Automating Web Service Composition: An Ontological Agent Framework

Automating Web Service Composition: An Ontological Agent Framework

Tamer M. Al Mashat (Cairo University, Egypt), Fatma A. El-Licy (Cairo University, Egypt) and Akram I. Salah (Cairo University, Egypt)
DOI: 10.4018/978-1-4666-6178-3.ch014
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Abstract

In the Service-Driven Computing paradigm, applications are typically built by composing a set of Web services. Web service composition facilitates rapid development of applications via service reuse and enables the creation of complex services from simpler application services. Research efforts in the area of Web service composition are concerned mainly with two challenges, namely automated service synthesis and verification of the composed Web services. This chapter presents a framework for Web service composition based on semantic specification through OWL-S to establish an ontological agent for automating Web service composition. The semantic description serves to define the planning domain for the agent to automate the composition procedure. A Petri nets model is applied to build a formal representation of the structure and behavior of the service. Finally, AND-OR graph methodology is used to represent the dependences among Web services to select between alternatives based on Quality of Service.
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Introduction

The World Wide Web is evolving from being just a collection of pages to being a collection of services that interoperate through the Internet. Services provide a new Web model, in which, sites exchange dynamic information on demand. The Web has become a provider of different kinds of business to customer (B2C) and business to business (B2B) services for governments, organizations, and individuals. With the rapid growth of the Web, its services become more complex and versatile. When a single Web service is not enough to satisfy a required functionality, there exists the potential to compose new services from existing ones.

Service composition, however, is a complicated task to be handled manually. The cause of complexity, in general, is three fold. First, the number of services available over the Web is continuously increasing which complicates the search in the massive Web service repository. Second, existing Web services may be updated and new Web services may be created on the fly, thus, an effective composition system should be able to detect those changes in order to make the decision based on the up to date information. Third, because Web services are developed and specified under a diversity of concept models, there are no agreements on a unique language to define and evaluate a given Web service. This diversity of the service composition complexities motivates the necessity for a semantic understanding of the Web services. These complexities dictate the inevitability of developing an automatic or semi-automatic tool for Web service composition.

Automated Web service composition (WSC) is akin to both the Artificial Intelligence (AI) planning problem and software synthesis problem and draws heavily on the research areas of both (McIlraith & Son, 2002). Software synthesis refers to a process that generates functions, data structures, or entire programs from problem specifications (Hewett, 1996). Automated WSC is achieved through a reasoning system that organizes, combines, and executes Web services, which collectively achieves user’s objectives (Pistore, et al. 2005). The reasoning system involves resolving constraints between given Web service inputs, outputs, preconditions, and effects (IOPEs), and typically, the desired outputs and effects (OEs). For example, if one starts with user’s goal (some desired outputs and effects), and matches it to the outputs and effects of a Web service (modeled as a process), the result is an instantiation of a process plus descriptions of new goals to be satisfied based on the inputs and preconditions of that process.

The new goals (inputs and preconditions) would hopefully match other processes (outputs and effects), so that composition occurs intrinsically. The constraints between these inputs, outputs, preconditions, and effects dictate the nominated Web services. Web service preconditions and (conditional) effects are not encoded in any existing industrial standard. Yet, they are available as an unambiguous computer-interpretable form in OWL-S (Ouassila, & Zizette, 2011).

Composition problems can be distinguished into two types (Martin et al., 2007): those that involve only information-providing services and those that involve both information-providing and world-altering services. The former requires a rich semantic representation of inputs and outputs (IO), whereas, the latter requires a representation of IOPEs. The findings of matching Web services to a given IOPEs could include several alternatives; therefore, a choice method must be available to elect one of them.

The objective of the introduced ontological agent framework is to provide a higher/complex service by composing a set of Web services when no atomic service meets user requirements. The ontological agent accomplishes this task by manipulating user goals according to the OWL-S service description which defines the planning domain’s business process workflow for the agent. Service composition is established by transforming OWL-S process model to Petri nets model to verify certain properties such as reachability, liveness, and deadlocks. Subsequently, the Web service discovery is based on the Petri nets model information (IOPE).The discovered Web services are represented in AND-OR graphs which provide the convenience of selecting between alternatives based on QoS.

Key Terms in this Chapter

Simple Object Access Protocol: An XML-based communication protocol to access the Web services over the network using transport protocol such as HTTP. SOAP is language and platform independent.

Web Service: A modular application that can be described, located, and invoked on the Internet. A Web service is designed to support interoperable machine-to-machine interaction over a network. It has an interface described in a machine processable format, specifically WSDL.

Semantic Web Services: Web services annotated with semantics. Semantic Web services extend the existing Web services with semantic capability.

Web Service Composition: Combination and coordination of a set of services with the purpose of achieving functionality that cannot be realized through existing services.

Web Ontology Language for Services: A high level language (XML-based) used for describing Web service properties. It consists of three parts: service profile, process model, and grounding. Service profile includes general information and is used to describe what the service will do. A process model describes how the service will perform its functionally and the grounding describes links with industry standards. Its main goal is to enable users to automatically discover, invoke, compose, and execute Web services under certain conditions.

Universal Description, Discovery, and Integration: A Web-based distributed directory that enables businesses to list themselves on the Internet and discover each other, similar to a traditional phone book's yellow and white pages.

Software Agent: A piece of software capable of performing the specified tasks on behalf of the user.

Petri Nets: A formal and graphical technique for the specification and analysis of concurrent, discrete-event-based dynamic systems.

Web Service Description Language: An XML-formatted language used to describe a Web service's capabilities as collections of communication endpoints capable of exchanging messages. It provides a machine-readable description of how the service can be called, what parameters it expects, and what data structures it returns. It thus serves a purpose that corresponds roughly to that of a method signature in a programming language.

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