一种基于多QoS注册中心和模型异构的WEB服务选择算法

多QoS注册中心并且QoS模型异构给服务选择带来巨大困难。借鉴多属性群决策(MAGDM)理论的基本思想,该文提出一种解决上述难题的多注册中心和模型异构的Web服务选择算法(MRHQ_WSSA)。MRHQ_ WSSA算法能综合评估各QoS注册中心的QoS信息,从而获得QoS综合最优的服务组合计划。MRHQ_WSSA算法包括5个步骤：用户偏好规格化、群偏好确定、加权规格化决策矩阵、确定群理想方案、计算群贴近度。最后通过实验验证算法的优势和有效性。     

动态QoS数据驱动的可靠Web服务选择

基于服务质量(QoS)的Web服务最优选择是一个热点问题。高度动态的QoS数据导致QoS模型的不确定性,对可靠的Web服务选择构成巨大的挑战,该文提出动态QoS数据驱动的可靠Web服务选择(DQoS_RSS)。首先利用均值标准差刻画QoS数据的效益和风险,提高QoS描述的准确度;接着建立不确定服务Skyline集,缩小搜索空间,提高选择效率;借鉴优劣解距离法(TOPSIS),设计2种Web服务选择算法,获得体现用户需求的最优服务。另外,介绍2种QoS模型转换器,以及能够适应QoS动态变化的QoS模型自适应调整机制。最后,实验分析验证了该方法的优越性和高效性。     

基于Bootstrap技术的Web服务QoS值的置信区间估计和预测

目前对Web服务QoS（Quality of Service）的预测研究,通常预测QoS的静态值,很少预测QoS值的置信区间.本文借助非参数统计学的Bootstrap技术,提出估计Web服务QoS值置信区间的方法;然后利用与当前Web用户相似的其他Web用户调用待预测Web服务的QoS历史数据,预测当前Web用户调用待预测Web服务的QoS值的置信区间.本文估计了WSDream数据集1中每个用户调用每个Web服务的QoS值的置信区间,实验发现这些置信区间的上下限近似服从重尾分布.通过随机选择WSDream数据集1中60%到90%的用户和Web服务作为训练集,预测另外10%到40%的用户和Web服务的QoS值,实验结果表明预测的QoS置信区间与估计的QoS置信区间的平均覆盖率超过70%,最高达76%.在服务选择或服务推荐时给用户提供一个估计的或预测的QoS置信区间,可以更好地满足用户的个性化需求.     

基于差异演化算法的QoS全局最优动态Web服务选择

QoS全局最优动态Web服务选择是服务组合中的一个难题。基于差异演化算法,设计一种用于解决该问题的DE-GODSS算法。算法的主要思想是将问题表示为一个带QoS约束的多目标服务组合优化问题,通过理想点的方法将多目标向单目标转化,然后利用差异演化算法的智能优化原理进行算法设计及求解,最终产生一组满足约束条件的优化服务组合流程集。理论分析证明DE-GODSS算法的时间复杂度优于已有的多目标遗传算法,且实验结果表明该算法的收敛速度优于已有的多目标遗传算法。     

物联网服务动态评价选择方法研究

对于物联网WoT面向服务SOA的软件架构成中基于服务质量QoS选择最优服务的问题,给出了反馈控制的QoS属性向量动态更新过程和服务动态评价选择方法.基于WoT设备资源受限的特点,通过指数加权平均和以并发引用服务的客户端个数为价格因素的随机指数标记REM方式估计服务时间,在系统在线概率中加入服务相邻状态检测实现服务可用性的估计,基于偏好权值和QoS属性向量通过TOPSIS过程选择最优服务.NS-3.13的模拟实验结果表明基于QoS属性向量动态更新选择最优服务的准确性明显优于简单QoS属性向量.     

Web service selection algorithm based on principal component analysis

Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user’s preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user’s QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.     

A fuzzy modeling based dynamic resource allocation strategy in service grid

One of the major challenges in service grid is to guarantee the promised quality of service (QoS) for all the admitted users or applications, while maximizing the resource utilization through dynamic resource sharing. An efficient resource allocation method should ensure the service QoS and balance the load among service grid nodes which are often highly dynamic, heterogeneous and linked by wide-area network. In this paper, a new dynamic resource allocation method is presented and analyzed based on fuzzy modeling to solve the adaptation between heterogeneous applications with multiple QoS requirements and grid resource. Simulations in service grid with heterogeneous QoS requirements reveal that the proposed dynamic resource allocation method can distribute most suitable resource among the different service quickly and sensitively as the service QoS demand varies under the constraint of achieving maximum utilization of grid resources.     

一种新的基于Web服务超市平台的QoS测试方法

为保证Web服务的质量,需要对QoS(Quality of Service)进行测试.针对QoS测试中测试用例的自动生成和动态更新这些难点,基于实验室自主开发的Web服务超市平台,创新性地提出两阶段QoS测试方法:预测试阶段根据不同的数据选取策略,从数据池中不同的数据分区随机选择需要的数据组成若干测试用例进行测试;实值...     

具有全局质量保障的Web服务组合研究

随着面向服务架构（SOA）的开发技术不断成熟,Internet上涌现出功能相同或相似的Web服务集合越来越大,如何从这些集合中选出满足用户质量（QoS）的组合Web服务是目前国内外学者研究的热点问题。针对保证组合服务的质量（QoS）全局最优问题,基于图的理论构建服务组合模型,并在此模型上提出相应的服务选择算法,保障选择的组合服务的质量（QoS）全局最优。     

基于用户QoS的网络资源分配策略研究

针对5G网络在网络资源分配存在的问题,从用户业务QoS等级角度提出基于贝叶斯模型的网络资源优化分配策略模型。在对用户业务QoS等级划分的基础上采用优先节点自主控制策略进行网络资源分配,通过构建贝叶斯模型评价网络状态并进行动态学习推理,指导网络优先节点的控制决策,实现优先节点对最佳信道的优先选择。实验表明,与基于信道容量的信道资源分配策略相比,本文的策略在网络总体容量和网络公平性上具有更好的表现,能够更好满足异构网络的实际需求。     

具有QoS保障的组合服务管理框架

在可信服务中间件架构的基础上设计了一种具有QoS保障的组合服务管理框架,在此框架下提出了QoS规划算法和服务选择算法.利用上层的重协商机制和下层的组合服务调度机制为服务提供双层的QoS保障,以最大化的满足用户的QoS需求.最后通过实验证明了框架和算法的有效性.     

利用新的模糊免疫分类器的评价模型设计

随着Web服务数量的增加,根据Web服务的多维Qos属性度量Web服务质量成为研究热点之一。提出了一种利用模糊免疫网络记忆分类器的Web服务Qos评价。在该评价中首先结合SOA中Web服务描述给出了Web服务QoS评价模型。然后提出了一种新的人工免疫分类算法——FAINMC,利用该算法利用该算法对大量的Web服务实现准确、高效的分类。通过每类记忆细胞反应的特征得到相对应服务等级,最后使用模糊隶属度和百分法得到了反应Web服务质量优劣评价值。通过原型系统对模拟Web服务属性数据进行测试,表明该方法优选出QoS值尽可能大,QoS向量分量的特征分量一致性好的Web服务。     

A QoS‐Guaranteed Cell Selection Strategy for Heterogeneous Cellular Systems

In order to improve the accuracy of cell selection in heterogeneous cellular systems, this paper proposes a fuzzy multiple‐objective decision‐based cell selection (FMDCS) strategy. Since heterogeneous cellular systems have different access technologies and multiple traffic classes, the strategy adopts cell type, data rate, coverage, transmission delay, and call arrival rate as evaluation indices, and uses different weight vectors according to the traffic classes of the mobile host. Then, a fuzzy multiple‐objective decision algorithm is applied to select the optimal cell from all candidates. This paper also gives an instance analysis and simulation. The instance analysis shows FMDCS makes different selections for different traffic classes. Simulation results of the after‐handoff quality‐of‐service (QoS) show the selected cell can provide MH optimal service.     

A location-aware hybrid web service QoS prediction algorithm

Quality-of-service (QoS) describes the non-functional characteristics of Web services. As such, the QoS is a critical parameter in service selection, composition and fault tolerance, and must be accurately determined by some type of QoS prediction method. However, with the dramatic increase in the number of Web services, the prediction failure caused by data sparseness has become a critical challenge. In this paper, a new hybrid user-location-aware prediction based on WAA (HUWAA) is proposed. The implicit neighbor search is optimized by incorporating location factors. Meanwhile, the ability of the improved algorithms to solve the data sparsity problem is validated in experiments on public real world datasets. The new algorithms outperform the existing IPCC, UPCC and WSRec algorithms.     

基于局部近似过滤的多约束服务选择方法

随着Web服务数量与用户需求的不断增长,如何在功能约束和QoS约束下选择Web服务去构建高质量的组合服务已成为Web服务领域的一项重要研究内容。然而,现有大多数Web服务选择方法仅仅解决了在多种QoS约束下选择服务的问题,忽略了服务间的功能性约束。为解决这一问题,该文提出一种基于局部近似过滤的多约束服务选择方法。该方法首先利用候选服务在多种约束下的被选关系,滤除部分不满足约束的服务,并估算每个剩余候选服务的局部适应度;然后,利用文中设计的有向粒子群算法,以候选服务的局部适应度为引导信息搜索出最优方案。实验结果表明了方法的有效性。     

异构Web服务器集群的自适应成比例延时差异服务模型

随着Internet的迅速发展,Web服务在满足数量巨大而日益增长的社会需求中所起的作用越来越大,应用对Web服务器提出了更高的QoS(Quality of Service,服务质量)要求,特别是,要求其处理数量不断变更的用户访问,它们提出大量并发请求,并具有不同的QoS需求等.如何提高Web服务器QoS性能指标已成为当今研究的一大热点问题.本文提出一种成比例延时差异服务的异构Web服务器集群模型,该模型采用 : 队列模型刻划集群中各结点请求队列的请求到达和服务过程;在此基础上,提出两种基于反馈控制机制的请求派发自适应修正算法,每种算法均实现了相应的请求选择和派发策略.实验数据表明,本文所提出模型是适用于异构Web服务器集群的,两种请求派发自适应修正算法均能使异构Web服务器集群获得较好的服务质量(QoS)性能,具有较好的理论价值和应用前景.     

支持事务机制的Web服务组合QoS属性预测方法

该文提出了一种支持事务机制的Web服务组合QoS属性预测方法。分析了事务异常处理策略及其对组合服务执行流程的影响,定义了支持事务机制的组合服务描述模型,并基于此模型提出了组合服务QoS属性预测算法。实验证明该文方法在对具有事务机制的组合服务进行预测时,准确度优于已有的工作流预测方法,具有较好的可行性和有效性。     

Research on user-aware QoS based Web services composition

To improve user experience of composite Web services, a user-aware quality of service (QoS) based Web services composition model is proposed. Under such model, a Web services selection method based on quantum genetic algorithm is proposed. This algorithm uses quantum bit encoding, dynamic step-length quantum gate angle adjustment, neighborhood service search and dynamic punishment strategy to expand search scope and speed up convergence. Simulation experiment shows that this algorithm is more efficient than other existing algorithms in Web services selection.     

Network selection based on multiple attribute decision making and group decision making for heterogeneous wireless networks

One of the key issues for radio resources management is network selection strategy in heterogeneous scenarios.In order to provide ubiquitous service,the paper puts forward a network selection algorithm based on multiple attribute decision making(MADM) and group decision making(GDM).Firstly,the proposed algorithm acquires attribute weights’ vectors of the subjective and objective decision makers based on MADM,and then the two attribute weights’ vectors are synthesized to be a new attribute weights’ vector by using GDM.Considering that the results of GDM should be reasonable and convincible,the criterion of consistency is adopted for judging the compatibility of group judgments.More specifically,the algorithm takes into account not only objective attributes of networks but also the preference of subscribers and traffic class.Hence it guarantees that the subscribers can not select the networks with poor performance depending on their preference.The simulation results show that the proposed algorithm can effectively reduce the handoff number and provide subscribers with satisfactory quality of service(QoS).     

基于结构化噪声矩阵补全的Web服务QoS预测

随着面向服务计算技术的快速发展,越来越多具有相同或相似功能的Web服务被部署在网络上。用户进行服务选择之前,通常需要根据历史调用信息对未使用过的服务QoS进行预测。由于历史调用信息收集过程缺乏有效的监督和约束机制,所采样的QoS信息往往容易受到结构化噪声污染,从而导致现有方法预测性能急剧下降。为了克服这个困难,通过将Web服务QoS预测问题建模为L2,1范数正则化矩阵补全问题,提出了一类基于结构化噪声矩阵补全的Web服务QoS预测方法。真实数据集上的实验结果表明,该方法不仅能精确地辨识出QoS采样矩阵中噪声行所在位置,而且能对缺失Web服务QoS进行有效预测。