一种基于组合赋权法的Web服务选择策略*

针对Web服务选择中服务请求偏好权重表达的模糊性及服务质量(QoS)属性值间存在的相互制约关系等问题,提出一种基于组合赋权法的Web服务选择策略。首先利用模糊层次分析法(FAHP)和主成分分析法(PCA)分别计算主观QoS权重和客观QoS权重;然后综合主、客观QoS权重利用组合赋权法(CWA)计算服务请求的综合QoS权重;最后提出一种综合评价函数,以保障所选择的服务在满足服务请求偏好的基础上,能更准确地反映候选Web服务总体QoS水平。实例分析表明该方法是有效的。     

基于二维QoS模型的Web服务组合

在实际应用中,单个Web服务通常无法满足复杂应用的需求,如何组合已有的服务,从而提供更强大更完整的商业功能已成为此领域的研究热点。然而现行的SOA架构中,Web服务组合方法中很少考虑Web服务质量（QoS）问题,或者对Qos考虑得不够全面,这样,组合出的服务不能确保能够满足用户的QoS需求。针对这一问题,提出了Web服务的二维QoS模型,并使用了改进的UDDI规范,在此基础上给出了基于QoS的Web服务组合的有色Petri网组合策略。在满足用户组合服务的功能需求的同时,也满足了用户对服务质量QoS的需求,实现了需求服务的优化。     

一种高效的服务组合优化算法

随着功能性属性相同而非功能性属性各异的Web服务的大量涌现,如何在服务组合业务流程中为各个任务选择相应的组件服务以达到组合服务的QoS(quality of service)最大化,并在此基础上满足不同用户的需求,已成为了国内外研究的热点.由于该问题的复杂性(NP-hard),目前存在的大多数方法都并不十分适合需要相对精确、实时决策的Web服务组合系统.因此,本文提出了一种基于凸包构建的组合服务优化算法(CM-HEU)用以解决QoS感知的服务组合优化问题.CM-HEU首先通过对组合服务中的每组任务进行凸包构建,以减少搜索空间.然后通过对初始解向量的多次升级和一次降级操作以达到全局优化的目标.实验表明:相对于现阶段存在的一些主流方法,CM-HEU不仅能得到一个比较理想的结果,并且具有良好的效率.     

基于有向层次图的Web服务自动组合方法

为解决多输入/输出的Web服务自动组合问题,提出了基于有向层次图的Web服务自动组合方法,主要步骤如下：1）根据用户请求的输入/输出参数集生成有向层次图;2）在有向层次图中构造完全规约图;3）在完全规约图中计算每一顶点的所有可达路径;4）为用户请求选择最优路径,并转化为Web服务组合序列。该方法能够求得最短步数内的所有Web服务组合序列,根据Web服务的服务质量(QoS)获得最优的组合序列,从而满足多输入/输出的用户请求。与基于图的Web服务组合方法相比,减少了搜索空间,适用于大规模的Web服务库。     

Web服务计算组合流程QoS验证

在满足功能需求的前提下,Web服务能否赢得市场, 主要取决于其服务质量(Quality of Services,QoS)。采用概率模型检验的方法判断Web服务计算组合流程的服务质量是否满足系统质量需求。依据用户访问Web服务产生的访问日志,采用聚类的方法,构建面向用户群组的Web服务流程的使用行为QoS模型。采用QoS扩展的状态图描述Web服务流程的QoS需求。然后,利用概率模型验证工具PRISM判断Web服务流程的QoS是否满足系统质量需求。验证面向用户群组的Web服务流程的使用行为质量模型是否满足系统质量需求,为服务流程结构的调整提供了依据。     

面向客户视角的QoS集成与组合服务优化

研究Web服务组合网上服务质量(QoS)的评价指标以及组合服务QoS计算模型,建立一种面向客户视角的网下服务质量评价体 系,包括服务费用合理度、服务与描述符合度及服务满意度。以服务费用为约束条件,提出一种的面向客户视角的Web服务QoS集成与组合服务优化模型。分析结果表明,与基于QoS的组合服务选取模型相比,该模型增加了服务质量指标,即网下服务(商品)的质量,更能满足客户需求。     

服务组合中面向端到端用户QoS需求的QoS聚合机制研究

服务组合基于多种基本的组合结构,组合多个已有的服务来满足用户的功能性和非功能性(即QoS)需求。通常,用户的需求直接是端到端的需求,而服务描述本身具有自身的QoS描述。由于所处的层次不同,端到端的QoS需求描述和单个服务的QoS描述存在一定的语义鸿沟。基于层次化本体模型建立QoS本体模型,建立了用户QoS和服务QoS之间的映射关系。并针对基本的服务组合结构,研究了异构QoS本体环境下服务的QoS聚合机制。基于基本组合结构的QoS聚合,提出了完整的服务组合中的QoS聚合算法和QoS转换算法,以满足端到端的QoS需求。     

随机QoS 感知的可靠Web 服务组合

在面向服务的环境下,单个Web 服务往往不能满足用户的要求,这时就需将已有的单个Web 服务进行组合,以便产生满足用户需求的、增值的组合服务.已有的服务组合方法都很少考虑Web 服务的随机性和Internet 环境的动态性,从而在服务选择过程中产生的规划都是静态规划,结果导致在服务组合时都以较大概率出现组合失败.针对上述问题,提出了Web 服务各随机QoS 指标的度量方法和自适应QoS 管理体系结构,并利用随机型离散事件系统唯一的动态控制方法——马尔可夫决策过程(MDP),设计出随机QoS 感知的可靠Web 服务组合算法.实验结果表明,考虑随机性的QoS 度量方法和QoS 管理体系结构,以及平衡了“风险”与“报酬”的MDP 有效地提高了服务组合成功率.     

基于可信QoS的路径查找及负载均衡策略研究

Web服务是云计算中资源调用的有效方式。单一Web服务功能往往有限,只能完成特定任务。服务组合则可以将多种Web服务形成有效的调用序列,实现更为强大的功能。服务发布量以及服务请求量的迅速激增带来了新的安全问题。首先,现有的服务组合方案均以服务质量(QoS)为依据进行Web服务选择,但服务质量通常由服务发布者提供,存在服务发布者发布虚假QoS值诱骗用户的欺诈现象;其次,传统的服务组合方案只生成一条最优路径,当恶意请求持续访问时,会造成某服务节点瘫痪,甚至整个服务组合系统失效。因此,针对服务质量恶意欺诈的问题,文章提出一种可信的QoS计算模型,根据Web服务发布者的信用综合评估服务质量;针对单一最优路径无法满足大量请求的问题,文章提出一种路径发现和负载均衡的多路径方法。仿真结果表明,文章提出的方法不仅能提高服务组合的成功率,满足用户的需求,而且能找到更多的服务组合方案执行。     

基于多目标粒子群优化算法的Web服务组合

基于服务质量(QoS)的Web服务组合是一个非线性、多目标优化求解问题,属于NP难问题.提出一种多目标粒子群优化算法来求解基于QoS的Web服务组合问题,在Web服务组合模型中考虑了服务执行代价、时间、可用性等五方面的因素.针对基于QoS的Web服务组合特点,借鉴运动学速度分解原理对粒子每维的速度进行相应分解,采用多目标指导粒子的飞行;基于Pareto支配关系来更新粒子的个体极值,采用精英归档技术维持种群多样性,粒子的全局极值由外部档案库中的非劣最优解提供;针对粒子群易陷入局部最优问题,采用了变异策略来改善.与基于遗传算法的Web服务组合算法相比,基于多目标粒子群优化的Web服务组合算法可以快速收敛,并获得综合QoS较好的解.     

Functionality Aware Dynamic Composition of Web Services

The composition of the web service is a common technique to attain the best results of complex web tasks. The selection of appropriate web services, linking those services in the action flow and attaining the actual functionality of the task are the important factors to be considered. Even though different frameworks and methods have been proposed to dynamically compose web services, each method has its advantage and disadvantage over the other. Most of the methods give much importance to the Quality of Service (QoS) but fail to achieve the actual functionality after composition. This paper proposes a functionality-oriented composition technique for composing web services. Moreover, this method helps reach the extreme functionality of each web service in the composition towards customer satisfaction. Apart from considering the overall QoS of every single service, the non-functional parameters associated with these services are also considered for achieving the expected functionality. Each of these non-functional parameters has a vital role in the functional performance of the web service. The web services that satisfy the non-functional requirements are chosen to form the composition to attain the best performance. The list of services in the proposed composition method is different from the conventional one, which is composed based on the overall QoS. The non-functional parametric values, the QoS of each web service and the overall QoS after composition are evaluated for the proposed method and experimentally analyzed to prove their advantage over the others.     

Quality-of-service oriented web service composition algorithm and planning architecture

In the next few decades, it is expected that web services will proliferate, many web services will offer the same services, and the clients will demand more value added and informative services rather than those offered by single, isolated web services. As the result, the problem of synthesizing web services of high quality will be raised as a prominent issue. The clients will face the trouble of choosing or creating composition plans, among numerous possible plans, that satisfy their quality-of-service (QoS) requirements. Typical QoS properties associated with a web service are the execution cost and time, availability, successful execution rate, reputation, and usage frequency. In engineering perspective, generating the composition plan that fulfills a client’s QoS requirement is a time-consuming optimization problem. To resolve the problem in a timely manner, we propose a constraint satisfaction based web service composition algorithm that combines tabu search and simulated annealing meta-heuristics. As an implementation framework of the algorithm, we suggest a QoS-oriented web service composition planning architecture. The architecture maintains expert made composition schemas in a service category and assists the client as pure user to choose the one he/she wants to use. The main modules of the architecture are composition broker and execution plan optimizer. With the aid of the UDDI server, the composition broker discovers candidate outsourced web services for each atomic process of the selected schema and gathers QoS information on the web services. After that, the execution plan optimizer runs the web service composition algorithm in order to generate a QoS-oriented composition plan. The performance of the algorithm was tested in a simulated environment.     

GACRM: A dynamic multi-Attribute decision making approach to large-Scale Web service composition

The problem of QoS-aware Web service composition (QWSC), i.e., how to select from a pool of candidate services to construct a composite service with the best overall QoS performance, is an NP-hard problem. To address a large-scale QWSC problem, a novel method is proposed based on information theory, multi-attribute decision making (MADM) and genetic algorithm. To capture complex judgments, the QWSC problem is formulated into a MADM representation which aims to find acceptable solutions assessed by multiple QoS attributes with varying distributions. To solve the MADM problem for QWSC, each QoS attribute is weighted in both a priori, subjective perspective and a posteriori, information-based perspective based on the discriminative capability of QoS attributes for a dynamic pool of candidate services. Furthermore, to solve the large-scale QWSC problem that conventional MADM methods cannot navigate, we develop a GACRM algorithm by integrating genetic algorithm (GA) with Compromise Ratio Method (CRM). Experiments demonstrate that GACRM obtains nearly the same solution ranking by the CRM but scales much better in terms of computation time for large-scale QWSC problems.     

基于领域本体的可信服务组合

针对现有Web服务组合方法缺乏对服务自身属性信任问题的深入考虑,服务组合过程可信需求无法得到保障,提出了一种基于领域本体的可信Web服务组合方法。将服务的非功能属性分为服务质量、服务信任和服务上下文三个主要方面,并采用本体构建工具Protégé构建原子服务本体,利用推理机FaCT++对原始服务集进行本体推理过滤;引入了融合本体推理过滤的Web服务架构;提出了基于层次任务网络(hierarchical tasknetwork,HTN)规划法的可信服务组合算法。仿真实验表明:与传统的组合方法相比,该方法可有效提高服务组合的效率和成功率。     

基于不确定服务质量感知的云服务组合方法

针对不确定服务质量（QoS）感知的云服务组合优化问题的求解,提出一种不定长时间序列（ULST）模型和锦标赛策略的改进遗传算法（T-GA）。首先,基于用户对服务不同时间段的访问规律,将服务质量的长期变化构建为不定长时间序列模型,该模型能够准确地描述一段时间内用户对服务的真实QoS访问记录。其次,提出一种基于不确定QoS模型的改进遗传算法,该算法采用锦标赛选择策略代替基本遗传算法中的轮盘赌选择策略。最后,在真实数据上进行了大量实验,所提的不定长时间序列模型能够有效地解决不确定QoS感知云服务组合问题,而锦标赛策略的改进遗传算法在寻优结果和稳定性方面均优于基于精英选择策略的遗传算法（E-GA）算法,且运行速度提高近1倍,是可行、高效且稳定的算法。     

Neighborhood Search Based Improved Bat Algorithm for Web Service Composition

Web services are provided as reusable software components in the services-oriented architecture. More complicated composite services can be combined from these components to satisfy the user requirements represented as a workflow with specified Quality of Service (QoS) limitations. The workflow consists of tasks where many services can be considered for each task. Searching for optimal services combination and optimizing the overall QoS limitations is a Non-deterministic Polynomial (NP)-hard problem. This work focuses on the Web Service Composition (WSC) problem and proposes a new service composition algorithm based on the micro-bats behavior while hunting the prey. The proposed algorithm determines the optimal combination of the web services to satisfy the complex user needs. It also addresses the Bat Algorithm (BA) shortcomings, such as the tradeoff among exploration and exploitation searching mechanisms, local optima, and convergence rate. The proposed enhancement includes a developed cooperative and adaptive population initialization mechanism. An elitist mechanism is utilized to address the BA convergence rate. The tradeoff between exploration and exploitation is handled through a neighborhood search mechanism. Several benchmark datasets are selected to evaluate the proposed bat algorithm’s performance. The simulation results are estimated using the average fitness value, the standard deviation of the fitness value, and an average of the execution time and compared with four bat-inspired algorithms. It is observed from the simulation results that introduced enhancement obtains significant results.     

Networked correlation-aware manufacturing service supply chain optimization using an extended artificial bee colony algorithm

Manufacturing service supply chain (MSSC) optimization has been intensively studied to find an optimal service composition solution with the best quality of service (QoS) value. However, traditional MSSC optimization methods usually assume that candidate services are independent of one another. Therefore, potentially better MSSC solutions may have been neglected by not considering the positive influence of correlations between services on the QoS value. This study proposes a novel networked correlation-aware manufacturing service composition (NCMSC) mathematical model to characterize the influence of vertical and horizontal correlations between services on the QoS value of MSSC solution. To solve the NCMSC model, an extended artificial bee colony (ABC) algorithm is proposed to find a near-optimal solution with the best QoS value. The specific improvements to the original ABC algorithm include the following: (1) a new matrix-based encoding scheme is proposed to describe the MSSC solution in which each column contains a vertical composite structure and collaborative services for each subtask; (2) the migration operator of a biogeography-based optimization algorithm is combined with the original ABC algorithm to address the discrete MSSC optimization problem and improve the performance of the original ABC algorithm. The results of the experiments illustrate the importance of networked correlations between services, better practicality, effectiveness, and efficiency of the extended ABC algorithm in solving the optimization problem of MSSC.