动态Web服务组合中基于QoS的服务选择研究
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摘要
Web服务吸收了分布式计算、Grid计算和XML等各种技术的优点,具有高度的互操作性、跨平台性和松耦合的特点,成为WWW发展的主要趋势。然而,单个Web服务的功能有限,只有通过组合单个Web服务才能实现服务重用和服务增值。而服务质量(QoS)是组合Web服务的生命。随着Web服务的发展,各行业和领域内服务功能不断细分和深化,用户对服务质量也有更高更多的需求。实现服务质量驱动下的Web服务组合是Web服务组合走向实用的必要条件。
论文以动态Web服务组合应用环境为背景,通过多种数学模型和工具研究了Web服务的QoS模型和基于QoS的服务选择问题,主要的研究成果包括：
1)提出了一种多侧面、层次化、统一的综合QoS模型。与现有的Web服务QoS模型相比,本文所提出模型的定义结构和属性类型定义从更多方面描述说明Web服务QoS属性,使得QoS属性定义更加清晰全面；统一的定义结构为Web服务QoS属性的可扩展性支持提供了可能。
2)在信息完备情况下,提出了一种基于模糊集理论支持混合QoS属性综合评价的Web服务选择方法。能够支持对模糊表达QoS信息和确定表达QoS信息的统一处理,包括相应的确定化和标准化方法。采用主客观结合方法确定QoS属性综合权重,并引入灰色关联度理论,通过定义隶属度函数作为贴近度函数衡量候选服务的相对优劣。本文的方法可以支持多种不同类型的QoS属性,而且概念清晰、计算步骤较为简单、易于编程实现。
3)在信息不完备情况下,提出了一种基于粗糙集理论的QoS驱动Web服务选择方法。能够支持数据补全、离散化、服务预筛选和服务排序,从而可以在Web服务QoS数据缺失、权重未知的情况下,利用粗集相似度和权重进行基于QoS的Web服务选择。
4)提出了一种基于扰动变异更新的改进粒子群算法,并将其应用于全局QoS约束的Web服务选择优化。通过借鉴遗传算法的优势,引入外部精英种群,利用扰动和变异更新机制保持粒子多样性,采用聚类机制保持外部精英种群的合适规模,通过比例分配来更新局部和全局极值,在保持快速收敛特性的同时,改善了PSO容易陷入局部极值的缺陷。通过实验验证了该算法对QoS驱动的Web服务选择过程的优化效果。
Web Service extracts the advantage of distributed computation, Grid computation and XML, and solves the problems of heterogeneous distributed computation and data reuse. Web Service has the characters of inter-operation, multi-platform and loose coupling, so it becomes the leading development trend of WWW. But single Web Service has limited function, service reuse and sevice increment can be obtained only through combining multiple Web Services. In the environment of distributed, heterogeneous and multi-autonomous-fields Wide Area Network which is represented by Internet, highly dynamic network environment and changeful user requirement desire that Web Service Composition can cast off the static componsition mode, rectify and optimize composite web services in good time so that provide efficient, cheap and dynamic service composition.
Quality of Service is the life of composite web services. As the development of Web Service, service functionality continually subdivides and deepens, and users have higher and various demands of QoS.The capability of realizing QoS-based web service composition with is the necessary condition that Web Service Composition can has practicability.
In the context of dynamic Web services application environment, the dissertation emploies variety of mathematical models and tools to study the QoS model of Web Service, and the problem of Qos-based service selection, The main points of the dissertation are described as follows:
1) The dissertation proposes a multi-lateral, hierarchical, unified General QoS model for web service. Compared with existing web service QoS model,the structure and attribute definitions of our model make more clear and comprehensive for QoS attribute definition. The Unified definition of the structure supports the scalability for QoS attribute stochastically.
2) With complete information, It presents a method for data normalization, which can process the hybrid QoS criterions judgement matrix. The dissertation uses an improved flexible combination of subjective and objective methods to determine the weights of QoS attribute, and emploies gray correlation degree of the ideal point method to sort web service. Compared with other similar researchs, the method has a certain flexibility and can process the weight with only part of information data. System parameters can be set up to regulate the size of the difference between the weight of QoS attributes. The use of gray correlation degree affiliation ways can reflect the different user needs more comprehensibly. Compared with other similar researchs, our method can support more types of QoS attributes. It also has a clear concept, relatively simple calculation steps, and easy to program implementation.
3) With incomplete information, the dissertation proposes a method for QoS-driven web service selection. It can support recruiting default in data, data discretization, web service filtration. So, we can use rough set similarity and weight to select web service with incomplete QoS data and unknown QoS attribute weight.
4) It presents an improved particle swarm optimization algorithm based on disturbance mutation update, and emploies the algorithm to optimiz the web service selection under global QoS constraints. It combines advantages of wide-ranged exploration with mutation operation,to maintain diversity of new found non-dominated solutions via proportional distribution in the external repository, and deep exploitations of PSO to enhance the solution searching abilities of particles. Introduction of all the refined method allow the improved PSO algorithm to maintain the capbility of fast convergence and prevent solutions from falling into the local optimal.
论文以动态Web服务组合应用环境为背景,通过多种数学模型和工具研究了Web服务的QoS模型和基于QoS的服务选择问题,主要的研究成果包括：
1)提出了一种多侧面、层次化、统一的综合QoS模型。与现有的Web服务QoS模型相比,本文所提出模型的定义结构和属性类型定义从更多方面描述说明Web服务QoS属性,使得QoS属性定义更加清晰全面；统一的定义结构为Web服务QoS属性的可扩展性支持提供了可能。
2)在信息完备情况下,提出了一种基于模糊集理论支持混合QoS属性综合评价的Web服务选择方法。能够支持对模糊表达QoS信息和确定表达QoS信息的统一处理,包括相应的确定化和标准化方法。采用主客观结合方法确定QoS属性综合权重,并引入灰色关联度理论,通过定义隶属度函数作为贴近度函数衡量候选服务的相对优劣。本文的方法可以支持多种不同类型的QoS属性,而且概念清晰、计算步骤较为简单、易于编程实现。
3)在信息不完备情况下,提出了一种基于粗糙集理论的QoS驱动Web服务选择方法。能够支持数据补全、离散化、服务预筛选和服务排序,从而可以在Web服务QoS数据缺失、权重未知的情况下,利用粗集相似度和权重进行基于QoS的Web服务选择。
4)提出了一种基于扰动变异更新的改进粒子群算法,并将其应用于全局QoS约束的Web服务选择优化。通过借鉴遗传算法的优势,引入外部精英种群,利用扰动和变异更新机制保持粒子多样性,采用聚类机制保持外部精英种群的合适规模,通过比例分配来更新局部和全局极值,在保持快速收敛特性的同时,改善了PSO容易陷入局部极值的缺陷。通过实验验证了该算法对QoS驱动的Web服务选择过程的优化效果。
Web Service extracts the advantage of distributed computation, Grid computation and XML, and solves the problems of heterogeneous distributed computation and data reuse. Web Service has the characters of inter-operation, multi-platform and loose coupling, so it becomes the leading development trend of WWW. But single Web Service has limited function, service reuse and sevice increment can be obtained only through combining multiple Web Services. In the environment of distributed, heterogeneous and multi-autonomous-fields Wide Area Network which is represented by Internet, highly dynamic network environment and changeful user requirement desire that Web Service Composition can cast off the static componsition mode, rectify and optimize composite web services in good time so that provide efficient, cheap and dynamic service composition.
Quality of Service is the life of composite web services. As the development of Web Service, service functionality continually subdivides and deepens, and users have higher and various demands of QoS.The capability of realizing QoS-based web service composition with is the necessary condition that Web Service Composition can has practicability.
In the context of dynamic Web services application environment, the dissertation emploies variety of mathematical models and tools to study the QoS model of Web Service, and the problem of Qos-based service selection, The main points of the dissertation are described as follows:
1) The dissertation proposes a multi-lateral, hierarchical, unified General QoS model for web service. Compared with existing web service QoS model,the structure and attribute definitions of our model make more clear and comprehensive for QoS attribute definition. The Unified definition of the structure supports the scalability for QoS attribute stochastically.
2) With complete information, It presents a method for data normalization, which can process the hybrid QoS criterions judgement matrix. The dissertation uses an improved flexible combination of subjective and objective methods to determine the weights of QoS attribute, and emploies gray correlation degree of the ideal point method to sort web service. Compared with other similar researchs, the method has a certain flexibility and can process the weight with only part of information data. System parameters can be set up to regulate the size of the difference between the weight of QoS attributes. The use of gray correlation degree affiliation ways can reflect the different user needs more comprehensibly. Compared with other similar researchs, our method can support more types of QoS attributes. It also has a clear concept, relatively simple calculation steps, and easy to program implementation.
3) With incomplete information, the dissertation proposes a method for QoS-driven web service selection. It can support recruiting default in data, data discretization, web service filtration. So, we can use rough set similarity and weight to select web service with incomplete QoS data and unknown QoS attribute weight.
4) It presents an improved particle swarm optimization algorithm based on disturbance mutation update, and emploies the algorithm to optimiz the web service selection under global QoS constraints. It combines advantages of wide-ranged exploration with mutation operation,to maintain diversity of new found non-dominated solutions via proportional distribution in the external repository, and deep exploitations of PSO to enhance the solution searching abilities of particles. Introduction of all the refined method allow the improved PSO algorithm to maintain the capbility of fast convergence and prevent solutions from falling into the local optimal.
引文
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