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Supporting quality of service (QpS) in wireless networks has been a very rich and interesting area of research. Many significant advances have been made in supporting QoS in single wireless networks. However, the support for the Q...
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Supporting quality of service (QpS) in wireless networks has been a very rich and interesting area of research. Many significant advances have been made in supporting QoS in single wireless networks. However, the support for the QoS across multiple heterogeneous wireless networks will be required in the future wireless networks. In connections spanning multiple wireless networks, the end-to-end QoS will depend on several factors such as mobility and connection patterns of users, and the QoS policies in each of the wireless networks. The end-to-end QoS is also affected by multiple decisions that must be made by several different network entities for resource allocation. The paper has two objectives: one is to demonstrate the decision making process for resource allocation in multiple heterogeneous wireless networks and the second is to present a novel concept of composite QoS in such wireless environment. More specifically, we present an architecture for multiple heterogeneous wireless networks, decision making process for resource request and allocation, a simulation model to study composite QoS, and several interesting results. We also present potential implications of composite QoS on users and network service providers. We also show how the QoS ideas presented in this paper can be used by wireless carriers for improved QoS support and management. The paper can form the basis for a significant further research in DSS for emerging 3G/4G wireless networks supporting QoS for a range of sophisticated and resource intensive mobile applications.
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Web service composition enables seamless and dynamic integration of Web services. The behavior of participant Web services determines the overall performance of a composition. Therefore, it is important to choose high quality serv...
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Web service composition enables seamless and dynamic integration of Web services. The behavior of participant Web services determines the overall performance of a composition. Therefore, it is important to choose high quality services for service composition. Existing Web service selection and discovery approaches rely on non-functional aspects (also known as quality of service or QoS), e.g., response time and availability. Though these parameters are crucial for selecting Web services, they may not reflect the user's perspective of quality. In this paper, we explore the feasibility of incorporating perceived quality from user's perspective for service selection and composition. We name such quality attributes as quality of experience (QoE). First, we propose a solution that automatically mines and identifies QoE attributes from the Web. Second, we study the application of such dynamically extracted QoE attributes for service selection. For the evaluation purpose, we collected more than 34,000 reviews from 58 different services in six domains. Our findings show that it is possible to automatically identify QoE attributes with an average precision and recall of 92 and 80 percent respectively. Our study shows that there is a strong positive correlation between QoS and QoE. Hence QoE can be used during service selection especially when QoS data are not available. Furthermore, we found 70 percent of service discovery queries indeed contain QoE attributes showing the importance of QoE attributes during the service discovery phase.
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Purpose - The Healthcare sector is one of the important sectors of the Service Industry. It is believed that in this sector, the customer server relationship is very critical, and even the slightest gap in the people quality may h...
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Purpose - The Healthcare sector is one of the important sectors of the Service Industry. It is believed that in this sector, the customer server relationship is very critical, and even the slightest gap in the people quality may have a huge impact on the delivered service quality. Some of these enablers are doctors, nursing staff and support staff. Furthermore, the nonpeople quality enablers such as diagnostic services, facilities, hygiene levels and so on are also likely to impact the delivered service quality. It was also felt that the degree of impact each enabler has on the service quality could vary. Therefore there is a need for structured and deep analysis. The paper attempts to identify, analyze and prioritize the enablers that impact the delivered service quality. Design/methodology/approach - The enablers have been identified through literature review and inputs from experts in the healthcare fraternity. The authors have explored different decision-making tools such as analytic hierarchy process (AHP), analytic network process (ANP), stepwise weight assessment ratio analysis, Hybrid Model and DEMATEL (Decision-Making Trial and Evaluation Laboratory) for the analysis of data in this paper. Based on the strengths of the approach and careful considerations by focus group discussions, DEMATEL was chosen as the best option. It is simple, unique, sparingly used in the healthcare sector, effective in prioritizing and gives meaningful insights on importance, cause and effect factors. DEMATEL approach converts the complex problem with interrelated factors into a clear structure that makes simple interrelationships among factors in the form of cause and effects digraph, and hence, the authors chose to use it. A case study in one of the hospitals has also been conducted to demonstrate the applicability of the developed index. The case study very strongly validates the developed index. Findings - This research paper has found that there are people quality enablers such as the doctor, nursing staff, support staff and nonpeople quality enablers such as facilities, diagnostic services and hygiene levels maintenance, which impact the delivered service quality. It also concludes that the delivered service quality depends not only on the quality but also on the availability of these enablers. The inputs received from the experts have been run through the DEMATEL methodology and importance computed for each. The top five priority enablers are Quality of Doctor, Availability of Doctor, Quality of Support Staff, Quality of Nursing Staff and Availability of Support Staff. Research limitations/implications - The weights of the enablers have been obtained using the DEMATEL tool. These weights have been calculated using the inputs from 22 experts, which meets the statistical requirement (Skulmoski, 2007). However, a larger group of experts can be reached, and based on the inputs received from them, the tool can be revalidated for repeatability and reproducibility. Using Fuzzy DEMATEL can also be explored for further analysis. Practical implications - The proposed framework to assess the service quality level of a healthcare organization is based on a sound approach of DEMATEL. The service index arrived, thereafter, can be used to rate the delivered service quality by any healthcare organization. It can be used to compare the similar type of healthcare organizations across locations. This Index can facilitate improvements in the healthcare organization through internal and external benchmarking. It also helps the organization to know the gaps, understand the root cause, improve upon them and become the best in class. This Index uses the inputs from the end customers to calculate the rating, which makes it more reliable and accurate. The overall scores obtained from the Index can provide the ranking to the healthcare providing organizations and options to customers to choose from best. The service quality index can be used by an organization to continuously monitor their delivered service quality scores and improve them to become the best in class. The research paper highlights the significant role played by the people quality and its strong impact/contribution on the delivered service quality. Hence, it is believed that it will encourage the healthcare organizations to prioritize the improvement and upgrade of the people quality over the nonpeople quality aspect. Originality/value - Putting people and nonpeople quality enablers in one single model and assigning weights to them using the DEMATEL approach is a new application in healthcare. Developing an Index to measure the delivered service quality in the healthcare sector is also different and new.
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The challenge of optimally selecting services from a set of functionally appropriate ones under Quality of Service (QoS) constraints - the Service Selection Problem - has been extensively addressed in the literature based on deter...
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The challenge of optimally selecting services from a set of functionally appropriate ones under Quality of Service (QoS) constraints - the Service Selection Problem - has been extensively addressed in the literature based on deterministic parameters. In practice, however, Quality of Service QoS parameters rather follow a stochastic distribution. In the work at hand, we present an integrated approach which addresses the Service Selection Problem for complex structured as well as unstructured workflows in conjunction with stochastic Quality of Service parameters. Accounting for penalty cost which accrue due to Quality of Service violations, we perform a worst-case analysis as opposed to an average-case analysis aiming at avoiding additional penalties. Although considering conservative computations, QoS violations due to stochastic QoS behavior still may occur resulting in potentially severe penalties. Our proposed approach reduces this impact of stochastic QoS behavior on total cost significantly.
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Quality improvement is one of the strategies that many tourist destinations are currently using in order to increase their competitiveness in international tourist markets. In this respect, this paper analyses existing perceptions...
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Quality improvement is one of the strategies that many tourist destinations are currently using in order to increase their competitiveness in international tourist markets. In this respect, this paper analyses existing perceptions on the quality of Nerja as a tourist destination by using a measurement tool to specify and quantify perceived quality levels. The method used in this paper is a modified version of the well-known SERVQUAL scale, widely used to measure quality of service. Apart from verifying the validity of the tool used, the results of this study highlight the importance of hotel services, the climate and the beauty of the landscape, and the friendliness of personnel towards customers. It must be pointed out, however, that overcrowding stands out as the biggest problem which may adversely affect Nerja's future as a tourist destination.
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Although Malaga is a major tourist destination, research focused on the coastal area. However, the interior of the province has a growing tourism industry, so this tourism industry needs to be studied. The goal of this study was t...
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Although Malaga is a major tourist destination, research focused on the coastal area. However, the interior of the province has a growing tourism industry, so this tourism industry needs to be studied. The goal of this study was to analyse the attractiveness of this destination through the perceived quality of tourists? experiences, measuring the effect of each agent involved in tourists? overall assessment of the destination. Using a two-step factorial analysis of data gathered with 660 valid questionnaires collected through an on-the-ground survey, the composition structure and relationships of satisfaction factors in the destination were identified. Subsequently, the relationships between each agent with tourists? overall assessment of the destination were extracted. The results suggest that tourism businesses are primarily responsible for the final quality of this destination, followed by organisations responsible of the management of tourism resources. Further, the results also show that there is room for improvement in quality. The worst ratings were given for the quality of leisure facilities and restaurants, while the aspects most valued by users have a low capacity for differentiation (i.e. climate, courtesy and value for money). Therefore, this tourist destination would benefit from implementing a system of integrated quality management.
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Telecommunication networks are ever more frequently relying on artificial intelligence and machine learning techniques to detect specific use patterns or potential errors and to take automated decisions when these are encountered....
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Telecommunication networks are ever more frequently relying on artificial intelligence and machine learning techniques to detect specific use patterns or potential errors and to take automated decisions when these are encountered. This concept requires that methods be employed to measure the level of quality of a given telecommunication service, i.e. to verify quality of service (QoS) metrics. In a broader context, methods assessing the entire user experience (quality of experience-QoE) are required as well. In this article, various approaches to assessing QoS, QoE and the related metrics are presented, with a view to implement these at an FTTH network operator in Poland. Since this article presents the architecture of the system used to analyze QoE performance based on a number of QoS metrics collected by the operator, we also provide a comprehensive introduction to the QoS and QoE metrics used herein.
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The ability to gauge quality of service is critical if we are to realise the potential of the service-oriented computing paradigm. Many techniques have been proposed for calculating the quality of a service, and they do so typical...
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The ability to gauge quality of service is critical if we are to realise the potential of the service-oriented computing paradigm. Many techniques have been proposed for calculating the quality of a service, and they do so typically by collecting quality ratings from the users of the service, then combining them in one way or another to derive the quality of the service. We argue that collecting quality ratings alone from the users is not sufficient for deriving a reliable and accurate quality measure for a service. This is because different users often have different expectations on the quality of a service and their ratings tend to be closely related to these expectations, i.e. how their expectations are met. In this paper, we propose a quality of service assessment model based on user expectations. That is, we collect expectations as well as ratings from the users of a service, then calculate the quality of the service using only the ratings that have similar expectations. Our experiments show that the method we propose here can result in more meaningful and reliable quality ratings for services.
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In this article we describe and present results of using an architecture that leverages the potential of IETF's Differentiated Services giving the border of the network the necessary knowledge to better react to core conditions wh...
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In this article we describe and present results of using an architecture that leverages the potential of IETF's Differentiated Services giving the border of the network the necessary knowledge to better react to core conditions when impairment is foreseen for important traffic such as video streaming, using limited signalization. The architecture is named Distributed Dynamic Quality of Service - DDQoS - and includes models for both the core and the edge of the network. A video quality assessment framework is developed, allowing standard industry metrics like VQM to be used for estimating quality of experience.
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Purpose Multimedia applications such as digital audio and video have stringent quality of service (QoS) requirement in mobile ad hoc network. To support wide range of QoS, complex routing protocols with multiple QoS constraints ar...
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Purpose Multimedia applications such as digital audio and video have stringent quality of service (QoS) requirement in mobile ad hoc network. To support wide range of QoS, complex routing protocols with multiple QoS constraints are necessary. In QoS routing, the basic problem is to find a path that satisfies multiple QoS constraints. Moreover, mobility, congestion and packet loss in dynamic topology of network also leads to QoS performance degradation of protocol.
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