Invocation Of Web Services Research Articles

A Semantic Web Services Classification approach based on IG-C4.5

Semantic Web services have emerged as the solution to the need for automating several aspects related to service-oriented architectures, such as service discovery and composition, and they are realized by combining Semantic Web technologies and Web service standards. The increasing number of available Web services has raised the need for their automated and accurate classification. Services Classification would be useful to enact powerful capabilities such as automatic selection, invocation, composition, location or discovery of web services. In this paper, We proposes a approach of Semantic Web Services classification taking into account the feature of textual description and the semantic annotations of OWL-S advertisements. An experimental test of the proposed techniques is reported, showing positive results, the efficiency and accuracy of the automatic service portfolio has been improved.

SWEFT: Semantic Web Service Engine for Telecommunication – An Automatic Discovery and Composition through Genetic Approach

The web service developed by telecommunication domain is ineffective since they are demonstrated by syntactic description rather than semantic. The motivation of the research is to have semantic description with existing web services, and provides discovery, composition and invocation of web services automatically. The objective is to identify the discovery and composition concerns and devise a compositional approach that covers all concerns. So a new prototype named Semantic Web Service Engine for Telecommunication which automatically discover and composite a web service was proposed, enables semantic through upper ontology and maps Web Service Description Language to Ontology Web Language-Semantic. For composition, a genetic algorithm was proposed which can solve problems with great distinctiveness. This approach automatically discovers and generates the required composite semantic web services and considers all identified concerns concurrently, improves the accuracy for the service discovery and unifies the semantic representation of telecommunications without human intervention.

AN ENHANCED METHOD TO COMPOSE BUSINESS PROCESS WEB SERVICES USING BPEL AND OPTIMIZED QOS PARAMETERS

Web services are reusable software components available across the web. These web services fulfill the requirements of the consumers in the form of business process requirements, software and technical requirements and other personal requirements. In order to achieve BPEL (Business Process Execution Language) process's QoS (Quality of Service) global optimization on dynamic Web service composition, the traditional dynamic Web service invocation model of BPEL process is enhanced and the service selection, refining and fault tolerance is added. Meanwhile, by improving the grading method, the paper designs and realizes the algorithm, whose result is the global optimization on QoS under the constraints. Through the comparison, the conclusion is that the optimal solution can be found more quickly by the improved algorithms and the business process's QoS global optimization under the constraints can be achieved by the modified model. This paper aims to determine a subset of web services from the candidate services to be invoked at run-time so as to successfully and efficiently orchestrate a composite web service.

Recommendation for Web Service Composition by Mining Usage Logs

Web service composition has been one of the most researched topics of the past decade. Novel methods of web service composition are being proposed in the literature include Semantics-based composition, WSDLbased composition. Although these methods provide promising results for composition, search and discovery of web service based on QoS parameter of network and semantics or ontology associated with WSDL, they do not address composition based on usage of web service. Web Service usage logs capture time series data of web service invocation by business objects, which innately captures patterns or workflows associated with business operations. Web service composition based on such patterns and workflows can greatly streamline the business operations. In this research work, we try to explore and implement methods of mining web service usage logs. Main objectives include Identifying usage association of services. Linking one service invocation with other, Evaluation of the causal relationship between associations of services

A Web Service Reliability Prediction Using HMM and Fuzzy Logic Models

With the increasing popularity of using Service-Oriented Systems (SOS), the reliability is becoming a significant concern for SOS. SOS are mainly built by Web services, hence prediction of reliability of Web service(s) leads to major concern in SOS. In this paper, Hidden Markov Model (HMM) and Fuzzy logic prediction model are used to predict reliability of Web service(s). The experiments are often conducted on real time Web services. The maximum likelihood value in HMM are calculated by Estimation-Maximization algorithm. Viterbi algorithm is used to restore the hidden states in HMM. The throughput, response time, and successful invocation of Web service are used to form rules in Fuzzy logic model. This helps to model highly complex problems that have multi-dimensional data. These experimental results prove better prediction method as compared to other conventional methods.

Reputation Measurement and Malicious Feedback Rating Prevention in Web Service Recommendation Systems

Web service recommendation systems can help service users to locate the right service from the large number of available web services. Avoiding recommending dishonest or unsatisfactory services is a fundamental research problem in the design of web service recommendation systems. Reputation of web services is a widely-employed metric that determines whether the service should be recommended to a user. The service reputation score is usually calculated using feedback ratings provided by users. Although the reputation measurement of web service has been studied in the recent literature, existing malicious and subjective user feedback ratings often lead to a bias that degrades the performance of the service recommendation system. In this paper, we propose a novel reputation measurement approach for web service recommendations. We first detect malicious feedback ratings by adopting the cumulative sum control chart, and then we reduce the effect of subjective user feedback preferences employing the Pearson Correlation Coefficient. Moreover, in order to defend malicious feedback ratings, we propose a malicious feedback rating prevention scheme employing Bloom filtering to enhance the recommendation performance. Extensive experiments are conducted by employing a real feedback rating data set with 1.5 million web service invocation records. The experimental results show that our proposed measurement approach can reduce the deviation of the reputation measurement and enhance the success ratio of the web service recommendation.

Assessing the Behaviour of Web Services using Finite States

Web service are the technology of a choice when developing business applications that needs to be loosely coupled, platform independent and capable to cross enterprise boundaries. The interactions that occur between web services need to be captured because such interactions would be very useful if captured using appropriate structures and analyzed for various purposes such as assessing the responsiveness of a web service to complete peer's requests. Since the invocations of web services (WS) are dynamic, the behaviour of the WS will be dynamic depending on how the invocations discover, and get serviced by WSs. For this reason if the states of the behaviour of a WS can be captured and assessed, then tuning the WS and its performance improvement can be engineered at any stage. This work is presented in this paper.

Quality Web Services Recommendation System Based on Enhanced Personalized Hybrid Collaborative Filtering Approach

Web service is an emerging technology in this decade for its openness and loosely coupled interaction among systems. Due to the proliferation of web services, more number of web services is available for similar functionality. QoS deals about the non-functional information of a Web services. Furthermore, QoS plays a vital role for differentiating web services which has similar functionality. Predicting the QoS value of a web service is an important process for web service discovery and selection. Due to the different network environment includes bandwidth, capacity and delay, the QoS value of a web service is differs from user to user. Therefore, QoS prediction is imperative for a recommendation system to provide best services based on QoS values. To achieve this, an enhanced collaborative filtering approach is introduced. In this approach, the PCC (Pearson Correlation Coefficient) is calculated for identifying the similar user and items. To increase the prediction accuracy, the user’s personalized degree of similarity is calculated and the Top-k users and items are identified. The confidence value computation helps to predict the missing values in the user-item matrix. By systematic integration of user-based and item-based methods, the final QoS values of a web services is predicted. The system has been tested with the invocation of real world web services, and the efficiency of the proposed approach is compared with the existing approaches. The MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) between the proposed and existing approaches shows the accurate prediction of the proposed approach.

A dataflow optimisation mechanism for service-oriented cloud workflow

While service-oriented cloud workflow shows potentials of inherent scalability, loose coupling and expenditure reduction, such issues as data transfer and efficiency have popped up as major concerns. In this paper, a dataflow optimisation mechanism is proposed, including data transfer strategy and data placement strategy. The data transfer strategy uses integrated data structures to enable the elimination of the SOAP serialisation and de-serialisation within the web service invocation by the exchange of their references. In addition, the data placement strategy groups the existing datasets and dynamically clusters newly generated datasets to minimise data transfers while keeping a polynomial time complexity. By integrating the optimisation mechanism into service-oriented cloud workflow system, we can expect efficiency improvements in data transfer and workflow execution. Experiments and analysis supported our efforts.

SEMANTIC ENHANCED UDDI USING OWL-S PROFILE ONTOLOGY FOR THE AUTOMATIC DISCOVERY OF WEB SERVICES IN THE DOMAIN OF TELECOMMUNICATION

The current web services which are evolved in the telecom domain such as payment web services, Yellow pages web services, operator web services, weather web services are failed to bring down the semantic as they used to prove its syntactic description. The reason for bringing down the semantic description into already existing web services will invoke certain operations like automatic discovery of web services, automatic composition of the necessary services, automatic invocation of web services and automatic monitoring of the execution process. At present the web services in the domain of telecommunication is following the parlay X standard. The parlay X has given a set of standard web service API’s for the telecom. The each of the services will have its own interface, services and types In this study in order to bring down the semantic representation we have proposed an idea to enable the semantic through the upper ontology like OWL-S and then how to map OWL-S to UDDI registry and also we have discussed some of the issues that we have faced while mapping OWL-S into UDDI registry. So the approach which we are going to propose improves the accuracy of the telecommunication network services description, discovery and matching, unifies the semantic representation of telecommunications network and Internet services.

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.

Colbar: A collaborative location-based regularization framework for QoS prediction

Quality-of-Service (QoS) is a fundamental element in Service-Oriented Computing (SOC) domain. At the ongoing age of Web 2.0, predicting the missing QoS values becomes more and more important since it is an indispensable preprocess of numerous service-oriented applications. Previous research works on this task underestimate the importance of users’ geographical information, which we argue would contribute to improving prediction accuracy in Web services invocation process. In this paper, we propose a novel collaborative location-based regularization framework (Colbar) to address the problem of personalized QoS prediction. We first leverage the personal geographical and QoS information to identify robust neighborhoods. And then, we collect the wisdom of crowds to construct two location-based regularization terms, which are integrated to build up an unified Matrix Factorization framework. Finally we make intermediate fusions to generate better prediction results. The experimental analysis on a large-scale real-world QoS dataset shows that the prediction accuracy of Colbar outperforms other state-of-the-art approaches in various criteria.

Intelligent business processes composition based on multi-agent systems

This paper proposes a novel model for automatic construction of business processes called IPCASCI (Intelligent business Processes Composition based on multi-Agent systems, Semantics and Cloud Integration). The software development industry requires agile construction of new products able to adapt to the emerging needs of a changing market. In this context, we present a method of software component reuse as a model (or methodology), which facilitates the semi-automatic reuse of web services on a cloud computing environment, leading to business process composition. The proposal is based on web service technology, including: (i) Automatic discovery of web services; (ii) Semantics description of web services; (iii) Automatic composition of existing web services to generate new ones; (iv) Automatic invocation of web services. As a result of this proposal, we have presented its implementation (as a tool) on a real case study. The evaluation of the case study and its results are proof of the reliability of IPCASCI.

A Web Service Selection Model using Cognitive Parameters

Semantic Web Service is considered to be the crux of Dynamic Web Service Selection. It looks forward to automate the different aspects of Service Selection which includes Web Service Discovery, Service Selection, Service Composition and Service Invocation. This paper aims at better understanding the Service Selection aspect of Semantic Web Service giving cognitive parameters the center stage. It looks at the psychological and basic behavioral aspect of consumer behavior. A model for Service Selection is proposed wherein an attempt has been made to measure the consumer behavior using cognitive parameters. A detailed study of these cognitive parameters has been made from both the service provider’s context and the service consumer’s context. These parameters are then used to perform the service selection effectively and efficiently. The cognitive parameters help in efficient modeling of user’s requirements and thus leading to better service selection.

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.

A Web Service Framework Supporting Multimedia Streaming

The transfer of streaming data is not well supported by current web services standards. To include multimedia streaming support in the web services domain, this paper presents a novel multimedia streaming web services framework for the transfer of streaming multimedia content. First, the framework includes an implementation of a query service for publishing a description of the multimedia content that is input to or output from a multimedia web service. This query service is specified in an extension of WSDL. Using MPEG-7 metadata, content descriptions can be queried before the invocation of a multimedia web service. Second, two new MEPs and their SOAP HTTP bindings are created for the exchange of streaming data between two SOAP endpoints. The implementations of these new MEPs use the MIME multipart/related structure and MTOM packaging when transferring the multimedia packets as SOAP messages. To reduce the transfer overhead introduced by the packaging method, this paper investigated extensively the application of various compression schemes for the SOAP messages as well as for the packaging of the binary packet data. Experiments show that the proposed framework can achieve a performance comparable to a simple HTTP multimedia streaming method.

An Intermediate Service Composer Architecture for Dynamic Discovery and Invocation of Web Services from Mobile Devices

An Intermediate Service Composer Architecture for Dynamic Discovery and Invocation of Web Services from Mobile Devices

Data flow analysis and testing for OWL-S semantic web service compositions

Semantic web services SWSs, which integrate the concept of ontology to support incorporation of machine understandable semantics into web services, have drawn much attention in recent years. By introducing semantics into web services, the quality and robustness of web service discovery, selection, and invocation can be greatly improved. However, web ontology language for service OWL-S, the most widely accepted standard used to describe SWS, is extremely complex and hard to understand. This makes OWL-S compositions difficult to analyse and test. In view of this, this paper proposes a data flow testing approach for web service compositions based on OWL-S. The data flow test artefacts introduced by OWL-S are identified and thoroughly analysed. A test model that considers a variety of control constructs and semantics of OWL-S is proposed to abstract these test artefacts. Based on the test model, test paths can be derived to effectively uncover defects caused by improper data handling and message exchanges of OWL-S compositions.

Personalized QoS-Aware Web Service Recommendation and Visualization

With the proliferation of web services, effective QoS-based approach to service recommendation is becoming more and more important. Although service recommendation has been studied in the recent literature, the performance of existing ones is not satisfactory, since (1) previous approaches fail to consider the QoS variance according to users' locations; and (2) previous recommender systems are all black boxes providing limited information on the performance of the service candidates. In this paper, we propose a novel collaborative filtering algorithm designed for large-scale web service recommendation. Different from previous work, our approach employs the characteristic of QoS and achieves considerable improvement on the recommendation accuracy. To help service users better understand the rationale of the recommendation and remove some of the mystery, we use a recommendation visualization technique to show how a recommendation is grouped with other choices. Comprehensive experiments are conducted using more than 1.5 million QoS records of real-world web service invocations. The experimental results show the efficiency and effectiveness of our approach.

Reliable Web service selection in choreographed environments

Previous research into Web service selection mainly uses an orchestration model, in which a single entity is responsible for the selection and invocation of various Web services. However in many application scenarios, each Web service independently performs a selection, even though achieving the business's goals demands collective, pairwise interactions across the total set of Web services. This study instead considers the Web service selection problem in a choreographed environment, in which each Web service maintains its confidentiality about its collaborators and exchanges only limited amounts of information with its partners. The goal is to maximize the likelihood of completing the entire choreography in a failure-prone environment. Several experiments show that the proposed method performs similarly to a centralized method and better than three distributed Web service selection methods that involve various degrees of information about other services.