EASY: Efficient semAntic Service discoverY in pervasive computing environments with QoS and context support

Pervasive computing environments are populated with networked software and hardware resources providing various functionalities that are abstracted, thanks to the Service Oriented Architecture paradigm, as services. Within these environments, service discovery enabled by service discovery protocols (SDPs) is a critical functionality for establishing ad hoc associations between service providers and service requesters. Furthermore, the dynamics, the openness and the user-centric vision aimed at by the pervasive computing paradigm call for solutions that enable rich, semantic, context- and QoS-aware service discovery. Although the semantic Web paradigm envisions to achieve such support, current solutions are hardly deployable in the pervasive environment due to the costly underlying semantic reasoning with ontologies. In this article, we present EASY to support efficient, semantic, context- and QoS-aware service discovery on top of existing SDPs. EASY provides EASY-L, a language for semantic specification of functional and non-functional service properties, as well as EASY-M, a corresponding set of conformance relations. Furthermore, EASY provides solutions to efficiently assess conformance between service capabilities. These solutions are based on an efficient encoding technique, as well as on an efficient organization of service repositories (caches), which enables both fast service advertising and discovery. Experimental results show that the deployment of EASY on top of an existing SDP, namely Ariadne, enhancing it only with slight changes to EASY-Ariadne, enables rich semantic, context- and QoS-aware service discovery, which furthermore performs better than the classical, rigid, syntactic matching, and improves the scalability of Ariadne.     

A specification model for context-based collaborative applications

This paper presents a model for building context-based systems in pervasive computing environments from high level specifications. A pervasive computing environment is viewed as a collaboration space consisting of mobile users, system services, and sensors and resources embedded in the physical environment. The approach presented here is developed for building collaborative activities in which users and environment services cooperate towards some shared objectives and tasks. The specification model allows expression of policies related to context-based discovery and secure access of resources, and role-based interactions among users and environmental services. Using several examples we illustrate the capabilities of our specification model for expressing various kinds of context-based requirements for resource access and user interactions.     

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。     

一种普适计算环境下基于语义的服务匹配算法

在普适计算环境中通过语义本体来表示环境中的概念进行服务发现可以提高服务发现的鲁棒性。给出了一种基于语义的服务匹配算法,根据不同的服务请求可以通过服务类型匹配、服务输入输出参数匹配和QoS参数匹配,实现了分层次、逐步过滤不匹配的服务。同时通过服务相似度的计算为服务请求者提供最满足需求的服务。实验结果证明该算法具有较高的匹配率和较好的匹配速度,完全适用于普适计算环境。     

A correlation-driven optimal service selection approach for virtual enterprise establishment

A virtual enterprise is an emerging business cooperation model which allows rapid response to the unpredictable market behavior and opportunity. For service oriented enterprises, where computing resources are encapsulated as services and published online, establishing a virtual enterprise can be regarded as a process of service composition. As there are increasing numbers of available services providing similar functionalities but with different quality values, and with potential business correlations among them, it is not trivial to orchestrate a composite service with optimal overall quality of service (QoS). In this paper, we formally propose a business correlation model including both quality correlations and selection correlations, and then present an efficient approach for correlation-driven QoS-aware optimal service selection based on a genetic algorithm. The genetic algorithm is tailored with niching technology, a repair operator and a penalty mechanism. The effectiveness and efficiency of the approach are demonstrated via empirical studies at last.     

Dynamic Service Composition in Pervasive Computing

Service-oriented architectures (SOAs) promise to provide transparency to resource access by exposing the resources available as services. SOAs have been employed within pervasive computing systems to provide essential support to user tasks by creating services representing the available resources. The mechanism of combining two or more basic services into a possibly complex service is known as service composition. Existing solutions to service composition employ a template-matching approach, where the user needs are expressed as a request template, and through composition, a system would identify services to populate the entities within the request template. However, with the dynamism involved in pervasive environments, the user needs have to be met by exploiting available resources, even when an exact match does not exist. In this paper, we present a novel service composition mechanism for pervasive computing. We employ the service-oriented middleware platform called pervasive information communities organization (PICO) to model and represent resources as services. The proposed service composition mechanism models services as directed attributed graphs, maintains a repository of service graphs, and dynamically combines multiple basic services into complex services. Further, we present a hierarchical overlay structure created among the devices to exploit the resource unevenness, resulting in the capability of providing essential service-related support to resource-poor devices. Results of extensive simulation studies are presented to illustrate the suitability of the proposed mechanism in meeting the challenges of pervasive computing user mobility, heterogeneity, and the uncertain nature of involved resources.     

Adaptive and context-aware service composition for IoT-based smart cities

Smart Cities are advancing towards an instrumented, integrated, and intelligent living space, where Internet of Things (IoT), mobile technologies and next generation networks are expected to play a key role. In smart cities, numerous IoT-based services are likely to be available and a key challenge is to allow mobile users perform their daily tasks dynamically, by integrating the services available in their vicinity. Semantic Service Oriented Architectures (SSOA) abstract the environment’s services and their functionalities as Semantic Web Services (SWS). However, existing service composition approaches based on SSOA do not support dynamic reasoning on user tasks and service behaviours to deal with the heterogeneity of IoT domains. In this paper, we present an adaptive service composition framework that supports such dynamic reasoning. The framework is based on wEASEL, an abstract service model representing services and user tasks in terms of their signature, specification (i.e., context-aware pre-conditions, post-conditions and effects) and conversation (i.e., behaviour with related data-flow and context-flow constraints). To evaluate our composition framework, we develop a novel OWLS-TC4-based testbed by combining simple and composite services. The evaluation shows that our wEASEL-based system performs more accurate composition and allows end-users to discover and investigate more composition opportunities than other approaches.     

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Cloud computing is a recent advancement wherein IT infrastructure and applications are provided as ‘services’ to end‐users under a usage‐based payment model. It can leverage virtualized services even on the fly based on requirements (workload patterns and QoS) varying with time. The application services hosted under Cloud computing model have complex provisioning, composition, configuration, and deployment requirements. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, we propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as data centers, virtual machines (VMs) and resource provisioning policies. It implements generic application provisioning techniques that can be extended with ease and limited effort. Currently, it supports modeling and simulation of Cloud computing environments consisting of both single and inter‐networked clouds (federation of clouds). Moreover, it exposes custom interfaces for implementing policies and provisioning techniques for allocation of VMs under inter‐networked Cloud computing scenarios. Several researchers from organizations, such as HP Labs in U.S.A., are using CloudSim in their investigation on Cloud resource provisioning and energy‐efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in the hybrid federated clouds environment. The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns. Copyright © 2010 John Wiley & Sons, Ltd.     

一种动态混合QoS语义的Web服务个性化推荐模型

服务推荐是服务计算中的主要问题之一,当前大多针对功能属性进行推荐,而在Web服务的QoS属性方面考虑较少,并且不支持动态变化的QoS属性。基于动态混合QoS的语义Web服务个性化推荐模型,把语义Web技术引入Web服务中,在QoS监控器下,有效监测Web服务的QoS属性变化并动态更新Web服务的QoS属性。根据建立的用户兴趣模型,向用户推荐具有个性化的Web服务。此外,在个性化推荐系统中使用最广泛的协同过滤推荐技术基础上,对数据进行了一系列的预处理填充,而且充分考虑了不同时间的项目评分对推荐的影响。结合用户兴趣度和用户评分的相似性计算方法,并通过不同的权值来表示它们的重要程度,综合计算目标用户的最近邻居集合,最终对用户u产生推荐。该系统在一定程度上提高了服务推荐的效率和准确度并满足用户查询需求。     

A lightweight conditional privacy-preserving authentication and access control scheme for pervasive computing environments

In pervasive computing environments, the users can get access to the services from the service providers in a highly desirable way. But the security of the user's authentication is a challenging field. Pervasive computing environments must provide the service to only legitimate users. On the other hand, some users attempt to keep their anonymity without revealing their identities while using some privacy-related services such as location information, printing, buying shares, etc. In this paper, we propose a conditional privacy-preserving authentication and access control scheme for pervasive computing environments, called CPriauac. Compared with the previous schemes in the literature, registration servers and authentication servers in the proposed scheme need not maintain any sensitive verification tables. The management of public keys is easier. Furthermore, the anonymity of the user can be removed efficiently once the dispute happens. The proposed scheme provides user anonymity against outside and inside parties, mutual authentication, accountability and differentiated access control.     

基于语义的QoS感知Web服务发现机制

随着提供相同功能的Web服务数量的日益增多,服务质量(Quality of Service,QoS)成为用户选择Web服务的重要考虑因素.目前,通过对服务QoS属性在语法层匹配来提供Web服务选取的机制不能很好地满足复杂QoS属性匹配的要求.研究了基于用户QoS需求偏好,将用户需求的QoS与候选服务的QoS进行语义比较,结合约束规划(Constraint Programming)方法,在语义层匹配Web服务的QoS属性,选取满足匹配要求的服务,最后对满足QoS属性值约束的候选服务进行优化选择处理,获取最终匹配的候选服务.     

基于云模型的不确定性QoS 感知的Skyline 服务选择

由于传统QoS感知的Web服务选择方法无法保证服务选择的可靠性和实时性,提出了一种基于云模型的不确定性QoS感知的Skyline服务选择方法.该方法首先通过云模型计算QoS的不确定性,然后采用Skyline计算提取Web服务中的Skyline服务,剔除冗余服务,最后采用混合整数规划在Skyline服务中进行服务选择.在公共有效数据集和合成数据集上的实验结果表明,所提出的方法能够为用户提供可靠、快速的服务选择.     

Enhancing Residential Gateways: A Semantic OSGi Platform

The OSGi (open service gateway initiative) service platform specification is the most widely adopted technology for building a control system for the networked home. Three main features contribute to its success. First, it supports various well-known protocols, simplifying communication among home devices. In addition, it defines a cooperative model for applications to dynamically discover and use services provided by others. Finally, it allows flexible remote management of these applications and the services they provide. So, an OSGi solution supports decentralization, diversification, and ubiquity not only in smart homes but in pervasive environments generally.     

基于QoS本体的Web服务描述和选择机制

随着Web服务数量的急剧增长,如何从大量功能相似的Web服务中选择具有最好的服务质量(Quality of Service,QoS)的Web服务成为研究的热点.提出了一种基于QoS本体支持QoS的服务选择方法,用QoS本体以及相应的词汇来描述QoS数据,基于以上的工作,提出了一种支持QoS的选择机制,将QoS参数的语义匹配度和数值匹配度相结合,利用归一化算法对不同类型的QoS参数取值进行标准化,最后提出了一个公平的,动态的选择机制和相关实验结论.     

一种QoS感知的Web服务群体评价方法

传统QoS感知的Web服务选择方法需要用户给出精确权重以表达其对QoS属性的偏好。为解决用户无明确偏好情况下的服务选择问题,提出了一种QoS感知的Web服务群体评价方法。对Web服务群体评价的需求进行了详细的分析,以有明确QoS偏好的用户对服务的历史选择结果为基础,利用群决策的Condorcet和Borda函数集结这些结果得到服务的群体评价,从而使得无明确QoS偏好用户可以参考该评价结果进行服务选择。理论分析和仿真实验验证了该服务群体评价方法的合理性和有效性。     

A robotic service framework supporting automated integration of ubiquitous sensors and devices

In recent years, due to the emergence of ubiquitous computing technology, a new class of networked robots called ubiquitous robots has been introduced. The Ubiquitous Robotic Companion (URC) is our conceptual vision of ubiquitous service robots that provides its user with the services the user needs, anytime and anywhere, in the ubiquitous computing environments. There are requirements to be met for the vision of URC. One of the essential requirements is that the robotic systems must support ubiquity of services. This means that a robot service must always be available even though there are changes in the service environment. More specifically, a robotic system needs to be interoperable with sensors and devices in its current service environments automatically, rather than statically pre-programmed for its environment. In this paper, the design and implementation of an infrastructure for URC called Ubiquitous Robotic Service Framework (URSF) is presented. URSF enables automated integration of networked robots in a ubiquitous computing environment by the use of Semantic Web Services Technologies.     

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.     

QoS-aware service composition for distributed video surveillance

Quality of Service (QoS) is essential for the ubiquitous access of media services in real-time distributed video surveillance applications. To have ubiquitous access of desired media with emergency officials’ handheld devices, appropriate media transcoding services are required. Currently, it is challenging to select and compose these services for each of the devices to satisfy the desired QoS demand. To compose these media services so that video stream is available for target pervasive and smart devices, a composition algorithm is required. Thus, this paper presents a QoS-aware service composition algorithm to select the best composition for the target ubiquitous client so that it can optimally provide QoS to heterogeneous users. We have implemented a video surveillance prototype to demonstrate the performance of the proposed QoS-aware composition algorithm. Results from this prototype reveal that the approach is suitable for real-time video surveillance.     

Broker-based SLA-aware composite service provisioning

QoS-aware service composition aims to satisfy users’ quality of services (QoS) needs during service composition. Traditional methods simply attempt to maximize user satisfaction by provisioning the composite service instance with the best QoS. These “best-effort” methods fail to take into account that there also exist other consumers competing for the service resources and their decisions of service selection/composition can impact on QoS. Since user's QoS needs can be met once the demanded level is reached, in this paper, we propose an “on-demand” strategy for QoS-aware service composition to replace the traditional “best-effort” strategy. The service broker is introduced to facilitate implementation of this strategy: it first purchases a number of service instances for each component from providers and then provisions the composite services with different QoS classes to consumers. This paper focuses on how the broker follows the service level agreement (SLA) to provision composite services in the “on-demand” manner. This problem is formally expressed as the minimization of the QoS distance function between SLA and QoS of composite service instances, under a series of constraints. Heuristic approaches are proposed for the problem and experiments are conducted at last to verify their effectiveness and efficiency.