Semantic Web Service Discovery Approach Using Service Clustering

The 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. Firstly to reduce the overhead and enhance the discovery efficiency, genetic algorithm is adopted as a method of service clustering. Furthermore, the evaluation and calculation of QoS was realized to satisfy the user's QoS requirements. In the end, simulation results demonstrated the effectiveness of the proposed method.

Grid is a distributed infrastructure which allows large scale resources sharing and system integration. Task scheduling in grid becomes more complicated when strategy needs to combine user's QoS with system's computing performance. On the basis of analysing classic Min-min heuristic, an improved task scheduling algorithm using triangle module operator to integrate user's QoS with system's computing performance is proposed. Simulation are conducted on GridSim, and the results strongly demonstrate the proposed algorithm performs better on makespan, resource load balancing and user's QoS utility than BF-Min-min and Min-min which does not consider user's QoS requirements.

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.

BFRA: bounded flooding routing algorithm for provisioning the globally optimal route in a hierarchical ATM network

Since routers in IP network are connected with ATM virtual path (VP) permanent virtual connection (PVC) and each VP contains bundles of VCs, a VP layer network can serve as a server layer and each IP layer network can be a client layer. Therefore the effective Internet service provisioning completely depends on the reliability of VP server layer network from the perspective of the optimality and the network survivability. This paper proposes the distributed ATM VP PVC restoration framework with the dynamic rerouting schemes in hierarchical transport network. The rerouting algorithm aims to provide rapid ATM VP PVC restoration in the case of fault or performance degradation in terms of maximization of network resource utilization and satisfaction of the end user's QoS requirement. It guarantees the IP network survivability in spite of ATM network faults or performance degradations. In addition, this paper evaluates the rerouting performance for a real network, the High Speed Information Network (HSIN).

Relay selection is a challenging issue in cooperative communication networks. In particular, in a multi-user multi- concurrent-transmission network, effects of the resource sharing of a relay by its served users on the relay selection strategy need to be taken into account. There is little research on this investigation in literature. In this paper, we propose a novel efficient and fair relay selection strategy, in which individual user's QoS requirement is inherently taken into account. In terms of efficiency, the proposed strategy is of low computational complexity. In terms of fairness, the system resource is utilized fairly among all relaying nodes so that the system has the best potential to accommodate as many users as possible. Simulation results indicate that the proposed selection strategy outperforms many existing ones, therefore justifying our arguments.

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.

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.