Semantic-based Service Discovery Research Articles

A Semantic-Based Service Discovery Framework for Collaborative Environments

A Semantic-Based Service Discovery Framework for Collaborative Environments

Semantic Driven Web Service Discovery (SDWSD) System

Service discovery is one of most challenging issues now-adays because of the increasing number of services but a very few techniques are available for their efficient discovery. It is worthless if there are abundant services available but we cannot avail our desired services only because of the irrelevant discovery system. The semantic based service discovery is proposed to enhance the discovery of these elusive services. Web service standards, in their present format supports only keyword based search and many services which can fulfill the user’s requirements are not retrieved. Basic requirement for efficient service discovery is to extract the contextual information provided in the service description. In such situation, the optimal solution is obtained by introducing semantics in the present Web Service Description Language (WSDL).

A DHT-based semantic overlay network for service discovery

The number of available Internet services increases every day. This trend demands distributed models and architectures to support scalability as well as semantics to enable efficient publication and retrieval of services. Two common approaches toward this goal are semantic overlay networks (SONs) and distributed hash tables (DHTs) with semantic extensions. SONs enable semantic-driven query answering but are less scalable than DHTs, which, in their turn, feature efficient but semantic-free query answering based on exact match. This paper presents a strategy and a system, called ERGOT, that combine DHTs and SONs to enable semantic-based service discovery in distributed infrastructures such as Grids and Clouds. ERGOT uses semantic annotations that enrich service specifications in two ways: (i) services are advertised in the DHT on the basis of their annotations, thus allowing us to establish a SON between service providers; (ii) annotations enable semantic-based service matchmaking, using a similarity measure between service requests and descriptions. An extensive evaluation of the system is presented and discussed. The experimental evaluation we carried out confirmed the efficiency of the implemented strategy in terms of both accuracy of search and network traffic.

A Method of Semantic Web Service Discovery Based on Bipartite Graph Matching

How to discover services for users efficiently is the key for the application of the Web service technology. The current semantic-based service discovery methods are of great inconvenience to be used and have much potential improvement for their performance. This paper proposes an information model of registered services that isn′t limited to specific service models and languages and supports semantic-annotation and interface-dependency declaration. Then, a method of service discovery based on bipartite graph matching is proposed that translates the service matchmaking to the problem of extended optimal matching for bipartite graph. It enhances the recall rate and precision as it considers the interface dependency relations within a service in matchmaking. A serial of experiments illustrate the method not only improves its efficiency much, but also has a linear complexity in time consumption to fulfill users′ requests.

An Efficient Service Discovery Method and its Application

To discover services efficiently has been regarded as one of important issues in the area of Service Oriented Computing (SOC). This article carries out a survey on the issue and points out the problems for the current semantic-based service discovery approaches. After that, an information model for registered services is proposed. Based on the model, it brings forward a two-phase semantic-based service discovery method which supports both the operation matchmaking and operation-composition matchmaking. The authors import the bipartite graph matching to improve the efficiency of matchmaking. An implementation of the proposed method is presented. A series of experiments show that the method gains better performance on both discovery recall rate and precision than a traditional matchmaker and it also scales well with the number of services being accessed.