The PORSCE II Framework: Using AI Planning for Automated Semantic Web Service Composition (original) (raw)

Semantic awareness in automated web service composition through planning

… : Theories, Models and …, 2010

Abstr act. PORSCE II is a framework that performs automatic web service composition by transforming the composition problem into AI planning terms and utilizing external planners to obtain solutions. A distinctive feature of the system is that throughout the entire process, it achieves semantic awareness by exploiting semantic information extracted from the OWL-S descriptions of the available atomic web services and the corresponding ontologies. This information is then used in order to enhance the planning domain and problem. Semantic awareness facilitates approximations when searching for suitable atomic services, as well as modification of the produced composite service. The alternatives for modification include the replacement of a certain atomic service that takes part in the composite service by an equivalent or a semantically relevant service, the replacement of an atomic service through planning, or the replanning from a certain point in the composite service. The system also provides semantic representation of the produced composite service.

PORSCE II: Using planning for semantic web service composition

Proc. of the …, 2009

This paper presents PORSCE II, an integrated system that performs automatic semantic web service composition through planning. In order to achieve that, an essential step is the translation of the web service composition problem into a planning problem. The planning problem is then solved using external domain-independent planning systems, and the solutions are visualized and evaluated. The system exploits semantic information to enhance the translation and planning processes.

An integrated approach to automated semantic web service composition through planning

2012

Abstract The paper presents an integrated approach for automated semantic web service composition using AI planning techniques. An important advantage of this approach is that the composition process, as well as the discovery of the atomic services that take part in the composition, are significantly facilitated by the incorporation of semantic information.

Semantically Aware Web Service Composition Through AI Planning

International Journal on Artificial Intelligence Tools, 2015

Web service composition is a significant problem as the number of available web services increases; however, manual composition is not an efficient option. Automated web service composition can be performed using AI Planning techniques, utilizing descriptions of available atomic web services, enhanced with semantic awareness and relaxation. This paper discusses a unified, semantically aware approach, handling both semantic (OWL-S & SAWSDL) and non-semantic (WSDL) web service descriptions. In the first case, ontology analysis is adopted to semantically enhance the planning domains and problems, in order to deal with cases where exact syntactic input-to-output matching is not feasible. In the non-semantic descriptions case, semantic information is acquired utilizing alternative sources such as lexical thesauri. Concept similarity measures are applied and utilized to achieve the desired degree of semantic relaxation. The solution to a web service composition problem is a plan describin...

Web service composition as a planning task: Experiments using knowledge-based planning

2004

Motivated by the problem of automated Web service composition (WSC), in this paper, we present some empirical evidence to validate the effectiveness of using knowledge-based planning techniques for solving WSC problems. In our experiments we utilize the PKS (Planning with Knowledge and Sensing) planning system which is derived from a generalization of STRIPS. In PKS, the agent's (incomplete) knowledge is represented by a set of databases and actions are modelled as revisions to the agent's knowledge state rather than the state of the world. We argue that, despite the intrinsic limited expressiveness of this approach, typical WSC problems can be specified and solved at the knowledge level. We show that this approach scales relatively well under changing conditions (e.g. user constraints). Finally, we discuss implementation issues and propose some architectural guidelines within the context of an agent-oriented framework for inter-operable, intelligent multi-agent systems for WSC and provisioning.

Planning for semantic web services

Semantic Web Services Workshop at 3rd International …, 2004

Using Semantic Web ontologies to describe Web Services has proven to be useful for various different tasks including service discovery and composition. AI planning techniques have been employed to automate the composition of Web Services described this way. Planners use the description of the preconditions and effects of a service to do various sorts of reasoning about how to combine services into a plan. OWL-S 1.1 will support the description of the preconditions and effects of services using OWL statements similar to atoms in Semantic Web Rule Language (SWRL). Thus, planners are required to understand the semantics of OWL in order to evaluate such preconditions. However, planners typically support only fairly limited reasoning capabilities which cannot handle the expressivity of Semantic Web ontologies. In particular, planners typically make the closed world assumption, whereas OWL has open world semantics. In this paper, we demonstrate how an OWL reasoner can be integrated with an AI planner to overcome these problems. We identify the challenges of writing the service descriptions and reasoning about them when OWL is used to describe preconditions and effects. We also investigate the efficiency of such an integrated system and show how OWL reasoning can be optimized for this system. Finally, we present the performance results of our prototype implementation.

Translating web services composition plans to OWL-S descriptions

Abstract: Web Services technology has led to simpler and more rapid development of Web Applications with improved functionality by which several platforms through the globe can communicate to exchange data and cooperate for problem solving. Methods for automated web services composition are studied so as to enhance this type of software development. Many studies focus on converting the composition problem to a planning problem and solving it using known planning algorithms.

Context optimization of AI planning for semantic Web services composition

Service Oriented Computing and Applications, 2007

Web services composition techniques are gaining momentum as the opportunity to establish reusable and versatile inter-operability applications. Many researchers propose their composition approach based on planning techniques. We propose our context aware planning method which comprises global planning and local optimization based on context information. The major technical contributions of this paper are: (1) We propose an ontology-based framework for the context-aware composition of Web services. Context model, which are structured based on OWL-S, captures the Service-related, Environment-related, and User-related context and can be used in an unambiguous, machine interpretable form. (2) We propose context-aware plan architecture and thus is more scalability and flexibility for the planning process, and thereby improving the efficiency and precision. (3) We propose a hybrid approach to build a plan corresponding to a context-aware service composition, based on global planning and local optimization, considering both the usability and adoption. We test our approach on a simple, yet realistic example, and the preliminary results demonstrate that our implementation provides a practical solution.

Towards Semantic Web Service Engineering

… Resource Retrieval in …, 2007

Semantic Web Services are a research effort to automate the usage of Web services, a necessary component for the Semantic Web. Traditionally, Web service discovery depends on detailed formal semantic descriptions of available services. Since a complete detailed service description is not always feasible, the client software cannot select the best service offer for a given user goal only by using the static service descriptions. Therefore the client needs to interact automatically with the discovered Web services to find information about the available concrete offers, after which it can select the best offer that will fulfill the user's goal. This paper shows when and why complete semantic description is unfeasible, it defines the role and position of offer discovery, and it suggests how it can be implemented and evaluated.

Automated composition of web services by planning at the knowledge level

… JOINT CONFERENCE ON …, 2005

In this paper, we address the problem of the automated composition of web services by planning on their "knowledge level" models. We start from descriptions of web services in standard process modeling and execution languages, like BPEL4WS, and automatically translate them into a planning domain that models the interactions among services at the knowledge level. This allows us to avoid the explosion of the search space due to the usually large and possibly infinite ranges of data values that are exchanged among services, and thus to scale up the applicability of state-of-the-art techniques for the automated composition of web services. We present the theoretical framework, implement it, and provide an experimental evaluation that shows the practical advantage of our approach w.r.t. techniques that are not based on a knowledgelevel representation.