Combinatorial Auction-based Mechanisms for Composite Web Service Selection

Composite service selection presents the opportunity for the rapid development of complex applications using existing web services. It refers to the problem of selecting a set of web services from a large pool of available candidates to logically compose them to achieve value-added composite services. The aim of service selection is to choose the best set of services based on the functional and non-functional (quality related) requirements of a composite service requester. The current service selection approaches mostly assume that web services are offered as single independent entities; there is no possibility for bundling. Moreover, the current research has mainly focused on solving the problem for a single composite service. There is a limited research to date on how the presence of multiple requests for composite services affects the performance of service selection approaches. Addressing these two aspects can significantly enhance the application of composite service selection approaches in the real-world. We develop new approaches for the composite web service selection problem by addressing both the bundling and multiple requests issues. In particular, we propose two mechanisms based on combinatorial auction models, where the provisioning of multiple services are auctioned simultaneously and service providers can bid to offer combinations of web services. We mapped these mechanisms to Integer Linear Programing models and conducted extensive simulations to evaluate them. The results of our experimentation show that bundling can lead to cost reductions compared to when services are offered independently. Moreover, the simultaneous consideration of a set of requests enhances the success rate of the mechanism in allocating services to requests. By considering all composite service requests at the same time, the mechanism achieves more homogenous prices which can be a determining factor for the service requester in choosing the best composite service selection mechanism to deploy

Privacy-preserved security-conscious framework to enhance web service composition

The emergence of loosely coupled and platform-independent Service-Oriented Computing (SOC) has encouraged the development of large computing infrastructures like the Internet, thus enabling organizations to share information and offer valueadded services tailored to a wide range of user needs. Web Service Composition (WSC) has a pivotal role in realizing the vision of implementing just about any complex business processes. Although service composition assures cost-effective means of integrating applications over the Internet, it remains a significant challenge from various perspectives. Security and privacy are among the barriers preventing a more extensive application of WSC. First, users possess limited prior knowledge of security concepts. Second, WSC is hindered by having to identify the security required to protect critical user information. Therefore, the security available to users is usually not in accordance with their requirements. Moreover, the correlation between user input and orchestration architecture model is neglected in WSC with respect to selecting a high performance composition execution process. The proposed framework provides not only the opportunity to securely select services for use in the composition process but also handles service users’ privacy requirements. All possible user input states are modelled with respect to the extracted user privacy preferences and security requirements. The proposed approach supports the mathematical modelling of centralized and decentralized orchestration regarding service provider privacy and security policies. The output is then utilized to compare and screen the candidate composition routes and to select the most secure composition route based on user requests. The D-optimal design is employed to select the best subset of all possible experiments and optimize the security conscious of privacy-preserving service composition. A Choreography Index Table (CIT) is constructed for selecting a suitable orchestration model for each user input and to recommend the selected model to the choreographed level. Results are promising that indicate the proposed framework can enhance the choreographed level of the Web service composition process in making adequate decisions to respond to user requests in terms of higher security and privacy. Moreover, the results reflect a significant value compared to conventional WSC, and WSC optimality was increased by an average of 50% using the proposed CIT

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

Dynamic Web Services Composition

Emerging web services technology has introduced the concept of autonomic interoperability and portability between services. The number of online services has increased dramatically with many duplicating similar functionality and results. Composing online services to solve user needs is a growing area of research. This entails designing systems which can discover participating services and integrate these according to the end user requirements. This thesis proposes a Dynamic Web Services Composition (DWSC) process that is based upon consideration of previously successful attempts in this area, in particular utilizing AI-planning based solutions. It proposes a unique approach for service selection and dynamic web service composition by exploring the possibility of semantic web usability and its limitations. It also proposes a design architecture called Optimal Synthesis Plan Generation framework (OSPG), which supports the composition process through the evaluation of all available solutions (including all participating single and composite services). OSPG is designed to take into account user preferences, which supports optimality and robustness of the output plan. The implementation of OSPG will be con�gured and tested via division of search criteria in di�erent modes thereby locating the best plan for the user. The services composition and discovery-based model is evaluated via considering a range of criteria, such as scope, correctness, scalability and versatility metrics

Semantics-aware planning methodology for automatic web service composition

Service-Oriented Computing (SOC) has been a major research topic in the past years. It is based on the idea of composing distributed applications even in heterogeneous environments by discovering and invoking network-available Web Services to accomplish some complex tasks when no existing service can satisfy the user request. Service-Oriented Architecture (SOA) is a key design principle to facilitate building of these autonomous, platform-independent Web Services. However, in distributed environments, the use of services without considering their underlying semantics, either functional semantics or quality guarantees can negatively affect a composition process by raising intermittent failures or leading to slow performance. More recently, Artificial Intelligence (AI) Planning technologies have been exploited to facilitate the automated composition. But most of the AI planning based algorithms do not scale well when the number of Web Services increases, and there is no guarantee that a solution for a composition problem will be found even if it exists. AI Planning Graph tries to address various limitations in traditional AI planning by providing a unique search space in a directed layered graph. However, the existing AI Planning Graph algorithm only focuses on finding complete solutions without taking account of other services which are not achieving the goals. It will result in the failure of creating such a graph in the case that many services are available, despite most of them being irrelevant to the goals. This dissertation puts forward a concept of building a more intelligent planning mechanism which should be a combination of semantics-aware service selection and a goal-directed planning algorithm. Based on this concept, a new planning system so-called Semantics Enhanced web service Mining (SEwsMining) has been developed. Semantic-aware service selection is achieved by calculating on-demand multi-attributes semantics similarity based on semantic annotations (QWSMO-Lite). The planning algorithm is a substantial revision of the AI GraphPlan algorithm. To reduce the size of planning graph, a bi-directional planning strategy has been developed

Activity-based shop floor management – A concept to enhance flexibility

Volatile markets, an increasing shortage of skilled workers and individual customer requirements as well as the growing desire for a fulfilling work-life balance among employees are influencing the production environment. Flexibility and adaptability are possible key factors to enable companies to meet these challenges. A concept for an activity-based shop floor management has been developed to make work organization more flexible in the area of production. In this concept, first of all activity packages are defined and evaluated, for example with regard to their requirements. Furthermore, it is necessary to define competence levels into which the employees are clustered according to their abilities. Thus, a competence-oriented matching of activity packages and employees is possible. The employee can choose tasks from the pre-grouped activity packages. The result is a generally valid concept for flexible staff deployment planning, which is evaluated in the automotive industry. This concept allows a change from role-based to activity-based task assignment with gamified incentive system, whereby specialists can be deployed more efficiently according to their qualifications

HTN planning: Overview, comparison, and beyond

Hierarchies are one of the most common structures used to understand and conceptualise the world. Within the field of Artificial Intelligence (AI) planning, which deals with the automation of world-relevant problems, Hierarchical Task Network (HTN) planning is the branch that represents and handles hierarchies. In particular, the requirement for rich domain knowledge to characterise the world enables HTN planning to be very useful, and also to perform well. However, the history of almost 40 years obfuscates the current understanding of HTN planning in terms of accomplishments, planning models, similarities and differences among hierarchical planners, and its current and objective image. On top of these issues, the ability of hierarchical planning to truly cope with the requirements of real-world applications has been often questioned. As a remedy, we propose a framework-based approach where we first provide a basis for defining different formal models of hierarchical planning, and define two models that comprise a large portion of HTN planners. Second, we provide a set of concepts that helps in interpreting HTN planners from the aspect of their search space. Then, we analyse and compare the planners based on a variety of properties organised in five segments, namely domain authoring, expressiveness, competence, computation and applicability. Furthermore, we select Web service composition as a real-world and current application, and classify and compare the approaches that employ HTN planning to solve the problem of service composition. Finally, we conclude with our findings and present directions for future work. In summary, we provide a novel and comprehensive viewpoint on a core AI planning technique.<br/