Challenges to describe QoS requirements for web services quality prediction to support web services interoperability in electronic commerce

Quality of service (QoS) is significant and necessary for web service applications quality assurance. Furthermore, web services quality has contributed to the successful implementation of Electronic Commerce (EC) applications. However, QoS is still the big issue for web services research and remains one of the main research questions that need to be explored. We believe that QoS should not only be measured but should also be predicted during the development and implementation stages. However, there are challenges and constraints to determine and choose QoS requirements for high quality web services. Therefore, this paper highlights the challenges for the QoS requirements prediction as they are not easy to identify. Moreover, there are many different perspectives and purposes of web services, and various prediction techniques to describe QoS requirements. Additionally, the paper introduces a metamodel as a concept of what makes a good web service

Online Service Quality Evaluation for Residential Hall in Universiti Utara Malaysia

The advantages of internet services cannot be overemphasized especially in the academic environment where it is mainly used for e-learning as online services. The universities are known to provide for their students by giving them shelters, known as Student Hall of Residence. Maybank Hall of Residence officers provide many services for their occupants in the hall. However, these services are yet to be evaluated in order to know the services quality they are giving to their occupants. This project designs a requirement model and developed a prototype to allow the Service Quality for the occupants of the Maybank Student Hall of Residence to evaluate the services using the on-line evaluation system. The result generated during the implantation phase of this project shows that the system is effective and easy to learn

Non-functional Property based service selection: A survey and classification of approaches

In recent years there has been much effort dedicated to developing approaches for service selection based on non-functional properties. It is clear that much progress has been made, and by considering the individual approaches there is some overlap in functionality, but obviously also some divergence. In this paper we contribute a classification of approaches, that is, we define a number of criteria which allow to differentiate approaches. We use this classification to provide a comparison of existing approaches and in that sense provide a survey of the state of the art of the field. Finally we make some suggestions as to where the research in this area might be heading and which new challenges need to be addressed

A Framework for Trusted Services

An existing challenge when selecting services to be used in a service- based system is to be able to distinguish between good and bad services. In this paper we present a trust-based service selection framework. The framework uses a trust model that calculates the level of trust a user may have with a service based on past experience of the user with the service and feedback about the service received from other users. The model takes into account different levels of trust among users, different relationships between users, and different levels of importance that a user may have for certain quality aspects of a service. A prototype tool has been implemented to illustrate and evaluate the work. The trust model has been evaluated in terms of its capacity to adjust itself due to changes in user ratings and its robustness

Understanding the Impact of Service Reputation on the Online Group-buying Behaviors

It has been well recognized that vendors’ reputation plays an important role in e-commerce. As a popular platform for promoting the services or products online, groupon websites have developed various reputation systems to assist the customers in making their purchase decisions. This paper performs an empirical study to investigate the impact of service reputation on the groupon buying behaviors using data from a major groupon website in China. A set of service reputation metrics is developed to measure the service reputation for different service providers, and the groupon buying behavior is measured by the amount of users participating in the corresponding collective buying activity. Correlation analysis is carried out to find out the relationship between the service reputation and the groupon purchase behaviors. Our research indicates the necessity for an improvement for the current service reputation systems of the groupon web sites

Service Selection Based on Non-functional Properties

Service-oriented Architecture supports software to be composed from services dynamically. Selecting and composing appropriate services according to business process, policies and non-functional constraints is an essential challenge. This paper proposes a method for automatic selection of the most relevant service for composition based on non-functional properties and the user’s context. In doing this we also propose a method of obtaining and evaluating non-functional aspects

Decomposing ratings in service compositions

An important challenge for service-based systems is to be able to select services based on feedback from service consumers and, therefore, to be able to distinguish between good and bad services. However, ratings are normally provided to a service as a whole, without taking into consideration that services are normally formed by a composition of other services. In this paper we propose an approach to support the decomposition of ratings provided to a service composition into ratings to the participating services in a composition. The approach takes into consideration the rating provided for a service composition as a whole, past trust values of the services participating in the composition, and expected and observed QoS aspects of the services. A prototype tool has been implemented to illustrate and evaluate the work. Results of some experimental evaluation of the approach are also reported in the paper

A STRUCTURE TO ASSIST COLLECTION OF CLOUD PROVISION PROVIDERS

Cloud-computing is a developing concept, by which new providers and services information are often entering existence, offering services of comparable functionality. Trust in addition to status is important concepts within online applications. They have produced easy selection appropriate to picking of consistent agent for electronic transactions. We   present a method referred to as choice of cloud firms that mixes reliability in addition to competence for estimation of chance of interaction which estimates supposed volume of interaction risk by way of mixing reliability in addition to competence of cloud provider. Reliability is computed from personal encounters that's acquired completely through direct relations otherwise from feedbacks connected with reputations of vendors.  Competence is assessed based on transparency within provider service level contracts guarantees

An effective method for clustering-based web service recommendation

Normally web services are classified by the quality of services; however, the term quality is not absolute and defined relatively. The quality of web services is measured or derived using various parameters like reliability, scalability, flexibility, and availability. The limitation of the methods employing these parameters is that sometimes they are producing similar web services in recommendation lists. To address this research problem, the novel improved clustering-based web service recommendation method is proposed in this paper. This approach is mainly dealing with producing diversity in the results of web service recommendations. In this method, functional interest, quality of service (QoS) preference, and diversity features are combined to produce a unique recommendation list of web services to end-users. To produce the unique recommendation results, we propose a varied web service classification order that is clustering-based on web services’ functional relevance such as non-useful pertinence, recorded client intrigue importance, and potential client intrigue significance. Additionally, to further improve the performance of this approach, we designed web service graph construction, an algorithm of various widths clustering. This approach serves to enhance the exceptional quality, that is, the accuracy of web service recommendation outcomes. The performance of this method was implemented and evaluated against existing systems for precision, and f-score performance metrics, using the research datasets

Modelling Confidence for Quality of Service Assessment in Cloud Computing

The ability to assess the quality of a service (QoS) is important to the emerging cloud computing paradigm. When many cloud service providers exist offering many functionally identical services, the prospective users of these services will wish to use one that offers the best quality. Many techniques and tools have been proposed to assess QoS, and the ability to deal with uncertainty surrounding the QoS verdicts given by any such techniques or tools is essential. In this paper, we present a probabilistic model to quantify confidence in QoS assessment. More specifically, we take the number of QoS data items used in assessment and the variation of data in the dataset into account in our measure of assessment reliability. Our experiments show that our confidence model can help consumers to select services based on their requirements effectively