to the model of purchase behavior regarding perceptions of service quality, the study may reveal that many possible antecedents of formation of shopping centre patronage behaviors may be still unreached in the contemporary studies.

The quality perceived by the user, a concept known as Quality of user Experience (QoE), is gaining momentum. Together with the efforts of providing appropriate architectures able to deliver the expected level of Quality of Service (QoS), users' perception of the level of quality could play a key role in making a VoIP multimedia application to succeed or to fail. QoE can be measured from different approaches; subjective ones are based on polls while objective ones are mainly based on QoS network performance parameters. Although a subjective evaluation could be costly and time consuming, it gives the most accurate results. Moreover, wireless environments incorporate new challenges in terms of QoS and QoE because of inherent wireless communication characteristics. In this way, our contribution is twofold. First, we carry out a subjective QoE assessment for VoIP applications in a real wireless environment. Skype, Gizmo5, ooVoo, and Damaka are the selected VoIP applications under study. Next, we contrast QoE results with QoS evaluation from the captured video calls made during the poll. Results show that there is no precise match on both assessments, because of QoE parameters that cannot be inferred from QoS analysis, because of the different effect of some QoS parameters which prevail, or even because of the popularity of the VoIP application.

In an era of rapid urbanization, the quality of network services in urban environments is becoming increasingly important. This article explores efforts to improve network service quality in several sampang cities through an evaluation of Quality of Service (QoS) and user perceptions of Quality of Experience (QoE). The research is based on a survey conducted at various locations in sampang city to collect data on the reliability, speed, and availability of network services. The survey involved a diverse sample of users, covering a wide range of ages, professions, and levels of technology usage. In addition, we also analyzed users' perceptions of service quality based on their experiences of using the network in an urban environment. The results highlighted several key challenges in improving QoS, such as user density, signal interference, and network infrastructure limitations. However, we also found that strategies such as the use of advanced network technologies, such as 5G and beamforming, as well as traffic prioritization based on application type, can help to significantly improve QoS. In addition, we found a strong positive correlation between improved QoS and improved QoE, suggesting that improved quality of service has a direct impact on improving user experience. These findings provide valuable insights for network operators and policy makers in their efforts to improve network services in dense urban environments. The research also recommends further investment in network technologies and the development of policies that support more effective management of network traffic to ensure optimal quality of service.

During the last few years, there has been significant interest in service quality issues, in general, and the quality of athletic services, in particular. The aim of this research was to see whether the 10 dimensions for the evaluation of service quality of Parasuraman, Zeithaml and Berry (1985) could be modified and used to evaluate the service quality of an athletic camp. The sample consisted of 369 participants, aged from 9‐18 years old athletes, and 126 parents. The questionnaire, which was created with the use of the 10 dimensions, consisted of 28 closed and 4 open questions (for the children's questionnaire) and 29 closed and 2 open questions (for the parents’ questionnaire). Factor analysis and Alpha Reliability test found out that there are 5 ("Training program”, “Contentment ‐ Intention”, “Safety & convenience in the facilities”, “Tangibles” and “Relations with the coaches") factors for the children and 4 factors for the parents ("Accommodation installations”, “Coaches'”, “Contentment ‐ Intention” and “Access ‐ Communication") that really affect them when they come to decide which camp to participate in/send their children to. These factors are the ones that the managers/directors of the athletic camps should take into consideration when offering their service.

Improving network quality and the effectiveness of digital infrastructure maintenance play an important role in supporting the achievement of the Sustainable Development Goals (SDGs). Through Quality of Service (QoS) analysis and network maintenance strategies at Diskominfo Bengkayang, this study shows that network quality generally meets ITU-T G.114 and Cisco standards, with a throughput of 6721 kb/s, packet loss of 0.200%, latency of 17.250699 ms, and jitter of 17.261801 ms. However, packet loss still exceeds the ideal limit (2%), which can affect the stability of digital services. The maintenance strategy implemented includes preventive and corrective maintenance, with an average recovery time of 1-3 hours. The main obstacles include limited technical human resources, lack of a real-time monitoring system, and the use of old network devices. This network quality improvement contributes to the achievement of SDG 9 (reliable infrastructure supporting the digitization of government services), SDG 11 (development of smart cities in Bengkayang), and SDG 17 (partnership with ISPs, academics, and the private sector). This research recommends the use of more comprehensive QoS parameters and infrastructure improvements to support better digital services in the future.

IEEE 802.11과 같은 무선 LAN 환경에서 실시간 멀티미디어 통신이 전송 데이터의 많은 부분을 차지하면서 성능 문제와 함께 네트워크의 QoS(Quality of Service)가 중요한 문제로 대두되고 있다. 802.11e MAC(Medium Access Control)은 기존 802.11 MAC의 문제를 해결하기 위해 우선순위 기반의 차별화 서비스를 제공한다. 특히 각 스테이션의 TXOP(Transmission Opportunity)는 한 번에 여러 프레임을 전송할 수 있는 시간을 규정하며 Priority와 함께 네트워크 성능 및 QoS 향상에 중요한 요소가 된다. 따라서 본 논문에서는 스테이션 수의 변화에 따라 네트워크의 최대 성능을 위한 프레임 사이즈와 TXOP, 그리고 Priority 값을 분석하고 최적의 값을 도출한다. 802.11e 표준 파라미터를 사용하여 시뮬레이션을 수행한 결과 Throughput은 스테이션의 수가 5일 때, TXOP Limit의 값이 6.016ms 일 때 가장 좋은 결과를 보였고 공정성은 TXOP Limit의 값이 3.008ms이고 Priority는 우선순위가 가장 높은 CW(Contention Window) 값이 7-15일 때가 아니고 그보다 낮은 CW 15-31일 때 가장 좋은 결과를 나타내었다. Since multimedia data takes large part of realtime transmission in wireless communication environments such as IEEE 802.11, QoS issues became one of the important problems with network performance. 802.11e MAC provides differentiated services based on priority schemes to solve existing 802.11 MAC problems. The TXOP is an important factor with the priority to improve network performance and QoS because it defines the time duration in which multiple frames can be transferred at one time for each station. In this paper, therefore frame sizes, TXOP Limit, and Priority values in accordance with the number of stations are experimented and derived for best network performance and QoS. Using 802.11e standard parameters, simulation results show the best throughput when the number of stations is 5 and TXOP Limit value is 6.016ms. For fairness, the best result is achieved at 3.008ms of TXOP Limit value and 15-31 of CW(Contention Window) that is lower priority than CW 7-15.

Wireless Sensor Networks (WSNs) comprise of groups of tiny sensor nodes that are deployed for collaborative missions such as environmental monitoring, target tracking and surveillance. Due to the miniature size of the nodes, they are typically deployed in large numbers and communicate via multiple hops through a wireless shared communication channel. The successful implementation of such networks is dependent on the enabling technologies (such as digital electronics and wireless communications), as well as the provisioning of Quality of Service (QoS) in the network. While there have been many efforts in QoS provisioning in traditional networks such as the Internet and Mobile Ad Hoc Networks (MANETs), these networks have very different characteristics from that of WSNs. Consequently, the QoS models and protocols that have been designed for the Internet and MANETs cannot be directly applied to WSNs. In this paper, we look at some of the existing QoS mechanisms in the networking literature, and the inherent characteristics of WSNs which make it challenging to provision for QoS in the network. We then identify some key performance metrics for WSN QoS and outline some mechanisms to achieve QoS in the sensor network. Finally, we propose WISER - a framework to enhance QoS in WIreless SEnsoR networks.

Introduction and penetration of high-speed and innovative mobile data services including social media and video services have been increasing significantly across the globe. This growth is driven by deployment and availability of capable and affordable mobile networks and smartphones. These trends have also been observed in Ethiopia as the country’s sole incumbent operator ethio telecom has expanded coverage and capacity of its mobile data network, especially for universal mobile telecommunications system (UMTS) network. The successful provision of these innovative services requires mobile operators to have continuous monitoring of the quality of their networks and customer satisfaction. To that end, this monitoring allows the operator to make timely network optimization, marketing and other relevant decisions that enhance service quality. Traditionally measurement and analysis of network quality of service (QoS) is performed using data from network management system (NMS) and drive/walk test (DT/WT). In recent times, the usage QoS data from crowdsourcing (CS) is also emerging as useful monitoring tool. However, all these methods do not fully capture users’ quality of experience (QoE), which is a function of not only network QoS but also other factors including subjective users’ technical literacy and opinion. As a result, operators have recently provided attention not only for QoS but also QoE. Yet, most quality related analyses are performed using data from only subjective survey, NMS, DT/WT, or CS. It is not straightforward to find quality investigation based on data from all the methods. More importantly, such quality investigation has not been made in the context of Ethiopia’s mobile market. In this paper, we perform QoS and QoE evaluation for UMTS mobile data service based on quality data from all NMS, WT, CS and subjective survey for a business area in Addis Ababa. The evaluation is made using downlink user throughput and mean opinion score (MOS) metrics. The obtained 50th percentile throughput results from NMS, WT and CS are good enough for web browsing and offline video streaming but not for high definition (HD) video calls and live HD video streaming. Furthermore, CS provides optimistic results compared to NMS and WT and its 90th percentile throughput is very good even for live HD video streaming. Moreover, the obtained MOS results from subjective survey almost fit to the QoS results, thus indicating that the network QoS is a significant contributor to users’ perceived QoE.

The relationship between the user perceived Quality of Experience (QoE) with Internet applications and the Quality of Service (QoS) of the underlying network and applications is complex. Unveiling statistical relations between QoE and QoS can boost the prediction and diagnosis of QoE. In this paper, we shed light on the relationship between QoE and QoS for a popular application: YouTube video streaming. We conducted a controlled study where we asked users to rate their perceived quality of YouTube videos under different network conditions. During this experiments, we also captured network QoS and application QoS. We then analyze the resulting dataset with SES, a feature selection algorithm that identifies multiple, minimal-size, statistically-equivalent signatures with maximal predictive power for a target variable (e.g., QoE). We found that we can build optimal QoE predictors using a minimal signature of only three features from application or network QoS metrics compared to four when we consider features from both layers.

The Quality of Service (QoS) evaluation techniques are required because web services having same functional properties are not a guarantee to have the same quality. This paper deals with a new QoS evaluation method for web services. The objective of the proposed approach is to offer the use of the existing QoS evaluation/assessment methods in constructing a new contextual QoS evaluation approach. The proposed approach is a multi-layer technique specified with the MAP formalism. The principle of the proposed contextual-oriented modelling approach is to guide the evaluator during all web services evaluation steps using different methodologies at varied levels of abstractions. A better understanding of the major web services quality factors that affect QoS will help QoS evaluators to judge the most appropriate QoS evaluation approach corresponding to their user and business requirements with more flexibility in personalising the QoS evaluation process.

Cloud systems are transforming the Information Technology trade by facultative the companies to provide admission to their structure and also software products to the membership foundation.Because of the vast range within the delivered Cloud solutions, from the customer's perspective of an aspect, it's emerged as troublesome to decide whose providers they need to utilize and then what's the thought of his or her option.Especially, employing suitable metrics is vital in assessing practices.Nevertheless, to the most popular of our knowledge, there's no methodical explanation relating to metrics for estimating Cloud products and services.QoS (Quality of Service) metrics playing an important role in selecting Cloud providers and also optimizing resource utilization efficiency.While many reports have got to devote to exploitation QoS metrics, relatively not much equipment supports the remark and investigation of QoS metrics of Cloud programs.To guarantee a specialized product is published, describing metrics for assessing the QoS might be an essential necessity.So, this text suggests various QoS metrics for service vendors, especially thinking about the consumer's worry.This article provides the metrics list may stand to help the future study and also assessment within the field of Cloud service's evaluation.

In order to improve the public transit's accessibility and promote service quality of the public transit, it is necessary to alleviate the 'last-mile' problem. The combination of the public transit and bicycle-sharing system is competitive compared with the private car. In 2016, the dockless bicycle-sharing system has been undergoing tremendous development. Because the dockless bicycle-sharing system is different from previous bicycle-sharing systems, components of service quality of the dockless bicycle-sharing system differ. However, there are few articles about the service quality of the dockless bicycle-sharing system. This paper examined the evaluation of service quality of the dockless bicycle-sharing system along with a measurement of users' satisfaction. A questionnaire about service quality was designed, which includes 15 factors. Through the analysis of travelers' evaluation of factors of the dockless bicycle-sharing system with Rasch Model, these original ordinal data (Likert data) was transformed to the interval data: the person parameter (ability) and the item parameter (difficulty). Through the analysis of interviewees' abilities, it was found that only education and monthly consumption have significant influence on interviewees' evaluation of service quality of the dockless bicycle-sharing system, while there is no significant influence of gender, weekly use of dockless shared-bicycle, private car ownership, or monthly income on the evaluation. Furthermore, it was found that users were dissatisfied with cycling under the adverse weather, disturbance from pedestrians and cars, continuity of the bicycle lane, complaint channel, and staff service the most.

Mobile Ad-hoc Networks (MANETs) are particularly difficult to manage due to the highly dynamic nature of its traffic, caused by variations on the number of users, their locations and the type of applications they use. This paper proposes a new modeling framework for mobile ad-hoc networks that integrates all important functional characteristics of a MANET and is able to predict network Quality of Service (QoS) based only on traffic measurements (or simulations), without requiring any information on the network structure, traffic routing or users' mobility. The application of the proposed framework to a specific modeling problem involves two phases: first, the network model is built from a set of (past) measurements of the gateways inbound/outbound traffic and the corresponding network QoS metrics; then, the constructed model can be used to predict (future) values of the QoS metrics based only on the inbound/outbound traffic. This framework does not impose any restrictions to the type of metrics that are selected to characterize QoS. Our results show that this approach can achieve excellent performance in terms of predicting QoS at multiple gateways, even when there are significant changes in the number of network users.