Applying CBR Over an AI Planner for Dynamic Web Service Composition (original) (raw)

Dynamic Web Service Composition. Use of Case Based Reasoning and AI Planning

2012

Web services have emerged as a major technology for deploying automated interactions between distributed and heterogeneous applications. The main advantage of web services composition is the possibility of creating valueadded services by combining existing ones to achieve customized tasks. How to combine these services efficiently into an arrangement that is both functionally sound and architecturally realizable is a very challenging topic that has founded a significant research area within computer science. A great deal of recent webrelated research has concentrated on dynamic web service composition. Most of proposed models for dynamic composition use semantic descriptions of web services through the construction of domain ontology. In this paper, we present our approach to dynamically produce composite services. It is based on the use of two AI techniques: Case-Based Reasoning and AI planning. Our motivating scenario concerns a national system for the monitoring of childhood immu...

Semantic Web Services Composition with Case Based Reasoning

Intelligent, Adaptive and Reasoning Technologies, 2011

Web service development is encouraging scenarios where individual or integrated application services can be seamlessly and securely published on the Web without the need to expose their implementation details. However, as Web services proliferate, it becomes difficult to matchmake and integrate them in response to users requests. The goal of our research is to investigate the utilization of the Semantic Web in building a developer-transparent framework facilitating the automatic discovery and composition of Web services. In this chapter, we present a Semantic Case Based Reasoner (SCBR) framework that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and composition. Our approach is original as it considers the runtime behaviour of a service resulting from its 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. To facilitate Web services composition, we extend our fundamental discovery and matchmaking algorithm using a lightweight knowledge-based substitution approach 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 the Constraint Satisfaction Problem (CSP).

Utilisation of Case-Based Reasoning for Semantic Web Services Composition

International Journal of Intelligent Information Technologies, 2000

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 article, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking, and investigate the use of case adaptation for service composition. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilizes OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services.

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...

The PORSCE II Framework: Using AI Planning for Automated Semantic Web Service Composition

2009

This paper presents PORSCE II, an integrated system that performs automatic semantic web service composition exploiting AI techniques, specifically planning. Essential steps in achieving web service composition include the translation of the web service composition problem into a solver-ready planning domain and problem, followed by the acquisition of solutions, and the translation of the solutions back to web service terms. The solutions to the problem, that is, the descriptions of the desired composite service, are obtained by means of external domain-independent planning systems, they are visualized and finally evaluated. Throughout the entire process, the system exploits semantic information extracted from the semantic descriptions of the available web services and the corresponding ontologies, in order to perform composition under semantic awareness and relaxation. 2 O. HATZI ET AL.

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.

AI Planning in Web Services Composition: a review of current approaches and a new solution

2000

Web services represent a relevant technology for interoper ability. An important step toward the development of applications basedon Web services is the ability of selecting and integrating heterogeneous s ervices from different sites. When there is no single service capable of performinga given task, there must be some way to adequately compose basic services to execu te this task. The

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.

Abstract Customizing the Composition of Web Services and Beyond

2012

Web services provide a standardized means of publishing diverse, distributed applications. Increasingly, corporations are providing services or programs within and between organiza-tions either on corporate intranets or on the cloud. Many of these services can be composed together, ideally automatically, to provide value-added service. Automated Web service com-position is an example of such automation where given a specification of an objective to be realized and some knowledge of the state of the world, the problem is to automatically select, integrate, and invoke multiple services to achieve the specified objective. A popular approach to the Web service composition problem is to conceive it as an Artificial Intelligence planning task. This enables us to bring to bear many of the theoretical and computational advances in reasoning about actions to the task of Web service composition. However, Web service com-position goes far beyond the reaches of classical planning, presenting a ...

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.