Search Space Reduction Approach for Self-adaptive Web Service Discovery in Dynamic Mobile Environment

2019 ◽  
pp. 1111-1121
Author(s):  
Salisu Garba ◽  
Radziah Mohamad ◽  
Nor Azizah Saadon
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Search Space ◽  
Mobile Environment ◽  
Web Service Discovery ◽  
Space Reduction ◽  
Search Space Reduction ◽  
Reduction Approach ◽  
Self Adaptive

Context-Aware Web Service Clustering and Visualization

2020 ◽  
Vol 17 (4) ◽  
pp. 32-54
Author(s):  
Banage T. G. S. Kumara ◽  
Incheon Paik ◽  
Yuichi Yaguchi
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Discovery ◽  
Search Space ◽  
Context Aware ◽  
Specific Context ◽  
Web Service Discovery ◽  
Domain Specific ◽  
Clustering Approach ◽  
Service Clustering

With the large number of web services now available via the internet, web service discovery has become a challenging and time-consuming task. Organizing web services into similar clusters is a very efficient approach to reducing the search space. A principal issue for clustering is computing the semantic similarity between services. Current approaches do not consider the domain-specific context in measuring similarity and this has affected their clustering performance. This paper proposes a context-aware similarity (CAS) method that learns domain context by machine learning to produce models of context for terms retrieved from the web. To analyze visually the effect of domain context on the clustering results, the clustering approach applies a spherical associated-keyword-space algorithm. The CAS method analyzes the hidden semantics of services within a particular domain, and the awareness of service context helps to find cluster tensors that characterize the cluster elements. Experimental results show that the clustering approach works efficiently.

Web Service Discovery Approaches for Dynamic Mobile Environment

2021 ◽  
Vol 13 (4) ◽  
pp. 16-38
Author(s):  
Salisu Garba ◽  
Radziah Mohamad ◽  
Nor Azizah Saadon
Keyword(s):  
Literature Review ◽  
Web Service ◽  
Systematic Literature Review ◽  
Service Discovery ◽  
Research Trends ◽  
Mobile Environment ◽  
Essential Information ◽  
Mobile Web ◽  
Web Service Discovery ◽  
Depth Analysis

Mobile web service (MWS) discovery is taking a new direction due to the explosion of users accessing mobile services using diverse mobile devices, coupled with the persistent changes in a dynamic mobile environment (DME). This leads to renewed adoption of lightweight solutions for the identification of the most suitable web services that correspond with the service requests. Contemporary mobile web service discovery approaches are plagued with performance and accuracy problems and are rarely compatible with the DME. The objective of this systematic literature review is to develop a more rigorous understanding and identify recent research trends in mobile web service discovery techniques in a dynamic mobile environment. This review followed the systematic literature review (SLR) guidelines. Essential information was extracted from the 76 relevant articles in line with the formulated questions and finally reported after in-depth analysis. The results of this study discuss the critical contributions and limitations of the proposed approaches.

Multi-Strategy Web Service Discovery for Smart Government

2014 ◽  
Vol 536-537 ◽  
pp. 625-631 ◽  
Author(s):  
Yun Yun Du ◽  
Xue Qin
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Large Scale ◽  
Search Space ◽  
Semantic Matching ◽  
Business Systems ◽  
Keyword Query ◽  
Web Service Discovery ◽  
Wide Range ◽  
Smart Government

Semantic Web Service technology is the solution to system integration and business collaboration for smart government which is cross-border and heterogeneous on a large scale. However the tremendous Web services search space caused by the wide range, large scale and complex e-government business systems is one of the great challenges for smart government. The paper focuses on researches about service discovery in e-government business integration for smart government. In accordance with the application environment and the current technical status of e-government, the author proposes a multi-strategy Web service discovery method on the basis of the proposed semantic model. The discovery process comprises three stages: keyword query with semantic enhancement, IO semantic matching and PE semantic matching. Finally similarity calculating method is proposed to evaluate the matching degree of each candidate service for service selection as well as the conclusions.

Self-Adaptive QoS-Aware Web Service Discovery using Ontology Approach

2015 ◽  
Vol 7 (3) ◽  
pp. 65-84 ◽  
Author(s):  
Nwe Nwe Htay Win ◽  
Bao Jianmin ◽  
Cui Gang ◽  
Saif Ur Rehman
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Feasible Solution ◽  
Evaluation Criteria ◽  
Discovery Process ◽  
Web Service Discovery ◽  
User Request ◽  
Adaptive Qos ◽  
Concept Attribute ◽  
Self Adaptive

In recent years, although semantic has been widely used in service discovery mechanisms, it still needs to exploit all semantic aspects included in service documents so that the discovered service can highly be relevant with user request. Moreover, it also needs to consider self-adaptability in discovering the services which can adapt to searching conditions or parameters in order to find other suitable and potential services if no feasible solution could exactly satisfy user QoS requirements. Therefore, this paper proposes a novel self-adaptive QoS-based service discovery mechanism which can adapt the discovery process with the help of semantically structured ontology trees if unexpected results are encountered. The discovery process matches the equivalences between service advertisement and requirement using three similarity evaluation criteria namely concept, attribute and constraint similarity. This discovery process is repeated until feasible solution is found and a set of most suitable services are returned to the users. The authors prototype their system called SQoSD to evaluate the efficiency and adaptability compared with OWLS-CPS and RQSS. The experimental results prove that our mechanism is superior to the other compared mechanisms.

Sign in / Sign up

Export Citation Format

Share Document