A QoS-aware Method for Web Services Discovery

The non-functional QoS (quality of service) information helps us to select a proper Web-service from the web applications, by using component services such as UDDI[1](Universal Description, Discovery, and Integration) and MDS(Monitoring and Discovery System). MDS is a suite of web services to monitor and discover resources and service on Grids, but MDS only based on function aspects. This paper studies on an approach to provide the QoS information and a discovery model by using MDS and gives a system deployment and implementation plan. The simulation results show that the method is effective in service discovery.

Interactive Web service choice-making based on extended QoS model

Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance assurance, ignoring domain specific or application level metrics which are also very important to service users. Industry Web service standards lack QoS expression. The support for QoS based service choice-making is very limited. We proposed an extended Web service QoS model based on configurable fuzzy synthetic evaluation system. Web service QoS is evaluated dynamically according to the service context. A QoS requirement description model is also given for service QoS requirement definition. An interactive Web service choice-making process is described, which takes QoS as a key factor when choosing from functionally equivalent services.

An approach for QoS measurement and web service selection sureness

Web services have gained popularity in recent years and provide a new model of web,which facilitates interaction of scientific and business applications through the Internet.More often,several services with similar functionality are available from a large and changing number of service providers.Quality of Service(QoS)is the dominant factor in service selection and is of great importance to users.In this paper,we propose a model for QoS measurement and web services selection.The model consists of QoS model,QoS monitoring,QoS comparison and service selection with a QoS feedback mechanism.The most suitable service is to take into account the agreed QoS,monitoring is done during invocation phase and if any deviation is recorded,next suitable service is selected.Finally the model is proved to be feasible and effective by simulation experiments.

Constraint-based QoS-aware Web Service Composition in Cross-organizational Collaboration

To improve the Quality of Service (QoS)-aware Web service compositions considering constraints between cross-organizational business,this paper analyzes the types of constraints,and accordingly proposes a Chaos Genetic Algorithm (CGA). The algorithm creates an initial population of service compositions based on the chaos theory,and then processes individuals which violate constraints in the initial population using repair strategies. Next,a new fitness function is designed to gradually eliminate the infeasible compositions generated in evolution. Finally,the algorithm makes minor chaotic disturbances on the evolved group to accelerate convergence and avoid local optimum. Experimental results demonstrate the effectiveness of the proposed algorithm.

Hybrid Metaheuristics Web Service Composition Model for QoS Aware Services

Recent advancements in cloud computing(CC)technologies signified that several distinct web services are presently developed and exist at the cloud data centre.Currently,web service composition gains maximum attention among researchers due to its significance in real-time applications.Quality of Service(QoS)aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS.But these models have failed to handle the uncertainties of QoS.The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users.On the other hand,trip planning is an essential technique in supporting digital map services.It aims to determine a set of location based services(LBS)which cover all client intended activities quantified in the query.But the available web service composition solutions do not consider the complicated spatio-temporal features.For resolving this issue,this study develops a new hybridization of the firefly optimization algorithm with fuzzy logic based web service composition model(F3L-WSCM)in a cloud environment for location awareness.The presented F3L-WSCM model involves a discovery module which enables the client to provide a query related to trip planning such as flight booking,hotels,car rentals,etc.At the next stage,the firefly algorithm is applied to generate composition plans to minimize the number of composition plans.Followed by,the fuzzy subtractive clustering(FSC)will select the best composition plan from the available composite plans.Besides,the presented F3L-WSCM model involves four input QoS parameters namely service cost,service availability,service response time,and user rating.An extensive experimental analysis takes place on CloudSim tool and exhibit the superior performance of the presented F3L-WSCM model in terms of accuracy,execution time,and efficiency.

A Neuro-Fuzzy Model for QoS Based Selection of Web Service

The automatic selection and composition of Web services rely strongly on the manner to deal with ambiguity inherent to the description of functionalities of these services and the client’s requests. Quality of Service (QoS) criteria become crucial in Web services selection and the problem of checking that a web service satisfies a given level of QOS is considered in recent research works. This paper presents a QoS based automatic classification method of web services. These services give generally similar functionalities and are offered by different providers. The main feature of our Web service selection model is to take advantage of the neuro-fuzzy logic for coping with the imprecision of QoS constraints values.

一种可扩展的Web Service QoS管理框架

Web Service是目前研究界和产业界广泛关注的技术之一.随着Web Service的广泛应用,研究者们普遍认识到,服务的非功能属性,即服务质量(Quality of Service,QoS)是面向服务的应用能否成功的关键因素之一.因此,研究者们尝试从多个角度对QoS相关问题展开了研究.然而,现有工作普遍关注基于QoS的动态服务选择和组装等上层应用技术,而对于如何获取、存储、度量QoS等基础支持技术研究较少,而这些基础性工作对QoS相关的研究工作具有显著的重要性.此外,不同应用领域对Web Service QoS的需求不尽相同,因此,需要有一套灵活的机制支持在QoS模型定义、QoS度量方法、QoS信息采集等方面体现出的领域特性.针对这个问题,文中提出了一个可扩展的Web Service QoS信息管理框架,详细分析了该框架涉及到的重要方法与核心技术,并给出了该框架在北京大学软件构件库系统中的设计决策和方案.最后,介绍了文中框架在一个863计划项目中的应用实例,该实例展示了用户根据其应用的领域需求对本框架进行扩展并进行Web Service QoS管理的方法,从而验证了本管理框架的可扩展性及实用性.

基于时间序列分析的Web Service QoS预测方法

通过网络提供服务的Web Service的服务质量会随着网络环境、服务器负载等因素的变化而变化,如何更好地帮助用户选择在未来一段时间内符合服务质量需求的Web Service,是目前服务计算领域中需要解决的关键问题之一。针对上述问题,提出了一种基于时间序列分析的Web Service QoS预测方法,并实现了相应的Web Service QoS自动预测工具。该工具能够根据Web Service的历史QoS数据,有效地预测未来短期内的QoS信息。以17832个Web Service的历史数据为基础,设计了相关实验,并验证了方法的有效性。

基于代理的Web Services QoS模型研究

服务质量(QoS)描述了服务满足消费者需求的能力,提供有保证的QoS是Web服务在商业应用中获得成功的关键。本文分析了Web Services QoS的特点和实现过程,提出一种更适合于Web Services环境下的QoS建模过程,提出一种基于代理的有QoS保障的Web Services模型。通过在传统的Web Services架构的基础上进行扩展,增加一个代理,充分发挥代理技术的灵活性、可扩充性、可重用性等优点。将QoS的相关工作完全交给代理来完成,实现一个改进的Web Services QoS架构。

Web Services QoS的研究与应用

出于对组合Web服务QoS管理的目的,从对组合服务管理的QoS要求出发,对WSDL进行扩展提出了新的服务描述语言,并扩展了Web服务的角色——服务代理角色,通过在传统的WebServices架构的基础上进行扩展,给出了一个改进的WebServices架构以及原型系统的实现方案和试验,并对试验结果作了分析。

基于多Agent的Web Service QoS模型

Web Service是采用面向服务的体系架构的基于标准的Web协议的软件构件,而Agent是一种在异构环境中自主行动以实现其设计目标的智能化软件实体。文章研究了利用Agent技术来进行动态发现、绑定符合用户QoS需求的Web Service,从而能够为用户提供更好的服务。

QoS Evaluation for Web Service Recommendation

Web service recommendation is one of the most important fi elds of research in the area of service computing. The two core problems of Web service recommendation are the prediction of unknown Qo S property values and the evaluation of overall Qo S according to user preferences. Aiming to address these two problems and their current challenges, we propose two efficient approaches to solve these problems. First, unknown Qo S property values were predicted by modeling the high-dimensional Qo S data as tensors, by utilizing an important tensor operation, i.e., tensor composition, to predict these Qo S values. Our method, which considers all Qo S dimensions integrally and uniformly, allows us to predict multi-dimensional Qo S values accurately and easily. Second, the overall Qo S was evaluated by proposing an efficient user preference learning method, which learns user preferences based on users' ratings history data, allowing us to obtain user preferences quantifiably and accurately. By solving these two core problems, it became possible to compute a realistic value for the overall Qo S. The experimental results showed our proposed methods to be more efficient than existing methods.

Web QoS控制研究综述

Internet的服务模式正由传统的数据通信与信息浏览向电子交易与服务转变 ,Web服务器系统作为支持电子商务的核心设施 ,需要对不同的用户或HTTP请求提供区分服务和性能保证 ,因此必须具备建立和支持服务质量 (QualityofService ,QoS)控制的机制与策略 .该文综述了WebQoS控制的研究现状 ,包括Web请求的分类机制、Web服务器应用软件的QoS控制机制、操作系统的WebQoS控制机制、中间件的WebQoS控制机制以及Web服务器集群系统的QoS控制机制与策略 ,并分析了进一步的研究方向 .

预测Web QoS的协作过滤算法

不同环境中用户对同一服务质量的感受可能存在较大差别,针对这一问题,提出了一种QoS预测方法.该方法不仅使用了历史QoS信息,还将环境因素、用户输入等对QoS的影响考虑进去.以这些信息为基础,首先通过高斯法对原始信息数据进行规范化处理,然后计算其他服务与待预测服务的相似度,找到与目标服务相似度较大的服务集,并根据服务相似度预测空白信息,在此基础上计算用户的相似度,从而为用户预测目标服务的QoS值.实验结果表明,这种方法可以显著提高Web服务质量预测的准确性.

基于内容自适应的Web QoS反馈控制系统研究

提出了一种基于内容自适应的Web QoS反馈控制系统。首先分析Web QoS的组成及主要保证方法,并研究了队列控制当中的反馈控制机制,实现任务数量的稳定;然后,分析了Web内容自适应的机制与实现,提高了系统的自我调节能力;最后详细介绍这种Web QoS系统的模型。

Web QoS及其保证方法

Internet的服务模式正由传统的数据通信与信息浏览向电子交易与服务转变,仅靠网络QoS机制并不能完全解决端到端的QoS控制问题。Web服务器系统作为核心设施,必须同样具备建立和支持QoS的机制与策略,对不同的用户或HTTP请求提供区分服务和性能保证。文中综述了Web QoS的发展情况、研究现状以及保证方法(包括请求分类机制的划分方法、Web服务供应商的Web系统解决方案以及无线网络的保证方法),并分析了进一步的研究方向。

Web QoS的测控技术

随着基于Web的Internet应用越来越广泛,提高Web服务器的性能(QoS),已成为当前研究的热点课题。为了提高Web服务器的性能,必须研究Web QoS的测控技术。系统地阐述了Web QoS的测控技术中的几个主要问题,包括:测量技术中的负载发生器、网络流量的自相似模型和测试软件等问题,控制技术中的Web QoS反馈控制、控制目标、建模和控制算法等问题。

Dynamic Web service selection group decision-making based on heterogeneous QoS models

In open and dynamic Internet environment, multi-periods quality of service （QoS）, multiple decision-makers based on heterogeneous QoS models and uncertainty weights make optimal Web service selection hard. To solve the difficulties above, dynamic Web service selection group decision-making based on heterogeneous QoS models （DWSSGD_HQM） is proposed. Drawing on and extending technique for order preference by similarity to ideal solution （TOPSIS）, DWSSGD_HQM supports multiple decision-makers based on heterogeneous QoS models expressed in real numbers, interval numbers, triangular fuzzy numbers and intuitionistic fuzzy numbers respectively, and takes multi-periods QoS and weights of user and group into account. Six steps are detailed. They are converting heterogeneous QoS models into ones expressed in interval numbers, calculating weighted normalized decision-matrix, determining the group positive-ideal and negative-ideal solutions, calculating the close-degrees of candidates, aggregating close-degrees of multi-periods for each decision-maker, and ranking the alternatives. Finally, experiments are conducted by using actual QoS data to evaluate the effectiveness of the proposed approach.