Semantic-driven matchmaking of web services using case-based reasoning

With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilises OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services

Improving Semantic Web Services Discovery Using SPARQL-Based Repository Filtering

Semantic Web Services discovery is commonly a heavyweight task, which has scalability issues when the number of services or the ontology complexity increase, because most approaches are based on Description Logics reasoning. As a higher number of services becomes available, there is a need for solutions that improve discovery performance. Our proposal tackles this scalability problem by adding a preprocessing stage based on two SPARQL queries that filter service repositories, discarding service descriptions that do not refer to any functionality or non-functional aspect requested by the user before the actual discovery takes place. This approach fairly reduces the search space for discovery mechanisms, consequently improving the overall performance of this task. Furthermore, this particular solution does not provide yet another discovery mechanism, but it is easily applicable to any of the existing ones, as our prototype evaluation shows. Moreover, proposed queries are automatically generated from service requests, transparently to the user. In order to validate our proposal, this article showcases an application to the OWL-S ontology, in addition to a comprehensive performance analysis that we carried out in order to test and compare the results obtained from proposed filters and current discovery approaches, discussing the benefits of our proposal

Prikaz znanja u internetu stvari: semantičko modeliranje i njegove primjene

Semantic modelling provides a potential basis for interoperating among different systems and applications in the Internet of Things (IoT). However, current work has mostly focused on IoT resource management while not on the access and utilisation of information generated by the “Things”. We present the design of a comprehensive and lightweight semantic description model for knowledge representation in the IoT domain. The design follows the widely recognised best practices in knowledge engineering and ontology modelling. Users are allowed to extend the model by linking to external ontologies, knowledge bases or existing linked data. Scalable access to IoT services and resources is achieved through a distributed, semantic storage design. The usefulness of the model is also illustrated through an IoT service discovery method.Semantičko modeliranje pruža potencijalnu osnovu za me.udjelovanje različitih sustava i aplikacija unutar interneta stvari (IoT). Međutim, postojeći radovi uglavnom su fokusirani na upravljanje IoT resursima, ali ne i pristupu i korištenju informacija koje generira “stvar”. Predstavljamo projektiranje sveobuhvatnog i laganog semantičkog opisnog modela za prikaz znanja u IoT domeni. Projektiranje slijedi široko-priznate najbolje običaje u inženjerstvu znanja i ontološkom modeliranju. Korisnicima se dopušta proširenje modela povezivanjem na eksterne ontologije, baze znanja ili postoje će povezane podatke. Skalabilni pristup IoT uslugama i resursima postiže se kroz distribuirano, semantičko projektiranje pohrane. Upotrebljivost modela tako.er je ilustrirana kroz metodu pronalaska IoT usluga

Towards a Unifying View of QoS-Enhanced Web Service Description and Discovery Approaches

The number of web services increased vastly in the last years. Various providers offer web services with the same functionality, so for web service consumers it is getting more complicated to select the web service, which best fits their requirements. That is why a lot of the research efforts point to discover semantic means for describing web services taking into account not only functional characteristics of services, but also the quality of service (QoS) properties such as availability, reliability, response time, trust, etc. This motivated us to research current approaches presenting complete solutions for QoS enabled web service description, publication and discovery. In this paper we present comparative analysis of these approaches according to their common principals. Based on such analysis we extract the essential aspects from them and propose a pattern for the development of QoS-aware service-oriented architectures

From software APIs to web service ontologies: a semi-automatic extraction method

Successful employment of semantic web services depends on the availability of high quality ontologies to describe the domains of these services. As always, building such ontologies is difficult and costly, thus hampering web service deployment. Our hypothesis is that since the functionality offered by a web service is reflected by the underlying software, domain ontologies could be built by analyzing the documentation of that software. We verify this hypothesis in the domain of RDF ontology storage tools.We implemented and fine-tuned a semi-automatic method to extract domain ontologies from software documentation. The quality of the extracted ontologies was verified against a high quality hand-built ontology of the same domain. Despite the low linguistic quality of the corpus, our method allows extracting a considerable amount of information for a domain ontology

Methods for Efficient and Accurate Discovery of Services

With an increasing number of services developed and offered in an enterprise setting or the Web, users can hardly verify their requirements manually in order to find appropriate services. In this thesis, we develop a method to discover semantically described services. We exploit comprehensive service and request descriptions such that a wide variety of use cases can be supported. In our discovery method, we compute the matchmaking decision by employing an efficient model checking technique

An intelligent framework for dynamic web services composition in the semantic web

As Web services are being increasingly adopted as the distributed computing technology of choice to securely publish application services beyond the firewall, the importance of composing them to create new, value-added service, is increasing. Thus far, the most successful practical approach to Web services composition, largely endorsed by the industry falls under the static composition category where the service selection and flow management are done a priori and manually. The second approach to web-services composition aspires to achieve more dynamic composition by semantically describing the process model of Web services and thus making it comprehensible to reasoning engines or software agents. The practical implementation of the dynamic composition approach is still in its infancy and many complex problems need to be resolved before it can be adopted outside the research communities. The investigation of automatic discovery and composition of Web services in this thesis resulted in the development of the eXtended Semantic Case Based Reasoner (XSCBR), which utilizes semantic web and AI methodology of Case Based Reasoning (CBR). Our framework uses OWL semantic descriptions extensively for implementing both the matchmaking profiles of the Web services and the components of the CBR engine. In this research, we have introduced the concept of runtime behaviour of services and consideration of that in Web services selection. The runtime behaviour of a service is a result of service execution and how the service will behave under different circumstances, which is difficult to presume prior to service execution. Moreover, we demonstrate that the accuracy of automatic matchmaking of Web services can be further improved by taking into account the adequacy of past matchmaking experiences for the requested task. Our XSCBR framework allows annotating such runtime experiences in terms of storing execution values of non-functional Web services parameters such as availability and response time into a case library. The XSCBR algorithm for matchmaking and discovery considers such stored Web services execution experiences to determine the adequacy of services for a particular task. We further extended our fundamental discovery and matchmaking algorithm to cater for web services composition. An intensive knowledge-based substitution approach was proposed to adapt the candidate service experiences to the requested solution before suggesting more complex and computationally taxing AI-based planning-based transformations. The inconsistency problem that occurs while adapting existing service composition solutions is addressed with a novel methodology based on Constraint Satisfaction Problem (CSP). From the outset, we adopted a pragmatic approach that focused on delivering an automated Web services discovery and composition solution with the minimum possible involvement of all composition participants: the service provider, the requestor and the service composer. The qualitative evaluation of the framework and the composition tools, together with the performance study of the XSCBR framework has verified that we were successful in achieving our goal

concept paper

In this concept paper, we outline our working plan for the next phase of the Corporate Semantic Web project. The plan covers the period from March 2009 to March 2010. Corporate ontology engineering will improve the facilitation of agile ontology engineering to lessen the costs of ontology development and, especially, maintenance. Corporate semantic collaboration focuses the human- centered aspects of knowledge management in corporate contexts. Corporate semantic search is settled on the highest application level of the three research areas and at that point it is a representative for applications working on and with the appropriately represented and delivered background knowledge. Each of these pillars will yield innovative methods and tools during the project runtime until 2013. We propose a concept draft and a working plan covering the next twelve months for an integrative architecture of a Corporate Semantic Web provided by these three core pillars

An architecture for user preference-based IoT service selection in cloud computing using mobile devices for smart campus

The Internet of things refers to the set of objects that have identities and virtual personalities operating in smart spaces using intelligent interfaces to connect and communicate within social environments and user context. Interconnected devices communicating to each other or to other machines on the network have increased the number of services. The concepts of discovery, brokerage, selection and reliability are important in dynamic environments. These concepts have emerged as an important field distinguished from conventional distributed computing by its focus on large-scale resource sharing, delivery and innovative applications. The usage of Internet of Things technology across different service provisioning environments has increased the challenges associated with service selection and discovery. Although a set of terms can be used to express requirements for the desired service, a more detailed and specific user interface would make it easy for the users to express their requirements using high-level constructs. In order to address the challenge of service selection and discovery, we developed an architecture that enables a representation of user preferences and manipulates relevant descriptions of available services. To ensure that the key components of the architecture work, algorithms (content-based and collaborative filtering) derived from the architecture were proposed. The architecture was tested by selecting services using content-based as well as collaborative algorithms. The performances of the algorithms were evaluated using response time. Their effectiveness was evaluated using recall and precision. The results showed that the content-based recommender system is more effective than the collaborative filtering recommender system. Furthermore, the results showed that the content-based technique is more time-efficient than the collaborative filtering technique