Towards runtime discovery, selection and composition of semantic services

Service-orientation is gaining momentum in distributed software applications, mainly because it facilitates interoperability and allows application designers to abstract from underlying implementation technologies. Service composition has been acknowledged as a promising approach to create composite services that are capable of supporting service user needs, possibly by personalising the service delivery through the use of context information or user preferences. In this paper we discuss the challenges of automatic service composition, and present DynamiCoS, which is a novel framework that aims at supporting service composition on-demand and at runtime for the benefit of service end-users. We define the DynamiCoS framework based on a service composition life-cycle. Framework mechanisms are introduced to tackle each of the phases and requirements of this life-cycle. Semantic services are used in our framework to enable reasoning on the service requests issued by end-users, making it possible to automate service discovery, selection and composition. We validate our framework with a prototype that we have built in order to experiment with the mechanisms we have designed. The prototype was evaluated in a testing environment using some use case scenarios. The results of our evaluation give evidences of the feasibility of our approach to support runtime service composition. We also show the benefits of semantic-based frameworks for service composition, particularly for end-users who will be able to have more control on the service composition process.     

面向语义服务结构中的服务接口问题研究

以往的服务接口模型没有规定业务伙伴任务的内部行为,这使业务处理难以准确地进行任务指派,也难以实现服务的按需组合以及业务处理模式的高度重用。为了克服上述问题并有效构建沟通服务提供者和需求者的桥梁,提出了面向语义服务结构的接口模型,该模型用抽象状态机抽象化描述和Web服务调用实例相关的服务行为,将服务交互的抽象和实现区分开,这既有效解决了服务双方的通讯和协作问题,便于交互模型的重用,而且为Web服务的自动发现、按需组合和智能推理提供了坚实的技术基础。     

面向语义Web服务组合的模糊Petri网推理算法

就语义Web服务自动组合技术而言,在服务组合时需要建立形式化的描述模型,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.而现有的组合方法与实施框架可能出现全局状态的指数性增长.针对这一问题,提出一种适合于Web环境的模糊Petri网逆向推理算法.该算法结合模糊Petri网的逆向推理和代数运算的优点,能有效减小算法空间复杂度,把一个大的、复杂的系统转化为一个只与问题相关的、小的系统来处理.最后,通过一个例子说明了算法的可用性.     

物联网环境下基于情境的语义Web服务选择

当前Web服务海量增加，物联网应用技术快速发展、不断普及，而现有的Web服务选择算法低效、用户匹配度低。针对该问题提出一种物联网环境下基于情境的语义Web服务选择方法。该方法应用QoS参数的无量纲化与语义Web服务动态选择方式，将物联网环境下服务与语义Web服务相结合，并根据用户需求针对QoS选择最优的服务集。实验表明，该方法能有效地提高用户服务动态选择的成功率。     

Applying intelligent agents and semantic web services in eGovernment environments

The increasing volume of eGovernment‐related services is demanding new approaches for service integration and interoperability in this domain. Semantic web (SW) technologies and applications can leverage the potential of eGovernment service integration and discovery, thus tackling the problems of semantic heterogeneity characterizing eGovernment information sources and the different levels of interoperability. eGovernment services will therefore be semantically described in the foreseeable future. In an environment with semantically annotated services, software agents are essential as the entities responsible for exploiting the semantic content in order to automate some tasks, and so enhance the user's experience. In this paper, we present a framework that provides a seamless integration of semantic web services and intelligent agents technologies by making use of ontologies to facilitate their interoperation. The proposed framework can assist in the development of powerful and flexible distributed systems in complex, dynamic, heterogeneous, unpredictable and open environments. Our approach is backed up by a proof‐of‐concept implementation, where the breakthrough of integrating disparate eGovernment services has been tested.     

情景感知的物联网服务推荐方法研究

如何根据用户实时的情景高效地为其推荐最为合适的物联网服务,已经成为当前服务计算与物联网领域亟需解决的关键问题之一。针对这一问题,提出了一种基于情景感知的物联网服务推荐方法。首先基于改进的FolkRank算法生成当前用户可用的物联网服务列表;之后,依据用户当前关键的情景构建用户情景信息模型,根据用户的情景模型从服务列表中筛选出最能满足用户当前情景的物联网服务。实验结果表明,所提出的情景感知的物联网服务推荐方法是可行的与有效的。     

服务网络：Web 服务组合的新基点*

在对W eb服务组合的研究工作回顾和总结的基础上,提出了依据组合过程中服务的复用程度对W eb服务组合进行分类的方法,建立了有关服务模式的概念;与此同时,提出服务网络(services network,SN)的概念来表达服务间的依赖、关系、属性和能力等语义关联。结合本体概念和模糊推理,将语义信息和对模糊信息的处理能力引入到服务的发现、匹配、组合过程中,使SN成为支撑动态、灵活、自主的服务组合的新基点.     

Smart Spaces for Adaptive Information Integration in Bioinformatics

Bioinformatics is reaping the benefits of advances in Semantic Web technology thanks to the growing number of available biomedical web resources and portals. Although positive in general, this abundance poses practical challenges to researchers who must be skilled in techniques for retrieving and integrating sparse and complex contents, and thereof calls for more “intelligent” and user friendly ways of interaction to easily get information. With the aim of making available the intelligent functionality of smart systems, this paper presents SSAIIB (Smart Spaces for Adaptive Information Integration in Bioinformatics), a reference framework for designing bioinformatics smart applications that support discovering, aggregating and delivering contents from web resources according to user’s goals, tasks and concerns. The “Smart Spaces” are software environments whose smartness lies in their ability to adaptively accomplish specific user’s activities such as the exploiting content from biomedical resources, integrating data captured from different sources, supporting data analytics, etc. SSAIIB is structured around two main technologies: service oriented architectures and software agents. In particular, it relies on mechanisms for dynamically assembling suitable services and the use of agents as a natural metaphor for both modelling user’s activities and accessing web resources. A case study is presented that shows the application of SSAIIB to the design and the implementation of a smart space for annotating biomedical texts.     

Developing Ambient Intelligence Systems: A Solution based on Web Services

Enabling the ambient intelligence vision means that consumers will be provided with universal and immediate access to available content and services, together with ways of effectively exploiting them. Concentrating on the software system development aspect, this means that the actual implementation of any ambient intelligence application requested by a user can only be resolved at runtime according to the user's specific situation. This paper introduces a base declarative language and associated core middleware, which supports the abstract specification of Ambient Intelligence applications together with their dynamic composition according to the environment. The proposed solution builds on the Web services architecture, whose pervasiveness enables both services availability in most environments, and specification of applications supporting automated retrieval and composition. In addition, dynamic composition of applications is dealt in a way that enforces the quality of service of deployed applications in terms of security and performance.     

A systematic literature review on web service clustering approaches to enhance service discovery,selection and recommendation

With the advancement of web 2.0 and the development of the Internet of Things (IoT), all tasks can be handled with the help of handheld devices. Web APIs or web services are providing immense power to IoT and are working as a backbone in the successful journey of IoT. Web services can perform any task on a single click event, and these are available over the internet in terms of quantity, quality, and variety. It leads to the requirement of service management in the service repository. The well-managed and structured service repository is still challenging as services are dynamic, and documentation is limited. It is also not a piece of cake to discover, select and recommend services easily from a pool of services. Web service clustering (WSC) plays a vital role in enhancing the service discovery, selection, and recommendation process by analyzing the similarity among services. In this paper, with a systematic process total of 84 research papers are selected, and different state-of-the-art techniques based on web service clustering are investigated and analyzed. Furthermore, this Systematic Literature Review (SLR) also presents the various mandatory and optional steps of WSC, evaluation measures, and datasets. Research challenges and future directions are also identified, which will help the researchers to provide innovative solutions in this area.     

A design and implementation of a framework for games in IoT

Interconnection of the sensing and actuating devices providing the ability to share information across platform through a unified framework for enabling innovative applications. This is achieved by seamless ubiquitous sensing, data analytics and information representation as the unifying framework. Extending the current internet with interconnected objects and devices and their virtual representation has been a growing trend in recent years. Internet of Things (IoT) services are becoming a popular services. This will be supported challenges in a large of aspects such as smart health, green energy, smart home and personalized applications. So, the IoT plays more and more important issue in lifestyle through entertainment such as Games. As of yet, there has not been much research done on IoT environment games as a service. In this paper, we propose schemes of the design and implantation of IT convergence framework for games as a service of IoT. First of all, we discussed what to consider when design and implementation of IT convergence framework for games through contents using user’s mobile devices and various sensors in IoT environment and suggest related techniques. Then, we showed the possibility of games in the IoT environment by creating games and measuring the interactions of users in the IoT environment.     

Ant-based service selection framework for a smart home monitoring environment

Selecting ambient media services in a smart home monitoring environment is challenging. Services in such an environment should be ubiquitous, adaptive, and robust with respect to access and delivery. Many different techniques exist for selecting services in smart environments, for example, dynamic programming, genetic algorithms, and fuzzy logic. However, existing approaches to service selection fail to address the dynamic nature of the services and the requirement of considering the user context and user satisfaction. We address this issue by proposing an ant-inspired service selection framework based on dynamic user preferences and satisfaction. This ant-inspired approach is robust to failures and adaptive to dynamic context. The proposed framework enables different categories of residents (e.g., elderly people, fathers with children, mothers, and so on) to access various media services in such a way that their experiences are optimized with regard to their surrounding environment. Experimental results demonstrate the viability of the proposed framework.     

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.     

本体驱动的语义Web服务动态复合的研究

传统Web服务的复合由于缺乏足够的语义信息而大大降低了服务复合的效率和准确率。语义Web弥补了传统Web语义不足的缺点。但是,面对语义Web上分布的海量知识,如何有效地利用语义信息实现Web服务复合成为一个迫切需要解决的问题。文章针对这一问题,提出一种基于多维用户模型的动态服务复合机制。该机制在Web服务语义标识的启发下通过语义匹配算法能够实现Web服务的顺序复合和并行复合。采用这种服务复合机制将会在一定程度上提高语义Web服务复合的效率和准确率。     

The MASSIF platform: a modular and semantic platform for the development of flexible IoT services

In the Internet of Things (IoT), data-producing entities sense their environment and transmit these observations to a data processing platform for further analysis. Applications can have a notion of context awareness by combining this sensed data, or by processing the combined data. The processes of combining data can consist both of merging the dynamic sensed data, as well as fusing the sensed data with background and historical data. Semantics can aid in this task, as they have proven their use in data integration, knowledge exchange and reasoning. Semantic services performing reasoning on the integrated sensed data, combined with background knowledge, such as profile data, allow extracting useful information and support intelligent decision making. However, advanced reasoning on the combination of this sensed data and background knowledge is still hard to achieve. Furthermore, the collaboration between semantic services allows to reach complex decisions. The dynamic composition of such collaborative workflows that can adapt to the current context, has not received much attention yet. In this paper, we present MASSIF, a data-driven platform for the semantic annotation of and reasoning on IoT data. It allows the integration of multiple modular reasoning services that can collaborate in a flexible manner to facilitate complex decision-making processes. Data-driven workflows are enabled by letting services specify the data they would like to consume. After thorough processing, these services can decide to share their decisions with other consumers. By defining the data these services would like to consume, they can operate on a subset of data, improving reasoning efficiency. Furthermore, each of these services can integrate the consumed data with background knowledge in its own context model, for rapid intelligent decision making. To show the strengths of the platform, two use cases are detailed and thoroughly evaluated.     

COCOA: COnversation-based service COmposition in pervAsive computing environments with QoS support

Pervasive computing environments are populated with networked services, i.e., autonomous software entities, providing a number of functionalities. One of the most challenging objectives to be achieved within these environments is to assist users in realizing tasks that integrate on the fly functionalities of the networked services opportunely according to the current pervasive environment. Towards this purpose, we present COCOA, a solution for COnversation-based service COmposition in pervAsive computing environments with QoS support. COCOA provides COCOA-L, an OWL-S based language for the semantic, QoS-aware specification of services and tasks, which further allows the specification of services and tasks conversations. Moreover, COCOA provides two mechanisms: COCOA-SD for the QoS-aware semantic service discovery and COCOA-CI for the QoS-aware integration of service conversations towards the realization of the user task’s conversation. The distinctive feature of COCOA is the ability of integrating on the fly the conversations of networked services to realize the conversation of the user task, by further meeting the QoS requirements of user tasks. Thereby, COCOA allows the dynamic realization of user tasks according to the specifics of the pervasive computing environment in terms of available services and by enforcing valid service consumption.     

Web服务动态组合方法研究与设计

目前基于工作流的Web服务组合方法大多要求预先定义流程结构,不能适应现代企业业务流程复杂多变的需求.提出了一种Web服务动态组合方法,将流程中动态部分用黑盒子流程进行封装,在执行时根据预定义规则和用户需求将黑盒子流程自动组合展开为实际运行流程.对具体服务、抽象服务、黑盒子流程等概念和服务选取规则、服务组合规则进行了定义,详细描述黑盒子流程展开算法,并设计了一个实现动态服务流程组合的框架结构.     

Semantic model-driven architecting of service-based software systems

Model-driven development is a software development framework that emphasises model-based abstraction and automated code generation. Service-based software architectures benefit in particular from semantic, ontology-based modelling. We present ontology-based transformation and reasoning techniques for layered semantic service architecture modelling. Integrated ontological layers support abstract domain modelling, architectural design, and interoperability aspects. Ontologies are beneficial due to their potential to formally define models, to allow reasoning about semantic models, and to automate transformations at all layers. Ontologies are suitable in particular for the Web Services platform due to their ubiquity within the Semantic Web and their application to support semantic Web services.     

An exploration of IoT platform development

IoT (Internet of Things) platforms are key enablers for smart city initiatives, targeting the improvement of citizens’ quality of life and economic growth. As IoT platforms are dynamic, proactive, and heterogeneous socio-technical artefacts, systematic approaches are required for their development. Limited surveys have exclusively explored how IoT platforms are developed and maintained from the perspective of information system development process lifecycle. In this paper, we present a detailed analysis of 63 approaches. This is accomplished by proposing an evaluation framework as a cornerstone to highlight the characteristics, strengths, and weaknesses of these approaches. The survey results not only provide insights of empirical findings, recommendations, and mechanisms for the development of quality aware IoT platforms, but also identify important issues and gaps that need to be addressed.