Optimizing Description Logic Reasoning for the Service Matchmaking and Composition

The Semantic Web is a recent initiative to expose semantically rich information associated with Web resources to build more intelligent Web-based systems. Recently, several projects have embraced this vision and there are several successful applications that combine the strengths of the Web and of semantic technologies. However, Semantic Web still lacks a technology, which would provide the needed scalability and integration with existing infrastructure. In this paper we present our ongoing work on a Semantic Web repository, which is capable of addressing complex schemas and answer queries over ontologies with large number of instances. We present the details of our approach and describe the underlying architecture of the system. We conclude with a performance evaluation, which compares the current state-of-the-art reasoners with our system

Semantic Web Technologies in Support of Service Oriented Architecture Governance

As Service Oriented Architecture (SOA) deployments gradually mature they also grow in size and complexity. The number of service providers, services, and service consumers increases, and so do the dependencies among these entities and the various artefacts that describe how services operate, or how they are meant to operate under specific conditions. Appropriate governance over the various phases and activities associated with the service lifecycle is therefore indispensable in order to prevent a SOA deployment from dissolving into an unmanageable infrastructure. The employment of Semantic Web technologies for describing and reasoning about service properties and governance requirements has the potential to greatly enhance the effectiveness and efficiency of SOA Governance solutions by increasing the levels of automation in a wide-range of tasks relating to service lifecycle management. The goal of the proposed research work is to investigate the application of Semantic Web technologies in the context of service lifecycle management, and propose a concrete theoretical and technological approach for supporting SOA Governance through the realisation of semantically-enhanced registry and repository solutions

Integrative Use of Information Extraction, Semantic Matchmaking and Adaptive Coupling Techniques in Support of Distributed Information Processing and Decision-Making

In order to press maximal cognitive benefit from their social, technological and informational environments, military coalitions need to understand how best to exploit available information assets as well as how best to organize their socially-distributed information processing activities. The International Technology Alliance (ITA) program is beginning to address the challenges associated with enhanced cognition in military coalition environments by integrating a variety of research and development efforts. In particular, research in one component of the ITA ('Project 4: Shared Understanding and Information Exploitation') is seeking to develop capabilities that enable military coalitions to better exploit and distribute networked information assets in the service of collective cognitive outcomes (e.g. improved decision-making). In this paper, we provide an overview of the various research activities in Project 4. We also show how these research activities complement one another in terms of supporting coalition-based collective cognition

Semantic Blockchain to Improve Scalability in the Internet of Things

Generally scarce computational and memory resource availability is a well known problem for the IoT, whose intrinsic volatility makes complex applications unfeasible. Noteworthy efforts in overcoming unpredictability (particularly in case of large dimensions) are the ones integrating Knowledge Representation technologies to build the so-called Semantic Web of Things (SWoT). In spite of allowed advanced discovery features, transactions in the SWoT still suffer from not viable trust management strategies. Given its intrinsic characteristics, blockchain technology appears as interesting from this perspective: a semantic resource/service discovery layer built upon a basic blockchain infrastructure gains a consensus validation. This paper proposes a novel Service-Oriented Architecture (SOA) based on a semantic blockchain for registration, discovery, selection and payment. Such operations are implemented as smart contracts, allowing distributed execution and trust. Reported experiments early assess the sustainability of the proposal

Methods for Efficient and Accurate Discovery of Services

With an increasing number of services developed and offered in an enterprise setting or the Web, users can hardly verify their requirements manually in order to find appropriate services. In this thesis, we develop a method to discover semantically described services. We exploit comprehensive service and request descriptions such that a wide variety of use cases can be supported. In our discovery method, we compute the matchmaking decision by employing an efficient model checking technique

An intelligent framework for dynamic web services composition in the semantic web

As Web services are being increasingly adopted as the distributed computing technology of choice to securely publish application services beyond the firewall, the importance of composing them to create new, value-added service, is increasing. Thus far, the most successful practical approach to Web services composition, largely endorsed by the industry falls under the static composition category where the service selection and flow management are done a priori and manually. The second approach to web-services composition aspires to achieve more dynamic composition by semantically describing the process model of Web services and thus making it comprehensible to reasoning engines or software agents. The practical implementation of the dynamic composition approach is still in its infancy and many complex problems need to be resolved before it can be adopted outside the research communities. The investigation of automatic discovery and composition of Web services in this thesis resulted in the development of the eXtended Semantic Case Based Reasoner (XSCBR), which utilizes semantic web and AI methodology of Case Based Reasoning (CBR). Our framework uses OWL semantic descriptions extensively for implementing both the matchmaking profiles of the Web services and the components of the CBR engine. In this research, we have introduced the concept of runtime behaviour of services and consideration of that in Web services selection. The runtime behaviour of a service is a result of service execution and how the service will behave under different circumstances, which is difficult to presume prior to service 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. Our XSCBR framework allows annotating such runtime experiences in terms of storing execution values of non-functional Web services parameters such as availability and response time into a case library. The XSCBR algorithm for matchmaking and discovery considers such stored Web services execution experiences to determine the adequacy of services for a particular task. We further extended our fundamental discovery and matchmaking algorithm to cater for web services composition. An intensive knowledge-based substitution approach was proposed 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 Constraint Satisfaction Problem (CSP). From the outset, we adopted a pragmatic approach that focused on delivering an automated Web services discovery and composition solution with the minimum possible involvement of all composition participants: the service provider, the requestor and the service composer. The qualitative evaluation of the framework and the composition tools, together with the performance study of the XSCBR framework has verified that we were successful in achieving our goal

A graph-based framework for optimal semantic web service composition

Web services are self-described, loosely coupled software components that are network-accessible through standardized web protocols, whose characteristics are described in XML. One of the key promises of Web services is to provide better interoperability and to enable a faster integration between systems. In order to generate robust service oriented architectures, automatic composition algorithms are required in order to combine the functionality of many single services into composite services that are able to respond to demanding user requests, even when there is no single service capable of performing such task. Service composition consists of a combination of single services into composite services that are executed in sequence or in a different order, imposed by a set of control constructions that can be specified using standard languages such as OWL-s or BPEL4WS. In the last years several papers have dealt with composition of web services. Some approaches treat the service composition as a planning problem, where a sequence of actions lead from a initial state to a goal state. However, most of these proposals have some drawbacks: high complexity, high computational cost and inability to maximize the parallel execution of web services. Other approaches consider the problem as a graph search problem, where search algorithms are applied over a web service dependency graph in order to find a solution for a particular request. These proposals are simpler than their counterparts and also many can exploit the parallel execution of web services. However, most of these approaches rely on very complex dependency graphs that have not been optimized to remove data redundancy, which may negatively affect the overall performance and scalability of these techniques in large service registries. Therefore, it is necessary to identify, characterize and optimize the different tasks involved in the automatic service composition process in order to develop better strategies to efficiently obtain optimal solutions. The main goal of this dissertation is to develop a graph-based framework for automatic service composition that generate optimal input-output based compositions not only in terms of complexity of the solutions, but also in terms of overall quality of service solutions. More specifically, the objectives of this thesis are: (1) Analysis of the characteristics of services and compositions. The aim of this objective is to characterize and identify the main steps that are part for the service composition process. (2) Framework for automatic graph-based composition. This objective will focus on developing a framework that enables the efficient input-output based service composition, exploring the integration with other tasks that are part of the composition process, such as service discovery. (3) Development of optimal algorithms for automatic service composition. This objective focuses on the development of a set of algorithms and optimization techniques for the generation of optimal compositions, optimizing the complexity of the solutions and the overall Quality-of- Service. (4) Validation of the algorithms with standard datasets so they can be compared with other proposals

Fuzzy logic based qos optimization mechanism for service composition

Increase emphasis on Quality of Service and highly changing environments make management of composite services a time consuming and complicated task. Adaptation approaches aim to mitigate the management problem by adjusting composite services to the environment conditions, maintaining functional and quality levels, and reducing human intervention. This paper presents an adaptation approach that implements self-optimization based on fuzzy logic. The proposed optimization model performs service selection based on the analysis of historical and real QoS data, gathered at different stages during the execution of composite services. The use of fuzzy inference systems enables the evaluation of the measured QoS values, helps deciding whether adaptation is needed or not, and how to perform service selection. Experimental results show significant improvements in the global QoS of the use case scenario, providing reductions up to 20.5% in response time, 33.4% in cost and 31.2% in energy consumption

Flexible provisioning of Web service workflows

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