OntoPipeliner: An ontology-based automatic semantic service pipeline generator

The Web is a distributed environment rich with Web services going through continual metamorphosis; thus, sustaining semantic stability of service composition has become a major challenge. Automatic service composition – enabled both by the use of ontologies that describe service domains and by user-specified constraints bound to the ontologies – provides us candidate service pipelines at composition design time. The ontology-based languages for semantically describing web services, such as OWL-S, have been widely used. Though rich and comprehensive in their expressiveness, the use of these languages still leaves much of composition process manual. In this work, we present an ontology-based semantic web service composition system called OntoPipeliner. It employs a novel way of utilizing characteristics of Web services that reflect the classes and properties of domain ontologies and provides the ontology-guided constraints for automatic composition of services, in order to guide the user toward the best pipeline that meets the user requirements.     

动态Web Services的约束满足优化技术研究

Web Services合成是Web Services技术的重要方面，能够按要求提供选择新的服务。本文首先提出了Web Services服务约束的分类描述，进而分析了Web Services服务合成中如何按照服务约束指导服务选择，进而选择合适的服务集来满足客户的要求。该方法把动态Web Services合成转化为约束满足问题。     

QoS-aware middleware for Web services composition

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online business-to-business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different quality of service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming.     

基于领域本体和QoS的服务选取方法*

针对如何在众多Web服务中找到满足功能需求的服务,又如何在多个相似服务和多个组合方案中寻求最优目标,提出一种基于领域本体概念和决策理论的服务选取方法。该方法首先借助领域本体概念,根据输入输出参数的语义找到满足功能需求的服务,在多个相似服务和多组合方案选择上,通过对各QoS属性综合决策评估出最优解。最后通过实验验证了该方法的有效性和可行性。     

Automated and flexible composition based on abstract services for a better adaptation to user intentions

In recent years, the composition of loosely coupled services with the aim of satisfying the user intention is a widely followed research topic. The composition of services implies the ability to select, coordinate, interact, and interoperate existing services. This is considered as a complex task. This complexity is mainly due to the large number of available services and their heterogeneity as they are created by different organizations. This complexity is increased when services must be dynamically and automatically composed to meet requirements which are not satisfied by existing services. In fact, an approach for service composition must offer the potential to achieve flexible and adaptable applications, by selecting and combining services based of the request and the context of the user. In this perspective, different approaches have been developed for services composition. However, most of the existing composition approaches tend to be static and not flexible in the sense that they do not have the ability to adapt to user requirements.To overcome these challenges, we propose a composition approach in which the generation of the composition schema is performed at runtime through the use of abstract services provided at design time. The composition process that we propose takes as input a structure of user requirements materialized by a graph of intentions and enriches this graph to explicit the implicit relationships. The enriched graph is used to generate an initial composition schema by building the control flow and selecting the appropriate abstract services. The selection of these services is based on the semantic matching and the degree of semantic affinity between abstract services. Then, the final composition schema is generated using a refinement mechanism of abstract services using semantic matching techniques and taking into account user context and constraints.     

A decision-making method for personalized composite service

Web services are emerging technologies that enable application to application communication and reuse of autonomous services. Web services composition is a concept of integrating component services to conduct complex business transactions based on functionality and performance constraints. With the rapid growth of Web services on the Internet, the services owing the same functionality and different performance become more and more, and different users care for different quality. Therefore, designing effective decision-making method for the personalized composite service has become a fundamental problem for the application based on Web service. In this paper, oriented to the user need with single optimization objective, an efficient algorithm, which consists of Particle Swarm Optimization (PSO) and Niche technology, is presented to solve the Web service selection problem. Furthermore, in view of the practical composition requirements including multiple optimization objectives, an algorithm used to resolve the service selection with multi-objective multi-constraint is designed based on NPSO and the intelligent optimization theory of multi-objective PSO, which can produce a set of Pareto optimal composite services by means of optimizing various objective functions simultaneously. Experimental results show that NPSO algorithm owns better global convergence ability with faster convergence speed. Meanwhile, multi-objective multi-constraint NPSO is both feasible and efficient.     

基于Dijkstra算法的Web服务合成选择策略研究

Web服务合成中操作的选择是一个关键问题,这直接影响到用户对合成的复合服务的满意度、解决该问题的关键是对候选Web服务的输入输出数据关系进行建模,以及有效利用这些已有的数据依赖关系实现服务合成的请求。通过从Web服务规范语言中提取Web服务的语义信息．掏建Web服务的有向图,并分析Diikstra算法用于Web服务合成的问题。提出了相应的船决办法,给出了一个基于Diikstra算法的Web服务合成选择策略的算法。该算法能在合成中选择最恰当的操作组合．产生最终的复合服务。     

基于全局QoS 约束分解的Web 服务动态选择

随着执行时绑定的Web服务的提出及其被大量地应用到开放式服务中,用户对支持快速和动态的Web服务组合提出了新的要求.即在组合过程中,用尽可能短的时间花费选择满足用户端到端的QoS要求的服务.针对上述要求,提出了一种基于全局QoS约束分解的动态服务选择方法(Web service dynamic selection approach,简称WSDSA).该方法的主要思想是,通过基于模糊逻辑的自适应调整方法(adaptive adjustment method,简称AAM)和自适应粒子群优化算法(adaptive particle swarm optimization,简称APSO)将全局QoS约束自适应地分解为满足用户偏好的局部约束,然后利用局部最优获得最合适的组合服务.性能评价表明,WSDSA方法具有较好的有效性,仅用较低的时间花费就能达到或接近全局最优解,能够满足服务选择的实时性和动态性.     

Adaptive Service Composition in Flexible Processes

In advanced service oriented systems, complex applications, described as abstract business processes, can be executed by invoking a number of available Web services. End users can specify different preferences and constraints and service selection can be performed dynamically identifying the best set of services available at runtime. In this paper, we introduce a new modeling approach to the Web service selection problem that is particularly effective for large processes and when QoS constraints are severe. In the model, the Web service selection problem is formalized as a mixed integer linear programming problem, loops peeling is adopted in the optimization, and constraints posed by stateful Web services are considered. Moreover, negotiation techniques are exploited to identify a feasible solution of the problem, if one does not exist. Experimental results compare our method with other solutions proposed in the literature and demonstrate the effectiveness of our approach toward the identification of an optimal solution to the QoS constrained Web service selection problem     

Constrained evolutionary computing approach to Web service compositions

Web services are being adopted as a viable means of accessing Web-based applications. Web services are not only used to exchange information between enterprises but also to help software developers provide value-added services for various demands. Web service compositions are synthesised by researchers from elementary Web services, offering the opportunity for service providers and application developers to create value-added services. However, a problem exists in the current distribution process of Web service compositions: the general analysis and selection of services can be overly complex and are completed manually. Therefore, there is a need to manage composite Web services automatically. But the research related to ranking candidate services and selection of optimisation strategies is sparse. Yet, few have been published that consider the constraints of non-functional properties. In this article, a systemic but autonomous composition process has been proposed. This study proposes an evolutionary approach that applies the characteristics of the object-oriented concept of Web services and the genetic algorithm to effectively manage and optimise the Web service composition. It is capable of escaping not only from local optima due to a population-based approach, but also from unbiased nature, which enables it to perform well in a situation with little domain knowledge. In this article, the related literature is reviewed. Then, the Web service composition model incorporated with a genetic algorithm is proposed. Finally, a practical implementation is illustrated and shows a good result in terms of solution quality.     

基于Petri网的语义Web服务自动组合方法

Web服务组合使得开发人员可以快速地创建自己的应用程序.但是,随着Internet上可用的Web服务数目的增加,Web服务组合是一项高度复杂的任务.针对语义Web服务的自动组合问题,提出了一种既考虑服务输入/输出又考虑服务行为约束的自动组合方法.首先,注册服务被转化为一组Horn子句形规则,用户的输入和输出请求分别被转化为Horn子句中的事实和目标,从而将寻找满足用户输入/输出请求的合成服务问题转化为Horn子句的逻辑推理问题;然后,用Petri网来为该Horn子句集建模,T-不变量技术被用来判定是否存在满足用户输入/输出请求的合成服务;最后给出了两种算法来获取既满足用户输入/输出请求又满足用户行为约束的合成服务的Petri网模型.     

QoS全局最优的多目标Web服务选择算法*

针对现有方法的不足,提出一种基于QoS全局最优的多目标动态Web服务选择算法。在给出动态服务组合模型的基础上,以“抽象服务规划”为输入,以用户的非功能性需求为全局约束,将动态服务选择问题转换为一个带QoS约束的多目标服务组合优化问题;利用多目标蚁群算法,多个目标函数被同时优化并产生一组满足约束条件的Pareto优化解。通过运用实验与基于多目标遗传算法的Web服务选择算法进行对比,证明了该方法的可行性和有效性。     

Preference-driven personalization for flexible digital item adaptation

The delivery of multimedia content often needs the adaptation of the content in order to satisfy user constraints. With the Digital Item Adaptation part, the MPEG-21 standard already defines a useful frame-work to handle this task. However, in modern service-oriented architectures the functionality of adaptation is split over several services. Hence, the central instantiation of a suitable service chain needs to tackle a complex multi-objective optimization problem. In this problem between content choice and possible adaptations the current preference model in the MPEG-7/21 standard still lacks expressiveness. In the course of this paper we demonstrate this shortcoming and how the integration of more powerful models can ease the instantiation problem. Furthermore we explain how to efficiently evaluate preference trade-offs by evaluating skyline queries as currently investigated in the field of information systems. As a running example we use preference-based content adaptation in a typical media streaming application with Web services as basic modules. The contribution of our framework is to enable a central coordinator to instantiate an executable service composition chain by integrating all needed Web services to adapt the multimedia content in the best possible fashion in the sense of Pareto optimality. This work was supported in part by the German Research Foundation (DFG) within the Emmy-Noether Program of Exellence.     

GOS: a global optimal selection strategies for QoS-aware web services composition

Services composition technology provides a promising way to create new services in services-oriented architecture. However, some challenges are hindering the application of services composition. One of the major challenges encountered by composite services developer is how to effectively select a set of services across different autonomous regions (e.g., organization or business) to instantiate a composite service which can satisfy user’s QoS constraints. To solve QoS-aware Web service composition problem, this paper proposes a global optimization selection (GOS) approach based on prediction mechanism for QoS values of local services. The GOS includes two parts. First, the local preprocessing service selection algorithm can be used to increase composite services performance in run-time by predicting the change of service quality parameters. Second, GOS aims at enhancing the run-time performance of global selection by reducing QoS aggregation operations. The simulation results show that the GOS has excellent selection and lower execution cost than existing approaches.     

基于主体的语义Web服务自动组合研究

语义Web服务要解决的一个主要问题就是如何实现服务组合自动化.主体技术因其智能性、自主性等特点在解决语义Web服务组合问题中具有较大优势.通过分析语义Web服务组合研究现状,分析主体、语义Web与Web服务的紧密关系,论证了基于主体的语义Web服务的可行性并描述了基于多主体的Web服务组合平台架构.介绍了基于主体技术的语义Web服务组合技术,将服务组合看成是一个多主体环境下的规划问题,给出语义Web服务作为主体动作子类的形式化定义,并针对服务组合问题增加限定条件,定义服务之间的5种关系,试图从逻辑角度,以描述逻辑为基本工具,突出服务的动态性与交互性.最后利用主体的目标规划以及基于描述逻辑的有效推理,给出了服务的自动组合算法.     

面向用户主导问题求解环境的服务组合方法

为提高服务组合的即时性,适应用户业务需求的变化以及服务资源的动态和异构性,提出一种适应用户主导问题求解环境的服务组合方法。探讨了维护服务交互关系的相对稳定性的策略,提出了基于服务相容性的服务聚类规则,基于聚类服务关联图的组合模板构建方法及其最优性的保障手段和组合模板的具体化方法。实验结果表明,该方法可提高服务组合的即时性和适应性,提高服务组合的时间效率。     

SOA关键型系统QoS可感知的服务动态实时组合策略

针对运行于开放、不确定环境下SOA架构的多使命复杂关键型系统,提出了一个QoS可感知的服务动态组合体系结构及启发式服务实时组合算法,用于满足具有严格QoS限制的复杂用户需求。利用所提出的体系结构可以在线执行服务组合,大大提高了SOA关键型系统的灵活性。通过启发式算法解决了以往服务组合算法时间复杂度的NP难题,最后通过一组实验证明该启发式算法的实时性和具体优化结果。     

A User Requirement Oriented Web Service Discovery Approach Based on Logic and Threshold Petri Net

In recent years, the number of Web services has increased significantly. Web service discovery has drawn much attention with the development of Web service applications and big data analysis. Under this circumstance, traditional Web service discovery strategies cannot adequately meet high user requirements due to the efficiency and precision of service discovery is low. In order to improve the accuracy and efficiency of service discovery, a user requirement oriented Web service discovery approach based on Petri nets is proposed in this study. A data preprocessing strategy of Web service is first designed. Then, a service clustering method is proposed based on Petri nets, which can conduct service cluster head generation, service cluster composition, and service discovery. The proposed method utilizes a superior data preprocessing method. Using simulation experiments, the efficiency and precision of Web service discovery are illustrated. Finally, the application value of the approach on real Web service is discussed.      

增强多目标遗传算法下的组合服务的容错能力

利用多目标遗传算法得到一组满足约束条件的最优非劣方案集,用户根据实际需要从中选择满意的组合方案,同时,未被选择的流程作为备选方案以便发生意外时替代执行。提出了最优非劣方案的失效成功率和基本服务的相容性计算方法,选择可用性高且失效成功率较高的组合方案,以便执行发生意外时组合服务有较高的概率成功切换到备选方案继续执行,增强了组合服务执行的容错能力。实验结果说明了该方法的可行性和有效性。