Web Service Selection Approach Research Articles

Study of a linear-physical-programming-based approach for web service selection under uncertain service quality

Abstract To promote the practical use of web service technologies, it is critical to select a proper web service that will meet users’ preferences from a pool of web services with similar functions. It is usually a core issue during web service selection to describe and evaluate the quality of these web services. Average value can be employed to describe certain service quality and to evaluate the quality with multiple criteria through the Simple Additive Weight Method. Based on an analysis of various deficiencies in existing approaches proposed in some studies, four indicators were used: Price, Response Time, Reliability and Credibility. On top of that, recent sampling data sets were introduced to describe the uncertain quality of service (QoS) criteria; linear physical programming was used to evaluate QoS with comprehensive criteria to meet the need to objectively describe uncertain QoS criteria, and preference regions were set to adapt to interval characteristics of criteria. Finally, a computational example is provided to demonstrate the feasibility and effectiveness of the method.

Multi-criteria Web Services Selection: Balancing the Quality of Design and Quality of Service

Web service composition allows developers to create applications via reusing available services that are interoperable to each other. The process of selecting relevant Web services for a composite service satisfying the developer requirements is commonly acknowledged to be hard and challenging, especially with the exponentially increasing number of available Web services on the Internet. The majority of existing approaches on Web Services Selection are merely based on the Quality of Service (QoS) as a basic criterion to guide the selection process. However, existing approaches tend to ignore the service design quality, which plays a crucial role in discovering, understanding, and reusing service functionalities. Indeed, poorly designed Web service interfaces result in service anti-patterns, which are symptoms of bad design and implementation practices. The existence of anti-pattern instances in Web service interfaces typically complicates their reuse in real-world service-based systems and may lead to several maintenance and evolution problems. To address this issue, we introduce a new approach based on the Multi-Objective and Optimization on the basis of Ratio Analysis method (MOORA) as a multi-criteria decision making (MCDM) method to select Web services based on a combination of their (1) QoS attributes and (2) QoS design. The proposed approach aims to help developers to maintain the soundness and quality of their service composite development processes. We conduct a quantitative and qualitative empirical study to evaluate our approach on a Quality of Web Service dataset. We compare our MOORA-based approach against four commonly used MCDM methods as well as a recent state-of-the-art Web service selection approach. The obtained results show that our approach outperforms state-of-the-art approaches by significantly improving the service selection quality of top- k selected services while providing the best trade-off between both service design quality and desired QoS values. Furthermore, we conducted a qualitative evaluation with developers. The obtained results provide evidence that our approach generates a good trade-off for what developers need regarding both QoS and quality of design. Our selection approach was evaluated as “relevant” from developers point of view, in improving the service selection task with an average score of 3.93, compared to an average of 2.62 for the traditional QoS-based approach.

A Classification Based Web Service Selection Approach

Selection of an appropriate web service fulfilling the requirements of the end user is a challenging task. Most of the existing systems use Quality of Service (QoS) as predominant parameter for web service selection, without any preprocessing or filtering. These systems consider all of the candidate web services during selection process and require unnecessary processing of those web services which are far below the expectations of the end user. In this work, an approach for web service selection based on QoS parameters is proposed. The proposed method starts with prefiltering of candidate web services using classification technique. An improved PROMETHEE method, we call it as PROMETHEE Plus, is applied to most eligible web services and Maximizing Deviation Method based hybrid weight evaluation mechanism is adopted. Top-k web services matching closely with the QoS requirements of the end user are selected. Experiments on the dataset of real world web services are conducted. Experimental results show that our approach performs better in terms of end user satisfaction and efficiency with reference to the existing similar approaches.

A Hybrid User-Centric Approach for Efficient Web Service Selection

Over the last few years, e-commerce has exhibited explosive growth due to the ease of availability of the internet. E-commerce is rapidly changing the way in which businesses are interacting with each other as well as with their consumers. In each innovative e-commerce application, web services are being included as an important component. This leads to the availability of a huge number of web services that provide similar functionalities. The main challenge is to select the appropriate web service which fulfills the end user requirements. So, there is a need for a web service selection method that selects the web services not only based on their functionality, but also considers the nonfunctional requirements. This article proposes a method to preprocess web services using the J48 classification technique. After that, a hybrid weight evaluation mechanism is employed to obtain the weight values of each nonfunctional parameter. In the end, the web services that are near to user expectations are selected out using the ranking method.

Web Service Selection Approach Based on Agent and Fuzzy Logic

Web Service Selection Approach Based on Agent and Fuzzy Logic

How to deal with QoS value constraints in MCDM based Web service selection

SummaryThe aim of the current research is to develop a more accurate Web service selection approach that can deal with value constraints on QoS criteria in the user request. The purpose is to be able to promote services even when all the value constraints are not satisfied and hence rank them according to their closeness to meet the latter. For this effect, we use MCDM (Multi Criteria Decision making) methods together with suitable normalization techniques at different stages of the process. First of all, we consider an extension of the AHP method to compute and normalize the weights associated with the QoS criteria considered in the Web service selection. Second, we introduce a more consistent normalization technique, called OMRI, to normalize data according to value constraints. Third, we propose to extend different ranking MCDM methods to the OMRI normalization so that it becomes possible for them to cope with value constraints. The considered methods are SAW, TOPSIS, VIKOR, and WPM. To compare the accuracy of the extended ranking methods, we use the Borda compromise solution together with different similarity ratios. To validate the solution, several experiments have been conducted on a real dataset as well as on an artificial one.

ISAT: An intelligent Web service selection approach for improving reliability via two-phase decisions

Due to stochasticity and uncertainty of malicious Web services over the Internet, it becomes difficult to select reliable services while meeting non-functional requirements in service-oriented systems. To avoid the unreliable real-world process of obtaining services, this paper proposes a novel service selection approach via two-phase decisions for enhancing the reliability of service-oriented systems. In the first-phase decision, we define the problem of finding reliable service candidates as a multiple criteria decision making (MCDM) problem. Then, we construct a decision model to address the problem. In the second-phase decision, we define the problem of selecting services based on non-functional requirements as an optimization problem. Finally, we propose a convex hull based approach for solving the optimization problem. Large-scale and real-world experiments are conducted to show the advantages of the proposed approach. The evaluation results confirm that our approach achieves higher success rate and less computation time to guarantee the reliability when compared to the other state-of-the-art approaches.

Towards an efficient and a more accurate web service selection using MCDM methods

Nowadays, due to the fast growth of the number of web services with the same functionalities, the selection of the best services becomes a tricky task. Therefore, to provide a more powerful selection tool, web services are now additionally distinguished with respect to their non-functional aspects, especially to Quality of Service (QoS) requirements. Indeed, using QoS perspective in web service selection can help to promote the best candidate web services among those holding the same functional requirements. Hitherto, various QoS based web service selection approaches have been explored in the literature. However, two main challenging and conflicting issues are still demanding a specific attention, namely how accurate is the selection and what is the cost of such a process? In this paper, we target Multi Criteria Decision Making (MCDM) methods to select web services. Within this context, we propose a hybrid method to select the optimal web services based on MCDM. First of all, we use the Skyline method to reduce the research space by removing the dominated web services. Then, the BWM (Best Worst Method) is applied to normalize the weights associated with the QoS parameters according to the user request requirements. To rank the non-dominated web services with respect to the weights normalization, we explore the use of four different MCDM approaches that enjoy an affordable complexity, which are: VIKOR, SAW, TOPSIS and COPRAS. For the sake of a comparison, each method is first tested separately in order to assess its ability to select the optimal elements. Then, in order to provide the best compromise between the different ranking methods, we apply the Borda voting method to determine the compromise solution. Hence, we are able to measure the accuracy of each technique relatively to the Borda solution by applying a similarity function. The implementation and the simulation of the different methods have permitted to assess their performances in terms of time execution and accuracy. The results show clearly that MCDM ranking methods are more likely to diverge in selecting the best elements when the number of web services is increased. This finding argues for the pertinence of computing the Borda solution in the context of MCDM based web service selection.

A structural-semantic web service selection approach to improve retrievability of web services

Service-Oriented Computing promotes building applications by consuming and reusing Web Services. However, the selection of adequate Web Services given a client application is still a major challenge. The effort of assessing and adapting candidate services could be overwhelming due to the “impedance” of Web Service interfaces expected by clients versus the actual interfaces of retrieved Web Services. In this work, we present a novel structural-semantic approach to help developers in the retrieval and selection of services from a service registry. The approach is based on a comprehensive structural scheme for service Interface Compatibility analysis, and WordNet as the semantic support to assess identifiers of operations and parameters. We also empirically analyze, compare and contrast the performance of three service selection methods: a pure structural approach, a pure semantic approach, and the structural-semantic (hybrid) approach proposed in this work. The experimental analysis was performed with two data-sets of real-world Web Services and a service discovery support already published in the literature. Results show that our hybrid service selection approach improved effectiveness in terms of retrievability of Web Services compared to the other approaches.

Cloud computing system risk estimation and service selection approach based on cloud focus theory

The main cloud computing service providers usually provide cross-regional and services of Crossing Multi-Internet Data Centers that supported with selection strategy of service level agreement risk constraint. But the traditional quality of service (QoS)-aware Web service selection approach cannot ensure the real-time and the reliability of services selection. We proposed a cloud computing system risk assessment method based on cloud theory, and generated the five property clouds by collecting the risk value and four risk indicators from each virtual machine. The cloud backward generator integrated these five clouds into one cloud, according to the weight matrix. So the risk prediction value is transferred to the risk level quantification. Then we tested the Web service selection experiments by using risk assessment level as QoS mainly constraint and comparing with LRU and MAIS methods. The result showed that the success rate and efficiency of risk assessment with cloud focus theory Web services selection approaches are more quickly and efficient.

Outlier-robust web service selection based on a probabilistic QoS model

In real world, a service may be affected by various factors making service selection process a difficult task. Therefore it is important to select an appropriate service efficiently from a large number of services based on the quality of a service QoS. However, existing approaches have limitations in processing QoS data with outliers that may occur in reality. When decomposing a global QoS constraint given by a service requester into local constraints, local thresholds are commonly computed with no consideration of outliers. Therefore, an appropriate service may not be selected due to false negative errors. To address this limitation, we propose an outlier-robust Web service selection approach based on a probabilistic QoS model. Specifically, the approach prunes services which do not satisfy a global constraint due to outliers. A service is then selected based on its probability of satisfying a global constraint. Experimental results show that the proposed approach outperforms an existing solution in terms of global QoS conformance.

Quality of Experience: User's Perception about Web Services

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.

A Novel Trust-Aware Composite Semantic Web Service Selection Approach

The functional characteristics and the nonfunctional properties of service profile always play very important roles in composite semantic web service selection approach. But the credibility of this information cannot be guaranteed. This paper established a novel trust degree model of this information. Based on this model, the trust degrees can be calculated from execution log and user experience evaluation of candidate web services. Then the paper proposes a new composite semantic web service selection approach based on this credible information. Finally, we present two experiments to prove that the new approach can avoid the influence of exaggerated and unauthentic information effectively and accurately.

Topic Model based Collaborative QoS Prediction

With the increasing development and growth of Web services on the World Wide Web, the demand of appropriate Web service selection approaches are unprecedentedly strong, and Quality-of-Service (QoS) based service computing is becoming an important issue of service-oriented computing. In most of previous works, the QoS values of services to users are all conceived to be known, however, lots of them are unknown in practice application. Recently, lots of literatures aiming at predicting such missing QoS values are published, they all consider the unknown QoS values prediction as a fundamental step for the QoS-based service computing. Looking through existing works, we discover that the online cold-start scenario, in which some new coming Web services haven't been involved even once, hasn't been considered carefu lly. In this paper, we utilize a collaborative framework by integrating matrix factorization with probabilistic topic model to predict QoS values. Spec ifically, the basic idea of the proposed approach is collaborative filtering via matrix factorization, while the cold-start problem is handled by employing probabilistic topic model based on WSDL (Web Service Description Language) documents. The experiment are based on two real-world datasets (one contains 100 users and 150 Web services, and the other contains 339 users and 2344 Web services), and the results demonstrate the prediction accuracy of the proposed approach.

Dynamic Transaction Aware Web Service Selection

Web service composition, that recursively constructs a composite web service out of the existing services based on a business workflow has been acknowledged as a promising approach to meet the user demands, whenever a single service alone cannot fulfil the needs. In view of frequent failures in the internet environment where the composed service is executed, reliability of the composed service must be ensured. The reliability is determined by the behavioral or transactional properties of component services. The component services for each activity of the workflow must be selected based on their behavior so that their execution results in a consistent termination. Service selection must happen at run-time in order to consider the services available in a service registry at the time of execution. Towards this need, a dynamic transaction aware web service selection approach is proposed in this paper. Further, whenever user requirements change, a long running transaction must be interrupted and cancelled which is not addressed by any of the existing works. Hence, service cancellability property is proposed in this paper and incorporated in the dynamic selection approach. The overhead of the proposed run-time selection approach is assessed and the impact of increased services on its performance is also measured.

An approach for Web service selection based on confidence level of decision maker.

Web services today are among the most widely used groups for Service Oriented Architecture (SOA). Service selection is one of the most significant current discussions in SOA, which evaluates discovered services and chooses the best candidate from them. Although a majority of service selection techniques apply Quality of Service (QoS), the behaviour of QoS-based service selection leads to service selection problems in Multi-Criteria Decision Making (MCDM). In the existing works, the confidence level of decision makers is neglected and does not consider their expertise in assessing Web services. In this paper, we employ the VIKOR (VIšekriterijumskoKOmpromisnoRangiranje) method, which is absent in the literature for service selection, but is well-known in other research. We propose a QoS-based approach that deals with service selection by applying VIKOR with improvement of features. This research determines the weights of criteria based on user preference and accounts for the confidence level of decision makers. The proposed approach is illustrated by an example in order to demonstrate and validate the model. The results of this research may facilitate service consumers to attain a more efficient decision when selecting the appropriate service.

QoS-aware Web Service Selection based on Particle Swarm Optimization

QoS-aware binding of composite services provides the capability of binding each service invocation in a composition to a service chosen among a set of functionally equivalent ones to achieve a QoS goal. Hence, service selection approach plays a very important role in service computing. However existing approaches little considered the computation time. In this study, we propose a fast QoS-aware web service selection approach. This approach adopts a particle swarm optimization algorithm select the most service with users’ QoS requirements Experimental results show that our approach can find best suitable services with lower time cost than other approaches in web service selection.

Privacy-Aware Web Service Composition and Ranking

Service selection is a key issue in the Future Internet, where applications are built by composing services and content offered by different service providers. Most existing service selection schemas only focus on QoS properties of services such as throughput, latency and response time, or on their trust and reputation level. By contrast, the risk of privacy breaches arising from the selection of component services whose privacy policy is not compliant with customers’ privacy preferences is largely ignored. In this paper, the authors propose a novel privacy-preserving Web service composition and selection approach which (i) makes it possible to verify the compliance between users’ privacy requirements and providers’ privacy policies and (ii) ranks the composite Web services with respect to the privacy level they offer. The authors illustrate their approach using an eCommerce Web service as an example of service composition. Moreover, the authors present a possible Java-based implementation of the proposed approach and present an extension to WS-Policy standard to specify privacy related assertions.

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.

A Two-phase Multi-Constraint Web Service Selection Approach for Web Service Composition

A Two-phase Multi-Constraint Web Service Selection Approach for Web Service Composition