Web service composition has quickly become a key area of research in the services oriented architecture community. One of the challenges in composition is the existence of heterogeneities across independently created and autonomously managed Web service requesters and Web service providers. Previous work in this area either involved significant human effort or in cases of the efforts seeking to provide largely automated approaches, overlooked the problem of data heterogeneities, resulting in partial solutions that would not support executable workflow for real-world problems. In this paper, we present a planning-based approach to solve both the process heterogeneity and data heterogeneity problems. Our system successfully outputs an executable BPEL file which correctly solves non-trivial real-world process specifications outlind in the 2006 SWS Challenge. 1.

Automated matching of semantic service descriptions is the key to automatic service discovery and binding. But when trying to find a match for a certain request it may often happen, that the request cannot be serviced by a single offer but could be handled by combining existing offers. In this case automatic service composition is needed. Although automatic composition is an active field of research it is mainly viewed as a planning problem and treated separatedly from service discovery. In this paper we argue that an integrated approach to the problem is better than seperating these issues as is usually done. We propose an approach that integrates service composition into service discovery and matchmaking to match service requests that ask for multiple connected effects, discuss general issues involved in describing and matching such services and present an efficient algorithm implementing our ideas.

Abstract. We claim that a key component of effective Web service composition, and one that has largely been ignored, is the consideration of user preferences. In this paper we propose a means of specifying and intergrating user preferences into Web service composition. To this end, we propose a means of performing automated Web service composition by exploiting generic procedures together with rich qualitative user preferences. We exploit the agent programming language Golog to represent our generic procedures and a first-order preference language to represent rich qualitative temporal user preferences. From these we generate Web service compositions that realize the generic procedure, satisfying the user’s hard constraints and optimizing for the user’s preferences. We prove our approach sound and optimal. Our system, GologPref, is implemented and interacting with services on the Web. The language and techniques proposed in this paper can be integrated into a variety of approaches to Web or Grid service composition. 1

Thanks to recent advances, AI Planning has become the underlying technique for several applications. Figuring prominently among these is automated Web Service Composition (WSC) at the “capability ” level, where services are described in terms of preconditions and effects over ontological concepts. A key issue in addressing WSC as planning is that ontologies are not only formal vocabularies; they also axiomatize the possible relationships between concepts. Such axioms correspond to what has been termed “integrity constraints ” in the actions and change literature, and applying a web service is essentially a belief update operation. The reasoning required for belief update is known to be harder than reasoning in the ontology itself. The support for belief update is severely limited in current planning tools. Our first contribution consists in identifying an interesting special case of WSC which is both significant and more tractable. The special case, which we term forward effects, is characterized by the fact that every ramification of a web service application involves at least one new constant generated as output by the web service. We show that, in this setting, the reasoning required for belief update simplifies to standard reasoning in the ontology itself. This relates to, and extends,

Abstract — The introduction of Semantic Web techniques in Service-oriented Architectures enables explicit representation and reasoning about semantically rich descriptions of service operations. Those techniques hold promise for the automated discovery, selection, composition and binding of services. This paper describes an approach to derive formal specifications of Web Service compositions on the basis of the interpretation of informal user requests expressed in restricted Natural Language. Our approach leverages the semantic and ontological description of a portfolio of known service operations (called the Semantic Service Catalog). Each user request is processed against a Natural Language vocabulary that includes lexical constructs designed to convey the operations ' semantics, in order to recognize and extract fundamental functional requirements implied by the request, and associate them to entries in the Catalog. In addition, the request interpreter extracts from the request the overall service logic, expressed in terms of a set of modular templates describing control and data flow among the selected operations. The result is a composition specification that associates on demand each user request to a new composed service. That specification is formal and can thus be transformed in an executable flow document for a target service composition engine.

In this paper, we develop a novel algorithm that allows service consumer agents to automatically select and provision service provider agents for their workflows in highly dynamic and uncertain computational service economies. In contrast to existing work, our algorithm reasons explicitly about the impact of failures on the overall feasibility of a workflow, and it mitigates them by proactively provisioning multiple providers in parallel for particularly critical tasks and by explicitly planning for contingencies. Furthermore, our algorithm provisions only part of its workflow at any given time, in order to retain flexibility and to decrease the potential for missing negotiated service time slots. We show empirically that current approaches are unable to achieve a high utility in such uncertain and dynamic environments; whereas our algorithm consistently outperforms them over a range of environments. Specifically, our approach can achieve up to a 27-fold increase in utility and successfully completes most workflows within a strict deadline, even when the majority of providers do not honour their contracts.

Abstract. We claim that user preferences are a key component of effective Web service composition, and one that has largely been ignored. In this paper we propose a means of specifying and intergrating user preferences into Web service composition. To this end, we propose a means of performing automated Web service composition by exploiting a flexible template of the composition in the form of a generic procedure. This template is augmented by a rich specification of user preferences that guide the instantiation of the template. We exploit the agent programming language Golog to represent our templates as Golog generic procedures and we exploit a first-order preference language to represent rich qualitative temporally-extended user preferences. From these we generate Web service compositions that realize a given generic procedure, satisfying the user’s hard constraints and optimizing for the user’s preferences. We prove our approach is sound and optimal. Our system, GologPref, is implemented and interacting with services on the Web. The language and techniques proposed in this paper can be integrated into a variety of approaches to Web or Grid service composition. Preamble We were inspired to include the research that follows in this volume in honour of John Mylopoulos because it touches upon at least two different themes that John has addressed in his research in recent years. In particular, John’s work on Tropos has focused on the specification of information system requirements in terms of actors, goals, and interdependencies. The Tropos methodology can be realized in a variety of agent programming environments, including variants of Golog. John and his colleagues have applied the Tropos methodology to the design of a variety of software systems, including the design of Web services. In this context our Golog Web service composition templates can be seen as a specification of the requirements of our Web service composition, while our user preferences correspond to a specification of soft requirements to be optimized. An earlier version of this paper originally appeared as Web Service Composition

Abstract. To direct automated Web service composition, it is compelling to provide a template, workflow or scaffolding that dictates the ways in which services can be composed. In this paper we present an approach to Web service composition that builds on work using AI planning, and more specifically Hierarchical Task Networks (HTNs), for Web service composition. A significant advantage of our approach is that it provides much of the how-to knowledge of a choreography while enabling customization and optimization of integrated Web service selection and composition based upon the needs of the specific problem, the preferences of the customer, and the available services. Many customers must also be concerned with enforcement of regulations, perhaps in the form of corporate policies and/or government regulations. Regulations are traditionally enforced at design time by verifying that a workflow or composition adheres to regulations. Our approach supports customization, optimization and regulation enforcement all at composition construction time. To maximize efficiency, we have developed novel search heuristics together with a branch and bound search algorithm that enable the generation of high quality compositions with the performance of state-of-the-art planning systems. 1

Web services promise to revolutionise the way computational resources and business processes are offered and invoked in open, distributed systems, such as the Internet. These services are described using machine-readable meta-data, which enables consumer applications to automatically discover and provision suitable services for their workflows at run-time. However, current approaches have typically assumed service descriptions are accurate and deterministic, and so have neglected to account for the fact that services in these open systems are inherently unreliable and uncertain. Specifically, network failures, software bugs and competition for services may regularly lead to execution delays or even service failures. To address this problem, the process of provisioning services needs to be performed in a more flexible manner than has so far been considered, in order to proactively deal with failures and to recover workflows that have partially failed. To this end, we devise and present a heuristic strategy that varies the provisioning of services according to their predicted performance. Using simulation, we then benchmark our algorithm and show that it leads to a 700 % improvement in average utility, while successfully completing up to eight times as many workflows as approaches that do not consider service failures.

Abstract. The rising popularity of RESTful Web services has recently motivated the extension of existing service orchestration engines to support the composition of services that do not rely on machine-readable descriptions. At the same time, within the Linking Open Data initiative, data sets are published conforming to the Linked Data principles, which can be naturally achieved by exposing RDF data through RESTful interfaces. In this position paper, we motivate the use of service orchestration to define workflows for interlinking open data. We introduce the design of an abstract workflow for the semantic enrichment of such data with the purpose of providing an integrated view on otherwise isolated data sources. Finally, based on this abstract workflow we present early work on a concrete implementation and report on our experiences. 1