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.     

Research on dynamic business composition based on web service proxies

Web services-based business composition brings a number of advantages to the enterprise application development. How to select and compose the web services based on their functionality and QoS (Quality of Service) dynamically prove to be more and more important. In this paper we develop a proxy-based framework to compose Web services dynamically. The framework is featured with a QoS model, an effective service discovery and selection algorithms to facilitate the dynamic integration of Web services and management of abnormalities. Furthermore, a business process constructing method based on service slice is put forward to satisfy the users’ personalized requirements more effectively and flexibly. Our study concerns both functionality and QoS characteristics of Web services to identify the optimal business process solutions. A Complete case study is also included in this paper and the performance demonstrated that the framework and algorithms can provide a tangible and reliable solution to dynamic Web service composition and adaptation.     

Composing Web Services: A QoS View

An Internet application can invoke several services--a stock-trading Web service, for example, could invoke a payment service, which could then invoke an authentication service. Such a scenario is called a composite Web service, and it can be specified statically or established dynamically. Dynamic composition of Web services requires service consumers to discover service providers that satisfy given functional and nonfunctional requirements including cost and QoS requirements such as performance and availability. In previous columns, I've examined how quality of service (QoS) comes into play for service providers, consumers, and parallel transactions. Here, I'll show how it fits into composite Web services.     

Flexible service selection with user-specific QoS support in service-oriented architecture

Along with the development of the service-oriented architecture (SOA) and cloud computing, a large number of service providers have created an intense competitive world of business. Consequently, it is becoming increasingly complex to select a service provider for a user as a result of their various economic and social attributes. In this paper, we state the problem of how to find the appropriate services with satisfying the users' multiple QoS requirements. We consider the service's response time, trust degree and monetary cost. And inspired from the mode of Web search engine, such as Yahoo, Google, we propose an innovative service selection algorithm for SOA systems. The algorithm can recommend a number of suitable services based on the user's QoS requirements.Compared with the existing scheduling algorithms, our solution is much more flexible in supporting the multiple objectives and user personalization. We study the scalability of the algorithm with different numbers of jobs, service providers and QoS criteria. And we find that it can capture user's preferences value in less than six times of job submissions.     

QoS-Aware Web Service Configuration

With the development of enterprise-wide and cross-enterprise application integration and interoperation toward Web service, Web service providers try to not only fulfill the functional requirements of Web service users but also satisfy their nonfunctional conditions in order to survive in the competitive market. A hot research topic is how to configure Web services to meet their demand when the diversity of user requirements, distinction of service components' performance, and limitation of resources are considered. This paper builds a Web service configuration net based on Petri nets in order to exhibit Web service configurations in a formal way. Then, an optimal algorithm is presented to help choose the best configuration with the highest quality of service to meet users' nonfunctional requirements. Finally, the simulation results and related analysis prove the soundness and correctness of our model and algorithm.     

Model-driven trust negotiation for Web services

Trust negotiation is an approach to access control whereby access is granted based on trust established in a negotiation between the service requester and the service provider. Trust negotiation systems avoid several problems facing traditional access control models such as DAC (discretionary access control) and MAC (mandatory access control). Another problem is that Web service providers often do not know requesters identities in advance because of the ubiquitousness of services. We describe Trust-Serv, a trust negotiation framework for Web services, which features a policy language based on state machines. It is supported by lifecycle management and automated runtime enforcement tools. Credential retrieval and validation in Trust-Serv rely on predefined Web services that provide interactions with attribute assertion authorities and public key infrastructure.     

Quality management in service ecosystems

Service-oriented architectures and Web services mature and have become more widely accepted and used by industry. This growing adoption increased the demands for new ways of using Web service technology. Users start re-combining and mediating other providers’ services in ways that have not been anticipated by their original provider. Within organisations and cross-organisational communities, discoverable services are organised in repositories providing convenient access to adaptable end-to-end business processes. This idea is captured in the term Service Ecosystem. This paper addresses the question of how quality management can be performed in such service ecosystems. Service quality management is a key challenge when services are composed of a dynamic set of heterogeneous sub-services from different service providers. This paper contributes to this important area by developing a reference model of quality management in service ecosystems. We illustrate the application of the reference model in an exploratory case study. With this case study, we show how the reference model helps to derive requirements for the implementation and support of quality management in an exemplary service ecosystem in public administration.     

基于监视的服务质量评估方法

在面向服务的体系结构(Service Oriented Architecture,SOA)中,消费者的目标是发现和使用高质量的服务。随着Web服务数量的不断增加,为用户推荐和选择最满足需求的Web服务已经成为服务计算领域最重要的挑战之一。在SOA中,传统的质量评估方法偏重于消费者获得更高的性能,未充分考虑消费者的个性化需求,这样,并不一定让消费者获得完全满足其需求的服务。因此,在服务选择和推荐过程中不仅需要考虑服务的功能性需求,还需要考虑服务的非功能性需求。而且,服务质量的改变只能在服务运行过程中才能被发现。为了解决上述问题,本文提出一种基于监视的服务质量评估方法,充分考虑服务的功能性和非功能性属性,建立统一模型,根据监视数据动态评估服务质量,为动态环境下选择和推荐服务提供依据。本文最后描述了该方法的实现框架。     

基于质量的数据挖掘服务选择

在面向服务的数据挖掘系统中各种数据挖掘的算法封装成 Web服务.用户选择合适的数据挖掘服务执行自己的数据挖掘任务,而大多数最终用户并不具备这样的专业知识.从方便用户的角度出发,系统需提供一套服务选择机制,来帮助用户选择高质量的数据挖掘服务.综合通用Web服务的评价标准、数据挖掘领域的专用评价因子及用户评价反馈等多种因素及服务的动态性,给出了一个较全面的数据挖掘服务评价本体,讨论了服务质量的评价方法,给出了基于服务质量评价的动态数据挖掘服务选择方法,用户可根据数据挖掘服务评价本体的语义模型,输入质量约束条件,也可以调整评价因子权值,系统在满足用户约束条件的服务集中,通过计算出服务的综合质量值,挑选最适合的算法执行.     

Application-level QoS control for video-on-demand

User requirements and device heterogeneity call for Web services with differentiated quality of service (QoS). In particular, services with response-time constraints, such as video-on-demand (VoD), require the differentiation, control, and dynamic adaptation of QoS. Service providers and network operators need methodologies and mechanisms for managing runtime QoS. Using mobile agent technology, the ubiQoS middleware supports QoS tailoring and adaptation of video-on-demand flows in response to user preferences and terminal properties. The design, implementation, and deployment of QoS-aware Internet services can significantly benefit from a middleware approach at the application level. Our experimental results show the feasibility of application-level middleware solutions based on code mobility for Internet VoD services with differentiated QoS.     

Web应用服务器的适应性失效检测

失效检测是分布式系统的基本可靠性保障技术,它对运行时系统的存活状态进行及时检测.作为网络分布计算环境中的主流中间件,Web应用服务器(Web application server,简称WAS)需要提供良好的检测机制,并且要能满足适应性的需求.适应性失效检测要求失效检测器能够根据应用需求和系统环境的变化而动态地改变检测的质量.首先给出了WAS的多层失效检测模型,然后基于失效检测器的服务质量规约,提出了适应性失效检测算法,并设计了一个WAS的适应性失效检测框架.它能够满足动态调整失效检测质量和灵活集成失效检测器的要求.该工作在OnceAS应用服务器中进行了实现,并给出了OnceAS平台上的实验及数据.     

Daios: Efficient Dynamic Web Service Invocation

Systems based on the service-oriented architecture (SOA) paradigm must be able to bind to arbitrary Web services at runtime. However, current service frameworks are predominantly used through precompiled service-access components, which are invariably hard-wired to a specific service provider. The Dynamic and Asynchronous Invocation of Services framework is a message-based service framework that supports SOA implementation, allowing dynamic invocation of SOAP/WSDL-based and RESTful services. It abstracts from the target service's internals, decoupling clients from the services they use.     

QoS-aware service selection via collaborative QoS evaluation

We present in this paper a novel collaborative filtering based scheme for evaluating the QoS of large scale Web services. The proposed scheme automates the process of assessing the QoS of a priori unknown service providers and thus facilitates service users in selecting services that best match their QoS requirements. Most existing service selection approaches ignore the great diversity in the service environment and assume that different users receive identical QoS from the same service provider. This may lead to inappropriate selection decisions as the assumed QoS may deviate significantly from the one actually received by the users. The collaborative filtering based approach addresses this issue by taking the diversity into account instead of uniformly applying the same QoS value to different users. They predict a user’s QoS on an unknown service by exploiting the historical QoS experience of similar users. Nevertheless, when only limited historical QoS data is available, these approaches either fail to make any predictions or make very poor ones. The cornerstone of the proposed QoS evaluation scheme is a Relational Clustering based Model (or RCM) that effectively addresses the data scarcity issue as stated above. Experimental results on both real and synthetic datasets demonstrate that the proposed scheme can more accurately predict the QoS on unknown service providers. The efficient performance also makes it applicable to QoS evaluation for large scale Web services.     

Unlocking the Advantages of Dynamic Service Selection and Pricing

Bandwidth limitations, resource greedy applications verbose mark-up languages and an increasing number of voice and data users are straining the air interface of wireless networks. Hence, novel approaches and new algorithms to manage wireless bandwidth are needed. In addition, usage based pricing is becoming increasingly prevalent (pre-paid cell phones, calling cards, non-contract minutes, etc.). This paper unlocks the potential to improving the performance of overall system behavior by allowing users to change service level and/or service provider for a (small) price. The ability to dynamically re-negotiate service gives the user the power to control QoS while minimizing usage cost. On the other hand, the ability to change service level pricing dynamically allows the service providers to manage traffic better, improve resource usage and most importantly maximize their profit. This provides a surprising win-win situation for BOTH the service providers AND the users. In this paper we present easy to implement on-line algorithms to minimize the overall usage cost to individual mobile users. This on-line algorithm continuously receives pricing information and evaluates minimum QoS requirements. The algorithm then determines appropriate service level, chooses a service provider and sets a time for re-negotiation dynamically. Our algorithm can handle many practical issues such as capacity limitations, arbitrary price fluctuations and loss/gain of service providers due to mobility. Our results do not assume any specific technologies and can be applied to any environment that can employ dynamic pricing, including wired networks. In fact, dynamic pricing is becoming increasingly desirable since service provider and capacity changes are a growing by-product of mobility. Arriving and departing users at/from a cell tower (or wireless LAN) can effectively reduce or increase the available bandwidth in a cell (or LAN transmission area) and represents a natural opportunity for a pricing change.     

一个基于自管理单元支持差分服务的Web容器

随着Internet的飞速发展,符合J2EE规范的Web容器已经成为部署企业Web应用的主流平台.同时,企业Web应用的多样化和复杂性的增长,迫切地要求Web容器提供差分服务的支持.然而,传统的Web容器采用尽力而为的服务模型,无法提供差分服务支持.已有的研究采用准入控制、优先级调度等方法来为Web容器提供差分服务支持,但是它们只能提供单调、静态的差分服务策略.提出了一个基于自管理单元的Web容器DSWC,它能够根据SLA定义提供两级差分服务支持.此外,提出了一个自适应差分服务策略选择算法,它能够根据动态变化的运行环境自适应地选择差分服务策略.原型系统的实验结果显示,DSWC能够有效地为请求提供符合SLA定义的细粒度的差分服务支持.     

基于事例推理的Web服务QoS动态预测研究

随着面向服务计算技术的发展,网络上出现了大量功能相同而服务质量(QoS)有很大差别的Wcb服务,QoS逐渐成为评价和选择Web服务的重要依据。目前常用Web服务历史QoS的算术平均值来近似服务的QoS,这种度量方法没有考虑Wcb服务QoS的动态性,不能准确地度量Wcb服务的QoS,从而造成被选择的Wcb服务以较大概率不能满足用户的QoS需求。针对这一问题,提出了一种基于事例推理(C13R)的QoS动态预测方法,该方法将Web服务的QoS与服务的外界环境、所处理的任务类型、任务大小关联起来,利用事例推理技术预测Web服务处理新任务时的QoS。实验结果表明,该预测方法能有效地提高Wcb服务QoS的准确度。     

基于协同过滤的个性化Web服务选择方法

对传统的Web服务选择算法进行分析,并指出其在动态环境下存在的问题。为了解决该问题,提出了基于协同过滤算法的个性化Web服务选择方法,并设计了一个动态的Web服务选择架构,架构使用协同过滤算法对Web服务的服务质量(QoS)值进行预测并选择最优的Web服务以满足用户的需求。使用150万条真实Web服务的QoS数据与其他4类算法进行了对比实验,结果表明所提方法的可行性和准确性。     

基于隐私度和稳定度的D2D数据共享伙伴选择机制

设备到设备（D2D）数据共享已经成为一种很有前途的卸载蜂窝网络流量的解决方案,但数据共享伙伴的隐私脆弱性和服务不稳定性影响着共享服务的质量。针对这个问题,提出一种基于隐私度和稳定度的D2D数据共享伙伴选择机制（PSUS）。首先对提供者的隐私信息进行抽象和概括,根据提供者的隐私偏好和历史共享记录构建隐私度量的方法,得出提供者在不同共享服务中的隐私度;然后基于隐私度来设计数据共享过程,提供者在隐私偏好约束下缓存数据并在隐私度低的时候参与共享服务以满足提供者的隐私要求;最后在已满足隐私要求的提供者的基础上,设计一种多指标评价法来评估提供者的服务稳定性以选择稳定的共享伙伴。通过性能分析,证明所提机制的可行性。     

Using Policies to Manage Composite Web Services

When no single Web service can fulfil a user's request, providers often turn to composite Web services. However, developing a composite Web service is not simple and deploying the composition specification at runtime consists of several processes. Developers and deployers of composite Web services can use policies in various scenarios, from the announcement of Web services to the compatibility between Web services and composite Web services. Mapping guidelines for a Web service's behavior to policies can ensure an individual Web service's smooth engagement into a composite Web service