Web Service QoS Research Articles

Predicting Web Service QoS via Combining Matrix Factorization with Network Location

With the increasing abundance of Web Services across Internet, Quality of Service (QoS)based service recommendation has become a hot issue. It is necessary to predict the missing values of QoS for service recommendation. Because Web services run on the Internet, their network locations may be anther critical factor for QoS prediction. Although there have existed many works on QoS prediction, few consider the influence of the network locations of users or Web Services. In this paper, we propose a novel collaborative QoS prediction framework with network location-based regularization (NLBR). We first elaborate the popular Matrix Factorization (MF) model for missing values prediction. Then, by taking advantage of the local connectivity between Web services users, we incorporate network location information to identify the neighborhood. We conduct the experiments on a public large-scale real-world QoS dataset, Experiments show that our proposed approaches have the better prediction performance compared with the existed approaches.

Input Projection Algorithms Influence in Prediction and Optimization of QoS Accuracy

Regardless of new achievements in the research of prediction models, QoS is still a great issue for high quality web services and remains one of the key subjects that need to be studied. We believe that QoS should not only be measured, but have to be predicted in development and implementation phases. In this paper we assess how different input projection algorithms influence the prediction accuracy of a Multi-Layer Perceptron (MLP) trained with large datasets of web services QoS values.

The QoS Prediction of Web Service with Location Information Ensemble

With the increasing presence and adoption of web services, accurate QoS prediction methods are becoming increasingly important. Although some QoS prediction techniques have been proposed and analyzed recently, the performance is not satisfactory, since they didn't take the relation between QoS values and users' physical locations into consideration. In order to improve the precision of web service QoS prediction, we propose a probabilistic matrix factor model that fuses the users' own properties and their physical neighbors' performance together, so as to make a comprehensive use of both the users' QoS records and their location relation. The experimental results show that our method performs better than the state-of-the-art approaches.

Investigating QoS of Real-World Web Services

Quality of service (QoS) is widely employed for describing nonfunctional characteristics of web services. Although QoS of web services has been investigated intensively in the field of service computing, there is a lack of real-world web service QoS data sets for validating various QoS-based techniques and models. To investigate QoS of real-world web services and to provide reusable research data sets for future research, we conduct several large-scale evaluations on real-world web services. First, addresses of 21,358 web services are obtained from the Internet. Then, three large-scale real-world evaluations are conducted. In our evaluations, more than 30 million real-world web service invocations are conducted on web services in more than 80 countries by users from more than 30 counties. Detailed evaluation results are presented in this paper and comprehensive web service QoS data sets are publicly released online.

Fuzzy-based Clustering of Web Services’ Quality of Service: A Review

Clustering has been proposed in numerous researches on web services due to its ability in enhancing computational efficiency. The objective of this paper is to present a review on web services clustering and to propose fuzzy clustering of web services' based on quality of service (QoS). A total of 49 manuscripts, collected from ISI, SCOPUS and Google Scholar indexing databases, were critically reviewed. The review revealed that there is no report has been published before regarding fuzzy-based clustering of web services' QoS. It also revealed the importance of clustering in ensuring the efficiency of web services delivery particularly in their discovery, selection and recommendation processes. The results of the proposed fuzzy clustering can be used as reference to guide requestors to subscribe suitable services. They could also be implemented as the inference components for fuzzy- based web services applications. For future work, the generated clustering results will be implemented in web services QoS monitoring application. Index Terms—Clustering, fuzzy clustering, Fuzzy C-Means, QoS clustering, web services clustering.

Multiple Virtual Machines Resource Scheduling for Cloud Computing

Cloud computing emerges as a new computing paradigm concerned by both academia and industry. Resource management of multiple virtual machines is the core of Infrastructure as a Service. Fo cusing on the CPU resources, the purpose of this paper is to increase the QoS of web service by properly scheduling the CPU resource across the virtual machines. We formulate the CPU scheduling of multiple virtual machines into an integer programming problem. Then, a global regulation algorithm based on utility optimization theory is proposed. Experimental result s show that the regulation syste m of CPUs can significantly improve the performance of Web applications.

Web Service QoS Matching Research Based on Ontology

In this article,take into account QoS characteristics comprehensively and build a reliable QoS ontology model. Based on the model,Web service QoS matching will be divided into three stages.Firstly,make a estimation of semantic comparability between QoS parameters of candidate services meeting the functional requirements and the QoS parameters of requirements in QoSIndependent ontology,find candidate services meeting users needs; Then,according to the critical QoS parameters between adjacent services constraints to further refine the matching between the candidate services;Finally choose the maximum service QoS value meeting the user requests in specific areas. So as to improve the efficiency and accuracy of service matching.

Collaborative Web Service QoS Prediction via Neighborhood Integrated Matrix Factorization

With the increasing presence and adoption of web services on the World Wide Web, the demand of efficient web service quality evaluation approaches is becoming unprecedentedly strong. To avoid the expensive and time-consuming web service invocations, this paper proposes a collaborative quality-of-service (QoS) prediction approach for web services by taking advantages of the past web service usage experiences of service users. We first apply the concept of user-collaboration for the web service QoS information sharing. Then, based on the collected QoS data, a neighborhood-integrated approach is designed for personalized web service QoS value prediction. To validate our approach, large-scale real-world experiments are conducted, which include 1,974,675 web service invocations from 339 service users on 5,825 real-world web services. The comprehensive experimental studies show that our proposed approach achieves higher prediction accuracy than other approaches. The public release of our web service QoS data set provides valuable real-world data for future research.

Towards Context Aware QOS-Based Web Service Description and Discovery

This work concentrates on context of the execution environment in service selection process due to dynamically varying QoS attributes in service execution environment. In this paper, a context aware QoS Web Service (WS) description and discovery is proposed to overcome the issues related to QoS requirements in WS. In the proposed scheme, OWL-Q with OWL CONtext ONtology (CONON) ontology is modelled to provide the WS description with context aware QoS descriptions. To discover the most appropriate WS based on context and QoS descriptions, a context aware QoS semantic matchmaking algorithm is newly proposed based on Constraint Satisfaction Optimization Approach (CSOP). An efficient User Priority based Ranking (UPR) mechanism is performed based on user preferences to rank the matched WSs. Consequently, precision and recall of proposed context aware QoS WS discovery is compared with the existing QoS WS discovery and conclude that proposed approach achieves high precision and recall than existing QoS based approach.

Combination Messaging-based Web Service QoS Improvement

Combination Messaging-based Web Service QoS Improvement

Probability distribution estimation for Web service QoS based on max entropy principle

To manage the risk of service,it is necessary to obtain stochastic character of Quality of Service(QoS) that is represented as accurate probability distribution.This paper presented an approach to estimate probability distribution of Web service QoS in the case of small number of samples.Using max entropy principle,the analytical formula of the probability density function can be obtained by transforming the probability distribution estimation problem into an optimal problem with constraints obtained from sampling QoS data.Then an algorithm to estimate parameters of the probability density function was designed.The experimental and simulation results based on real Web service QoS data show the effectiveness of the proposed approach for probability distribution estimation of different QoS attribute.The efficiency and feasibility of the distribution estimation algorithm have got validated by experiments too.

An Optimal Architecture for Dynamic Web Service Discovery and Selection

The composition of a set of Web services is an important aspect of Web services technology. This allows solving several types of problems by combining available services elementary and ordering them to best meets the requirements of problems. Automatic composition gives us flexibility of selecting best candidate services at composition time satisfying QoS requirements; This would require the user to define constraints for selecting and composing candidate Web services. In this paper, we present QoS broker - based architecture for web services. From the model architecture which allows the management of QoS that we have previously proposed, we focus on how we can use web service with a technique supporting QoS under dynamic web service composition. The main goal of the architecture is to support the client in selecting web services based on his/her required QoS. We also present an efficient method to predict QoS of Web service and to select the suitable web service based on the consumer’s requirements along with QoS.

Web service selection algorithm based on principal component analysis

Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user’s preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user’s QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.

An Approach for Web Service QoS Dynamic Prediction

In order to accurately predict the Web service Qos in a highly dynamic environment,we put forward a Qos dynamic prediction method based on Semi-Markov Processes(SMP) and Case-based Reasoning(CBR).This method firstly uses semi-Markov process to predict business state of web service in the future, and then applies the technology of CBR to predict Web service QoS, for example,when the service deals with a specific task. Experimental results show that this prediction method can improve the accuracy of Web service QoS greatly. The results provides a reliable basis for the objective evaluation and successful Web service composition. entatio� grxS��#�segmentation algorithm based on iterative segmentation and maximum variance between clusters of traffic signs is studied. Secondly, with feature extraction of traffic signs based on SIFT studied, the codebook is generated by these feature clustering and images are described by histograms using Bag of Words (BOW) model. Finally, multi-class classifier based on SVM is designed to classify traffic signs. The experimental results demonstrate the effectiveness and practicality of the BOW model classification algorithm based on the traffic sign images collected in the natural environment.

Monitoring web services’ quality of service: a literature review

Monitoring Quality of Service (QoS) compliance is an important procedure in web service environment. It determines whether users' expectations are met, and becomes the vital factor for them to decide whether to continue paying for the service or not. The monitoring is performed by checking the actual services performance against the QoS stated in Service Level Agreement (SLA). In relation to that, the need for monitoring vague QoS specifications in SLA has become more apparent nowadays. This paper reviews the published literature on web services QoS monitoring. A total of 60 selected articles were systematically analyzed. There were 23 of the articles selected through restrictive search criteria while the other 37 were selected based on unrestrictive search criteria. The review shows that little evidence exists on monitoring vague QoS specifications of web services. Providing ability for monitoring QoS that is specified vaguely in SLA could give new insights and implications to web services field. This paper concludes with some recommended future works to construct the theory and perform the empirical research.

QoS-aware service selection via collaborative QoS evaluation

We present in this paper a novel collaborative filtering based scheme for evaluating the QoS of large scale Web services. The proposed scheme automates the process of assessing the QoS of a priori ...

A Novel Method of Web Services Selection Based on Weighted Grey Relational Model in Ubiquitous Computing Environments

Selecting high quality web services based upon QoS(Quality of Service) is a significant task in service-oriented computing environments. In this paper, according a real Quality of Web Service data sets:QWS Dataset (1.0), we developed a Weighted Grey Relational Analysis Model(WGRAM) for web service selection based on QoS, and combined with Analytic Hierarchy Process(AHP) and Grey Relational Analysis (GRA) to prioritize the relative importance of the QoS of web services. The comprehensive evaluation model (WGRAM) fully considered the influence of many factors given by experts, incorporating the qualitative analysis of the index of various factors and the quantization for scientific decision-making, it can provide weighted grey relational degree for each Web Services with the same functions(operations), and the grey relational sequence which can guide the optimal service selection from multiple functions similar service. The model possessed the characteristic of simple calculating process, and the result was reliable, It’s a reliable and effective method of web service quality factor assessment and a significant attempt for web services selection.

Ontology Mapping for Dynamic Multiagent Environment

Ontologies are essential for the realization of the Semantic Web, which in turn relies on the ability of systems to identify and exploit relationships that exist between and within ontologies. As ontologies can be used to represent different domains, there is a high need for efficient ontology matching techniques that can allow information to be easily shared between different heterogeneous systems. There are various systems were proposed recently for ontology mapping. Ontology mapping is a prerequisite for achieving heterogeneous data integration on the Semantic Web. The vision of the Semantic Web implies that a large number of ontologies present on the web need to be aligned before one can make use of them. At the same time, these ontologies can be used as domain-specific background knowledge by the ontology mapping systems to increase the mapping precision. However, these ontologies can differ in representation, quality, and size that pose different challenges to ontology mapping. In this paper, we analyzed the various challenges of recently introduced Multi-Agent Ontology Mapping Framework, DSSim and we have integrated an efficient feature called QoS-Web Services Composition with DSSsim. ie we have improved this framework with QoS based Service Compositions Mechanism. From our experimental results, it is established that this developed QoS based Web Services Compositions Mechanism for Multiagent Ontology Mapping Framework minimizing uncertain reasoning and improves matching time, which are encouraging results of our proposed work..

A Web Service QoS Predicting Algorithm based on QoS Ontology and BP Neutral Networks

A Web Service QoS Predicting Algorithm based on QoS Ontology and BP Neutral Networks

QoS Evaluation Model for Web Services Composition

With the gradual development and standardization of services-oriented computing (SOC), it becomes a rapidly growing software developing pattern to composition Web services into applications. Since Web services composition are long-lasting, loosely coupled and cross application and administrative boundaries, it is essential to choose proper services to compose the composite Web services to meet user’s requirements. This paper presents a QoS evaluation method for aggregation services when failure occurs and defines QoS evaluation model of the common aggregation patterns of transaction compensation. Experiment results show that when it is used to evaluate the QoS of composite Web services, QoS evaluation method of aggregation transaction compensation is much better than the Web services composition method based on random selection, and it is feasible and effective.