1.1 Research background
The Web was originally used for sharing information among scientists. At the beginning, this Document Web was used to store and share static information but it has gained increasing attention due to the advance of Internet technologies and the enhancement of hardware capabilities. The Web has changed its direction into being a Service Web which provides not only support for document sharing, but also the ability to enable organizations to provide their applications or services via the Web –the Internet. Consequently, the concept of Web services [1],[2],[3] has become widely relevant.
A Web service is a set of related functionalities which can be automatically accessed through the Web [3] and it makes information and software available and executable over the Internet, so it can be utilized as a building block for applications [4]. Web services can be registered (advertised) and queried (searched) by using Universal Description, Discovery and Integration (UDDI) [5]. In the meantime the Web Services Description Language (WSDL) [6] and the Simple Object Access Protocol (SOAP) [10] provide a machine-processable interface in which components that contribute to a composite web service can be executed automatically.
Two types of Web services are identified: simple and composite [9]. A simple service, a primitive service, is standalone and Internet-based application which can fulfillconsumers’ requests without any other Web services. A composite service is conceived as a conglomeration of several simple Web services over a designated flow structure [7],[8].
These primitive services can be grouped and they interact with each other to provide consumers a complete value-added service. For example, car dealer, insurance, and financial
loan services can be combined as a comprehensive car sale service.
Widely available and standardized Web service technologies make collaboration among different organizations possible. Web services are now used for developing and integrating highly distributed and heterogeneous systems in different domains such as e-business, grid services, and e-government systems. With service popularity and complexity, the concept of Service Oriented Architecture (SOA) or Service Oriented Computing (SOC) [23],[38],[55]
has been introduced and it has gained increasing significance in the research field of information systems. It attempts to provide a systematic approach for service composition in order to achieve Web services (components) sharing and reuse.
Two related concept in SOA / SOC are composite services and service composition. A composite service is a complex Web service which is composed of a number of simple (primitive) Web services. Service composition is the construction process of composite services [8]. Ideally, different primitive Web services within a complex Web service can come from diverse service providers and this leads to a new arduous problem –the issue of service semantics. Even though one output parameter of one primitive Web service has the same name and type with an input parameter of another primitive Web service, it is not necessary that these parameters can be linked up to form a consistent composite service.
The Semantic Web [13] has been proposed to dispose of the semantic issues. Many academic researchers and developers are endeavouring to build ontology for Web services.
The goal of the Semantic Web is to make the Web services not only understandable by humans but also by machines through adding semantic information to the advertised services and to the service requirement specifications in order to increase interoperability among primitive Web services. Several standards such as the Web Ontology Language (OWL) [14]
and the Web Ontology Language for Services (OWL-S or formerly DAML-S) [15] have been
introduced to achieve this goal. These standards help to handle the semantic issues that occur in Web service utilization.
1.2 Motivation and objective
In order to fully realize the benefit of the automation of Web service composition, service discovery is a crucial process for Web service utilization. Most of existing service composition approaches [38],[42],[43] assume that all primitive services are ready-to-use in someplace or can be identified via simple UDDI queries. Discovery or so-called matchmaking1 is considered as a search problem in a bounded space. It takes service consumers’ requests and a collection of services from services providers as input via its discovery mechanism to identify a list of best matched pairs. Some researches [16],[18]
handle the discovery problem by incorporating Semantic Web technologies. However, there are still two major problems that should be tackled in order to achieve an effective and efficient discovery process.
Principally, the issues associated with service discovery that involve the Web service having data repositories are not well addressed by the existing methods which focus on service capabilities, interface signatures, or functionalities. These methods are inadequate to identify appropriate services among the services which have similar functionalities, so it requires service consumers to include additional aspects (i.e. content of service or reputation) to evaluate services. In the context of Web service discovery, the representation of services and the selection of searching criteria are the critical factors to determine the quality of the output. Measuring the similarity between a serviceconsumer’srequests and the provided services in terms of: the software signatures; the capabilities; the syntax, and the semantics of services is a common element in discovery [12],[16],[18],[51]. However, recent work on
1 In this thesis, the term discovery will be used for consistency when discussing search or matchmaking.
Web service discovery has not paid sufficient attention to the use of underlying data and information about services as a search criterion.
Second, an effective service discovery mechanism to enable the formation of the required composite services that provide the required functionality is able to support the identification of the required services in a dynamic environment. The service consumers and providers often have different views on the content of services. Most of the existing service discovery approaches such as [12],[16],[17],[18],[19],[49],[50] and [51], based on either functional or non-functional attributes, do not address the issues associated with the impact of the diverse preferences and subjective expectations of the service consumers and providers which are generally used in searching for or in advertising Web services. Because consumers and providers often have different views on the content of services, the selected results may notconform to consumers’expectations and this hinders the efficiency of service discovery.
This study proposed a consensus-based service discovery approach which attempts to use the underlying data and information about services as a search criterion (quality rating).
Pre-classified services provide supplementary information with a higher level of abstraction, such as a quality rating for Cheap. This represents the capabilities and the underlying data associated with services. The proposed method attempts to refine the search space and to increase the precision rate in discovery. In the meanwhile, consumers are allowed to do search by using linguistic terms such as Cheap or Comfortable. Moreover, this consensus-based approach models subjective and fuzzy opinions and assists service consumers and providers in reaching a common consensus so that the cognitive differences among service consumers can be mitigated and the efficiency of service discovery can be increased. This approach, which is based on fuzzy group decision making methods and Semantic Web technologies, can be executed iteratively and therefore further fuzzy opinions
and preferences can be added to improve the precision of Web service discovery. The proposed approach will be implemented as a prototype system and tested through various experiments to demonstrate the effectiveness of the proposed approach.
1.3 Research approach
In this study, five research steps were adopted to solve the problems of service discovery mentioned above. These are described as follows:
(1) Overall literature review: reviewing the existing works about the Web services, Web services composition, Service Oriented Architecture (SOA) / Service Oriented Computing (SOC), the Semantic Web, and the tools for realizing these concepts.
(2) Research concept development: the research concept was generated mainly through literature review. In addition brainstorming and consultation with experts at international conferences was used to help identify a viable solution to the problem.
(3) Detailed literature review: the use of fuzzy set concepts being identified the research process focussed on studies of fuzzy set and theory, related to reaching a consensus.
These were concerns with concepts such as: fuzzy opinion representation; fuzzy majorities; fuzzy similarity measurement; fuzzy aggregation; reaching consensus;
resolution methods for group decision problems; and, the methodologies used to collect imprecise preferences.
(4) Architecture development: the proposed approach was implemented as a prototype system to solve the two major issues of service discovery mentioned in Section 1.2.
The main modules were employed to pre-classify the Web services in terms of different QoS terms. A method for reaching consensus over these terms used among service consumers and providers was implemented.
(5) Architecture verification: the proposed approach was tested through various experiments in which the data were collected from several famous website. The results demonstrate the effectiveness of the proposed approach.
1.4 Organization
The rest of this dissertation is structured as follows. Chapter 2 contains the literature reviews which include the descriptions of Web service composition, discovery and its related technologies. Chapter 3 will describe the fuzzy set theories which are used in reaching a consensus. The proposed architecture, including its scope, constraints and implementation considerations, will be presented in Chapter 4. Case studies and performance evaluations are presented in Chapter 5. Chapter 6 concludes this work and proposes the future work.
Finally, the references and appendix are attached at the end of the dissertation.