Web Service Discovery Architecture Research Articles

Multi-Layer Web Services Discovery Using Word Embedding and Clustering Techniques

We propose a multi-layer data mining architecture for web services discovery using word embedding and clustering techniques to improve the web service discovery process. The proposed architecture consists of five layers: web services description and data preprocessing; word embedding and representation; syntactic similarity; semantic similarity; and clustering. In the first layer, we identify the steps to parse and preprocess the web services documents. In the second layer, Bag of Words with Term Frequency–Inverse Document Frequency and three word-embedding models are employed for web services representation. In the third layer, four distance measures, namely, Cosine, Euclidean, Minkowski, and Word Mover, are considered to find the similarities between Web services documents. In layer four, WordNet and Normalized Google Distance are employed to represent and find the similarity between web services documents. Finally, in the fifth layer, three clustering algorithms, namely, affinity propagation, K-means, and hierarchical agglomerative clustering, are investigated for clustering of web services based on observed similarities in documents. We demonstrate how each component of the five layers is employed in web services clustering using randomly selected web services documents. We conduct experimental analysis to cluster web services using a collected dataset consisting of web services documents and evaluate their clustering performances. Using a ground truth for evaluation purposes, we observe that clusters built based on the word embedding models performed better than those built using the Bag of Words with Term Frequency–Inverse Document Frequency model. Among the three word embedding models, the pre-trained Word2Vec’s skip-gram model reported higher performance in clustering web services. Among the three semantic similarity measures, path-based WordNet similarity reported higher clustering performance. By considering the different word representations models and syntactic and semantic similarity measures, we found that the affinity propagation clustering technique performed better in discovering similarities among Web services.

An Architecture for Restful Web Service Discovery Using Semantic Interfaces

In the internet environment, web services based on representational state transfer (REST) have become the de facto standard. The addition of semantics is intended to enhance the description of web services with information that enables automatic agents to understand their data. However, the existence of different languages to semantically describe services makes it difficult to discover and select the service that best meets a requirement. Furthermore, relatively few proposals have a RESTful service semantic description, making the discovery process for RESTful services more difficult. This work proposes a RESTful semantic web service discovery architecture based on semantic interfaces (SERIN). SERIN is an ontology with annotations that semantically describe RESTful web services. This architecture enables software agents to automatically discover and make service calls in order to execute a determined task.

Web Service Discovery for Cloud-Based Mobile Application Using Multi-Level Clustering and QoS-Based Ranking

Since many service providers are providing similar web services, finding an accurate web service based on user preferences is becoming a challenging task. Therefore, enhancing web service discovery (WSD) method will improve the searching performance. In this paper, we firstly discuss and review some existing web service discovery approaches and identify their limitations. Subsequently, we propose a web service discovery method for cloud-based mobile application by using multi-level clustering technique to improve performance by reducing the searching scope. Our web service discovery architecture is able to increase the discoverability of more accurate web services based on user's preferences. Meanwhile, user preference Quality of Services (QoS) attributes are also used for ranking procedure to allow user to decide the quality of the mobile application. The experimental results show that our approach is able to increase the searching performance and provide a reliable list of selection for users.

Using semantic information for distributed web service discovery

With the increase in number and size of service registries, web service discovery becomes a challenging activity. There is also tremendous increase in the number of web services that are not registered to any of the business registries. Under these conditions, finding an appropriate web service may lead to problems in terms of performance, efficiency, end-to-end security and quality of the discovered services. Use of semantic information has been studied in web service discovery for improving the accuracy of the service discovery task. However, semantic information can be useful for improving the time efficiency as well. In this work, we propose a web service discovery architecture that is based on a coordinated set of domain-specific service discoverers crawling both business registries and private sites. By distributed and domain-specific crawling, it is aimed to shorten the search time and to provide up-to-date service status and load balancing via scalability.

Dynamic Web Service discovery architecture based on a novel peer based overlay network

Service Oriented Computing and its most famous implementation technology Web Services (WS) are becoming an important enabler of networked business models. Discovery mechanisms are a critical factor to the overall utility of Web Services. So far, discovery mechanisms based on the UDDI standard rely on many centralized and area-specific directories, which poses information stress problems such as performance bottlenecks and fault tolerance. In this context, decentralized approaches based on Peer to Peer overlay networks have been proposed by many researchers as a solution. In this paper, we propose a new structured P2P overlay network infrastructure designed for Web Services Discovery. We present theoretical analysis backed up by experimental results, showing that the proposed solution outperforms popular decentralized infrastructures for web discovery, Chord (and some of its successors), BATON (and it’s successor) and Skip-Graphs.

Aligning with the Web: an atom-based architecture for Web services discovery

During the past three years, the Web has undergone a radical change towards a highly user-centred cyberspace where end users can easily participate and collaborate for their own benefits and profits. The surge of Web services has created increasingly demand by end users and small-and-medium enterprises to effectively participate in service publication, discovery, and subscription over the Web. However, current public service discovery mechanism, one of the key aspects in the SOA, does not align itself with this fully user-oriented Web. The recent shutdown of public UDDI exposes issues and makes public Web services discovery missing. In this paper, we propose a novel Web service discovery architecture—AtomServ, which is built upon widely adopted Web2.0 technology (RSS/Atom) and the publish/subscribe model. It aims to provide a handy and scalable discovery facility for most Web services providers and requesters, who can easily participate in service discovery via various user-friendly application interfaces (e.g., web browsers, mobile phones). With the proliferation of RSS/Atom, AtomServ widens the adoption of service discovery by allowing simple and unified user access to frequently changing business services. This undoubtedly lowers the entry barrier for end users to play their roles in a user-centred Service-Oriented Web environment.