Trust-QoS Based Semantic Web Service Discovery Technology

Discovery of suitable Web services for a given user requirement is one of the key technology. A mechanism is proposed to support QoS-based semantic web service discovery in the paper. Firstly, to reduce the overhead and enhance the discovery efficiency, genetic algorithm is adopted as a method of service clustering. Furthermore, based on user's QoS requirements, the QoS-based service matchmaker was realized. In the end, simulation results demonstrated the effectiveness of the proposed method.

Web service (WS) discovery is a prerequisite for achieving WS composition and orchestration. Although a lot of research has been conducted on the functional discovery of WSs, the proposed techniques fall short when faced with the foreseen increase in the number of (potentially functionally-equivalent) WSs. The above situation can be resolved with the addition of non-functional (quality of service (QoS)) discovery mechanisms to WS discovery engines. QoS-based WS matchmaking algorithms have been devised for this reason. However, they are either slow - as they are based on ontology reasoners - or produce inaccurate results. Inaccuracy is caused both by the syntactic matching of QoS concepts and by wrong matchmaking metrics. In this paper, we present two constraint programming (CP) QoS-based WS discovery algorithms for unary constrained WS specifications that produce accurate results with good performance. We also evaluate these algorithms on matchmaking time, precision and recall in different settings in order to demonstrate their efficiency and accuracy.

Matching web services and client requirements in the form of goals is a significant challenge in the discovery of semantic web services. The most common but unsatisfactory approach to matching is set‐based, where both the client and web services declare what objects they require and what objects they can provide. Matching then becomes the simple task of comparing sets of objects. This approach is inadequate because it says nothing about the functionality required by the client or the functionality provided by the web service. As an alternative, we use the Frame Logic as implemented in Flora‐2 to specify web service capabilities and client requirements, including their preconditions, postconditions, and ontologies, implement a logic‐based discovery agent using Flora‐2, demonstrate its usefulness in a medical appointment making scenario, and show its efficiency both theoretically and by benchmarking. The result is an expressive yet concise representation scheme for semantic web services, and a practical, efficient, powerful, and fully implemented matching engine based purely on logical inference for web service discovery, with direct applicability to Web Service Modeling Ontology and Web Service Modeling Language, because both are based on Frame Logic.

Background/Objectives: This article proposes a novel methodology based on rubrics and feature-based schemes for the appraisal and comparison of approaches to semantic Web services composition and discovery. Methods/Statistical analysis: In order to evaluate the Semantic Web services composition and discovery approaches we created a new framework called RFSWS. This framework is the combination of traditional feature-based evaluation schemes and newly developed analytic rubrics tables. Five recently introduced prominent Semantic Web services composition approaches were identified, explained, and then evaluated/compared using RFSWS. Findings: In this work we determined aspects of Semantic Web services composition and discovery processes that can be evaluated as performance criteria in rubric tables. This is a novel application of rubrics, which have traditionally been used for grading student performance by teachers. We created a novel framework called RFSWS consisting of rubric tables and a feature-based evaluation scheme for the evaluation and comparison of Semantic Web service discovery and composition approaches, and applied it in the evaluation of five recently introduced prominent Semantic Web services composition approaches. Considering the shortcomings of existing Semantic Web services composition approaches that were discovered through this evaluation, we proposed an idealized dynamic Semantic Web service discovery and composition method, a yardstick by which all future Semantic Web services composition approaches can be evaluated. Application/ Improvements: Our novel RFSWS framework can be applied in the comprehensive and systematic evaluation/comparison of Semantic Web services discovery and composition approaches.

Directory services are a genuine constituent of any distributed architecture which facilitate binding attributes to names and then querying this information, that is, announcing and discovering resources. In such contexts, especially in a business environment, Quality of Service (QoS) and non-functional properties are usually the most important criteria to decide whether a specific resource will be used. To address this problem, we present an approach to the semantic description and discovery of web services which specifically takes into account their QoS properties. Our solution uses a robust trust and reputation model to provide an accurate picture of the actual QoS to user. The search engine is based on an algebraic discovery model and uses adaptive query-processing techniques to parallelise expensive operators. Architecturally, the engine can be run as a centralised service for small-scale environments or can be distributed among any number of cooperating registry providers.

Web services are the new paradigm for distributed computing. They offer interoperability of application and integration of large scale distributed systems. Amongst the web service standards, service registry is crucial to the overall utility of web service technology. However, the web services discovery mechanism pertaining with the UDDI [1] registry is inefficient because it only supports keyword-based and category-based matching, leading to irrelevant matches. Therefore, the provision of the scalable, flexible and robust web services publication and discovery system is crucial for the overall utility of web services. In this paper, we develop a scalable, robust and efficient infrastructure for web services publication and discovery amongst domain-based registries. More importantly, a novel algorithm is provided to classify web services into domain-based registries based on their semantic description. Experimental results show that our approach outperforms a centralized approach in terms of service discovery time.

Shared-Repository based Approach for Storing and Discovering web Services

The rapidly growing number and complexity of web services available on the Web raise a novel and challenging problem: utilizing semantics to organize web services for more effective services searching. Traditional UDDI is insufficient in this context, since the underlying semantics of web services are not exploited enough. Also, the user requirements are not described explicitly and consistently. Considering this situation, we construct a SAM-based service model for web services management, SAM-WS, and propose an approach for users to explicitly describe their QoS requirements using QoS ontology. Experimental results show the effectiveness by comparison of our approach and traditional keyword search.

The rapidly growing number and complexity of web services available on the Web raise a novel and challenging problem: utilizing semantics to organize web services for more effective services searching. Traditional UDDI is insufficient in this context, since the underlying semantics of web services are not exploited enough. Also, the user requirements are not described explicitly and consistently. Considering this situation, we construct a SAM-based service model for web services management, SAM-WS, and propose an approach for users to explicitly describe their QoS requirements using QoS ontology. Experimental results show the effectiveness by comparison of our approach and traditional keyword search.

Web services (WS) is called composite or compound when its execution involves interactions with other WS to utilize their features. The service providers published the web services through the internet as independent software components that are fulfilling the requirements of customer request. Clustering is more necessary for efficient web service discovery and web service composition processes. Clustering process groups the similar type of web services. In this paper, efficient clustering methods such as k-means clustering, Hierarchical agglomerative clustering and Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) clustering are introduced for web service clustering. The k-means clustering is a kind of partitional clustering where the web pages are divided into subsets with no hierarchy defined over them and the hierarchical agglomerative clustering is a type of hierarchical clustering where the web pages are arranged in tree structure in which leaves represents the data points and nodes denotes the clusters. BIRCH is an integrated hierarchical clustering algorithm uses the clustering features and cluster feature tree for general cluster description. Based on these clustering methods, web pages are clustered which are used for web service discovery and web service composition. The experiments are conducted on number of web services and the efficiency is evaluated in terms of accuracy, precision, recall and run time.

Efficient Discovery and Ranking of Web Services Using Non-functional QoS Requirements for Smart Grid Applications

Service discovery is the process to find a service that is best meet the user's requirement. Context of the user and the service plays an important role during the process because it takes into consideration more about the user and the service. In order to better implement the personalization of service discovery, and take into full consideration of the user's requirement and feature, a context-based framework for web services discovery is proposed in this paper. User Model and Intention Model are used in our framework to construct the user context. Service discovery and composition are carried out heuristically by considering both the user context and the web services context. And Service discovery is conducted by taking into account not only a published single web service but the combination of web services when a single web service can not be found. Service recommendation is also provided.

Due to the lack of semantic descriptions of the Web services, the search results returned by the service registries are effectively inadequate. This paper presents the Semantic Web services Clustering (SWSC) method that extends the semantic representation of services and groups the similar Web services in order to improve the service discovery. The empirical analysis shows the improvement in service discovery with the use of SWSC.

Semantic Web services is considered as the concept bringing the web to its full potential by combining the best features of web services, agent technology, grid and the Semantic web. In this paper we present a semantic Web Services platform based on software agent (JASW), which introduces Semantic web and software agent and takes the automated discovery, selection, orchestration and invocation of Web services as application background. In the platform, we adopt Semantic web to accurately describe Web services, and use software agent to implement discovery, selection, and orchestration of Web services.

Main challenges to the current semantic web service technologies are exponential continuous growth in the number of services on the Internet, syntax based discovery, lack of common agreed upon semantic service standards and heterogeneity of ontologies. In this paper, a service discovery approach independent of semantic service description models is proposed to solve the challenges of the current web service discovery. The idea is to combine principles from machine learning, data mining, statistical techniques and measures of semantic relatedness to make the semantic web service discovery process more intelligent, efficient and effective. The proposed approach exploits the use of semantic as well as syntactic information present within the service description profiles. Our approach is unique in terms of its application to any web service description language and the use of Omiotis measure of semantic relatedness for service discovery. The proposed approach has been implemented on OWL-S based service descriptions profiles and is able to find semantic relationship between the services which were otherwise discarded by the OWL-MX matchmaker. Empirical analysis shows that the proposed method out performs the