A monitoring approach for runtime service discovery

Effective runtime service discovery requires identification of services based on different service characteristics such as structural, behavioural, quality, and contextual characteristics. However, current service registries guarantee services described in terms of structural and sometimes quality characteristics and, therefore, it is not always possible to assume that services in them will have all the characteristics required for effective service discovery. In this paper, we describe a monitor-based runtime service discovery framework called MoRSeD. The framework supports service discovery in both push and pull modes of query execution. The push mode of query execution is performed in parallel to the execution of a service-based system, in a proactive way. Both types of queries are specified in a query language called SerDiQueL that allows the representation of structural, behavioral, quality, and contextual conditions of services to be identified. The framework uses a monitor component to verify if behavioral and contextual conditions in the queries can be satisfied by services, based on translations of these conditions into properties represented in event calculus, and verification of the satisfiability of these properties against services. The monitor is also used to support identification that services participating in a service-based system are unavailable, and identification of changes in the behavioral and contextual characteristics of the services. A prototype implementation of the framework has been developed. The framework has been evaluated in terms of comparison of its performance when using and when not using the monitor component.     

快速语义Web服务发现方法

针对现有的基于本体描述的语义Web服务发现方法发现效率较为低下的问题,提出一种新的服务发现方法.该方法在基于本体距离计算语义Web服务综合相似度的基础上,利用数据挖掘中的聚类算法AGNES对语义Web服务集合进行聚类预处理,形成若干服务簇,然后应用相应服务发现算法根据相似度阈值定位于某一服务簇内进行查找匹配,从而可减少搜索空间.理论与仿真实验结果表明,该方法既可保证服务发现的准确率,又可明显提高服务发现的效率.     

A semantic service discovery approach for ubiquitous computing

Services in the ubiquitous computing are heterogeneous in nature. To be pervasive, these services should be defined in terms of their functionality and capabilities rather than the meaningless Universally Unique IDentifiers (UUIDs) or types of services. With that, clients can access the proper service based on semantic requests, rather then a pre-configured profile. In this paper, we study the requirements for semantic query to be feasible in service discovery processes. Current discovery protocols and the concept of semantics are brought together to construct a framework to realize the semantic service discovery for ubiquitous computing. Many issues are discussed in relation to service discovery topologies, ontology languages, and semantic query languages.     

Hybrid approach for context-aware service discovery in healthcare domain

Context-awareness computing is a research field which often refers to healthcare as an interesting and rich area of application. Context aware computing attains environments monitoring by means of sensors to provide relevant information or services according to the identified context. In particular, wireless ad hoc sensor networks for medical purposes are playing an increasing role within healthcare. Body Sensor Networks (BSN) are being designed for prophylactic and follow-up monitoring of patients in e.g. their homes, during hospitalization, and in emergencies. This work presents an integrated environment aimed at providing personalized healthcare services which appropriately meet the user?s context. Deploying the semantics embedded in web services and context models is a mandatory step in the automation of service discovery, invocation and composition. Nevertheless, in a context aware domain purely logic-based reasoning on respectively context and services may not be enough. The main idea of this work is related to enrich with qualitative representation of context underling data by means of Fuzzy Logic in order to automatically recognize the context and to consequently find the right set of healthcare services among the available ones. Semantic formalisms (e.g., OWL, OWL-S, etc.) enable the context and services modeling in terms of domain ontology concepts. On the other hand, soft computing techniques support activity of unsupervised context analysis and healthcare semantic service discovery. Goal is to define context-aware system whose quality of retrieved services relies on the acquisition of user context by means of a robust theoretical approach. Moreover, this work defines hybrid architecture which attains a synergy between the agent-based paradigm and the fuzzy modeling. Specifically, the system exploits some task oriented agents in order to achieve context recognition, services matchmaking and brokerage activities.     

基于变更管理的网络管理接口服务动态发现模型*

介绍了网络管理接口服务的特点;分析了现有服务发现机制应用到网络管理领域中的不足;提出了一种基于变更管理的网络管理接口服务发现模型,介绍了模型的特点并且详细介绍了模型中的核心实体NMISFC的功能。通过在移动网管接口中的应用,验证了此模型的有效性。     

A trustworthy QoS-based collaborative filtering approach for web service discovery

Many network services which process a large quantity of data and knowledge are available in the distributed network environment, and provide applications to users based on Service-Oriented Architecture (SOA) and Web services technology. Therefore, a useful web service discovery approach for data and knowledge discovery process in the complex network environment is a very significant issue. Using the traditional keyword-based search method, users find it difficult to choose the best web services from those with similar functionalities. In addition, in an untrustworthy real world environment, the QoS-based service discovery approach cannot verify the correctness of the web services’ Quality of Service (QoS) values, since such values guaranteed by a service provider are different from the real ones. This work proposes a trustworthy two-phase web service discovery mechanism based on QoS and collaborative filtering, which discovers and recommends the needed web services effectively for users in the distributed environment, and also solves the problem of services with incorrect QoS information. In the experiment, the theoretical analysis and simulation experiment results show that the proposed method can accurately recommend the needed services to users, and improve the recommendation quality.     

基于本体的Web服务发现方法研究

针对传统Web服务发现准确率低下的问题,提出一种基于本体的服务发现方法.该方法首先基于领域本体构建了Web服务描述模型,并应用OWL-S描述Web服务增强了Web服务的语义信息,然后从基本信息语义相似度、功能语义相似度等方面综合计算Web服务相似度,最后基于Web服务相似度进行请求服务与目标服务的匹配.给出了基于本体的服务发现相关算法,并设计了基于三层架构的服务发现原型系统.实验结果表明,该方法可提高Web服务发现的查全率及查准率.     

An effective dynamic service composition reconfiguration approach when service exceptions occur in real-life cloud manufacturing

Cloud Manufacturing Service Composition (CMSC), as one of the key issues of Cloud Manufacturing (CMfg), has already attracted much attention. Existing researches on CMSC mainly focus on the optimization efficiency in ideal conditions, while scarcely focus on how to efficiently reconfigure CMSC when service exceptions occur. Uncertain service exceptions often occur during CMSC's execution in real-life CMfg. Thus, it is an urgent issue to perform an adjustment for CMSC to continue to complete the processing task. Besides, some practical constraints are non-negligible in real-world CMfg. Thus, it is necessary to consider them when reconfiguring CMSC. To bridge these gaps, this paper proposes a dynamic service composition reconfiguration model when service exceptions occur under practical constraints (DSCRWECPC). This model redefines optimization objectives, including machining quality, service quality, and cost. Besides, DSCRWECPC considers service exceptions, the cloud manufacturing service occupancy time constraint, the strict time constraint of original CMSC, and dynamic service quality change as its practical constraints. To solve this model, this paper proposes a service composition reconfiguration algorithm (SCRIHHO) based on the strengthened Harris Hawks Optimizer (HHO). Finally, to certify SCRIHHO's performance, this paper conducts numerical experiments and the case application to perform comparisons between SCRIHHO and other algorithms (Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO)). Results showed SCRIHHO in this paper is superior to PSO, GWO when tackling the practical DSCRWECPC in CMfg.     

基于向量空间的Web服务发现模糊方法

Web服务已逐渐发展成为重要的分布式计算范式。在综合分析了现有的Web服务描述文档的基础上,提出了一种基于模糊集的服务特征项集选取算法以及Web服务向量空间的生成方法。利用生成的向量空间,对Web服务进行模糊聚类。基于此,文中给出了向量空间中进行Web服务发现的模糊方法。所提出的方法只需利用现有的Web服务描述信息,保证了服务发现的有效性。     

An automatic key discovery approach for data linking

In the context of Linked Data, different kinds of semantic links can be established between data. However when data sources are huge, detecting such links manually is not feasible. One of the most important types of links, the identity link, expresses that different identifiers refer to the same real world entity. Some automatic data linking approaches use keys to infer identity links, nevertheless this kind of knowledge is rarely available. In this work we propose KD2R, an approach which allows the automatic discovery of composite keys in RDF data sources that may conform to different schemas. We only consider data sources for which the Unique Name Assumption is fulfilled. The obtained keys are correct with respect to the RDF data sources in which they are discovered. The proposed algorithm is scalable since it allows the key discovery without having to scan all the data. KD2R has been tested on real datasets of the international contest OAEI 2010 and on datasets available on the web of data, and has obtained promising results.     

基于语义Web的仿真服务动态发现机制

仿真服务的动态发现是进行基于Web的可组合可扩展仿真研究的首要步骤。首先,基于OWL-S本体规范建立了仿真服务描述模型,对仿真服务与仿真需求进行了形式化表示;然后,研究了网格和Web服务技术支撑下的仿真服务动态发现系统结构,以及基于语义Web和领域本体的动态发现机制;进而,提出了基于本体的服务匹配算法,包括领域定位算法和服务定位算法两部分,领域定位算法大大降低了进行服务定位时候选服务集合的大小,有效地保证了服务匹配精度和效率;最后,通过模拟的实验数据对基于本体的匹配算法的性能进行了分析。     

基于功能语义标注的Web服务发现方法*

针对Web服务发现中存在的语义异构、逻辑推理复杂、应用实施代价较大以及查准率有待进一步提高等问题,提出了一种基于功能语义标注的Web服务发现方法。定义了领域功能语义模型和本体映射机制,对服务进行功能语义标注以增加语义信息;服务发现时,先对其功能进行语义相似度匹配,满足给定阈值的服务再进行接口匹配。仿真实验表明,提出的方法在保证服务匹配效率的同时,有效避免了语义异构问题,相比传统方法查准率提高了34.1%。     

基于策略的可控服务发现与动态路由模型

如何改进现有服务发现模型使之适应动态可变的服务运行环境并选择最符合用户需求的Web服务正在引起研究领域关注.提出了一种基于策略的可控服务发现与动态路由模型(P-WSDRM).该模型支持抽象服务、服务实例和服务发现者的属性定义,支持携带属性描述信息的服务发布与发现,引入了策略判定机制,支持服务发现者基于已定义的策略进行服务发现和实例路由.目前已经于Linux平台和目录服务实现了该模型的一个原型系统.     

Local martingale difference approach for service selection with dynamic QoS

Users in Service-oriented architecture (SOA) seek the best Quality of service (QoS) by service selection from the candidates responding in succession. In case the QoS changes dynamically, choosing one service and stop the searching is problematic for a service user who makes the choice online. Lack of accurate knowledge of service distribution, the user is unable to make a good decision. The Local Martingale Difference (LMD) approach is developed in this paper to help users to achieve optimal results, in the sense of probability. The stopping time is proved to be bounded to ensure the existence of an optimal solution first. Then, a global estimation over the time horizon is transformed to a local determination based on current martingale difference to make the algorithm feasible. Independent of any predetermined threshold or manual intervention, LMD enables users to stop around the optimal time, based on the information collected during the stochastic process. Verified to be efficient by comparison with three traditional methods, LMD is adaptable in vast applications with dynamic QoS.     

An abstract model of service discovery and binding

We propose a formal operational semantics for service discovery and binding. This semantics is based on a graph-based representation of the configuration of global computers typed by business activities. Business activities execute distributed workflows that can trigger, at run time, the discovery, ranking and selection of services to which they bind, thus reconfiguring the workflows that they execute. Discovery, ranking and selection are based on compliance with required business and interaction protocols and optimisation of quality-of-service constraints. Binding and reconfiguration are captured as algebraic operations on configuration graphs. We also discuss the methodological implications that this model framework has on software engineering using a typical travel-booking scenario. To the best of our knowledge, our approach is the first to provide a clear separation between service computation and discovery/instantiation/binding, and to offer a formal framework that is independent of the SOA middleware components that act as service registries or brokers, and the protocols through which bindings and invocations are performed.     

保证服务可用性的服务发现模型研究

针对UDDI提供的Web服务资源可用性差的问题,分析了不同SOA角色对Web服务可用性需求,构建了一种可保证服务可用性的服务发现模型。该模型利用轮询算法定期轮流对Web服务进行可用性度量,以判断UDDI的可用率,当可用率降低到预警值时能够立即更改轮询周期,提高对服务可用性的监控。通过对UDDI服务可用性的评估不仅保证了UDDI的可用性,同时也保障了用户发现服务的可用性。     

A simulation-based approach for dynamic process management at web service platforms

Web services technology is being adopted as a viable deployment approach for future distributed software systems that enable business-to-business and business-to-consumer interactions across the open and dynamic internet environment. Recent research is focused on developing support technologies for web service discovery, on-demand service composition, and robust execution to facilitate web services based deployment of business processes. Developing techniques to cope with the volatile and open nature of the web during execution of composite services at the service platform is essential for delivering reliable and acceptable performance in this new process delivery framework. In this paper, we propose a simulation-based framework to guide scheduling of composite service execution. Online simulation of the dynamics of the open environment is used for scheduling service requests at the service platform. Comparison of the look-ahead simulation for different scheduling policies with the current execution state provides guidelines for service execution in order to cope with system volatility. We have implemented a prototype of the proposed framework and illustrate the feasibility of our approach with experimental studies.     

基于分布式环境一种动态依赖关系发现的方法

本文提出了一种为分布式应用动态构造依赖性模型的方法。这个方法通过对系统进行主动干扰来获得建模的先验知识,然后基于贝叶斯网络构造方法,对分布式应用的组件间关系建立依赖性模型。和传统的被动建模技术不同的是,这种主动方法不需要事先对系统细节充分了解,它通过在运行环境中部署探针,捕捉和测量与部署的主动干扰相关的系统反馈,通过机器学习的方法识别分布式应用中构件间的动态调用的依赖关系,为分布式应用建立动态运行过程中的依赖性模型。动态建立的依赖性模型可用于分布式应用的运行时管理,用于分布式应用执行过程中的故障定位和恢复,对于分布式应用自主计算环境的实现,提供一种实用的方法。