SOA中服务质量建模、预测及保障
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摘要
面向服务的体系结构(Service-Oriented Architecture, SOA)作为新一代软件架构,顺应了应用集成、电子商务、电子政务等领域敏捷应对环境变化的需求,在学术研究及企业实践中得到了日益广泛的应用。在SOA框架中,分布于不同功能组织的基于标准接口、可互操作的服务能够被迅速地组合与重用,为分布、异构环境下的资源共享及应用集成提供了技术上的有效支持。
Web服务以其自治、松耦合、以及良好的互操作性,成为当前SOA的重要实现标准之一。伴随着SOA的应用普及,Internet上涌现出大量功能相同、相似或重叠的Web服务。因此,服务的非功能属性,特别是服务质量(Quality of Service, QoS),成为服务组合及服务选择的关键标准。鉴于分布式环境的复杂多变,为保证服务的QoS满足用户需求,需要将QoS管理穿于服务的整个生命周期。其中,组合服务的设计时QoS预测,基于QoS的服务选择,运行时的QoS监控及保障是QoS管理涉及的重要研究课题。
建立合适的Web服务QoS数学模型是开展相关研究课题的基础与前提。现有研究工作通常利用固定单值或概率分布描述QoS属性,且针对不同的QoS指标分别独立建模。利用概率分布函数描述服务QoS在一定程度上反映了QoS的动态特性,但是现有方法究其本质均可归结于静态建模的范畴。现实中,服务的QoS通常随时间而变化,且在时间要素的作用下,不同的QOS属性之间存在一定的相关性。现有QoS模型忽视了时间要素对服务QoS带来的重大影响,直接导致了建模精确度的缺失,并继而影响到预测、服务选择等后续研究课题的实施效果。因此,弥补既有研究的不足,揭示服务QoS的时间相关性、建立动态QoS模型并展开相关研究具备理论及现实意义。
另外,在组合服务运行过程中,服务发现及服务替换机制是应对成员服务失效或QOS水平下降等不利因素的关键举措。由于现实中通常难以找到完全符合需求的可替代服务,基于适配的服务替换成为研究热点之一。尤其是对于会话型服务,如何迅速获取服务接口层面及会话协议层面的适配方案,以敏捷应对服务替换的需求,近年来引起了学术界的诸多关注。
本文在分析现有QoS研究成果的基础上,围绕QOS建模、组合服务QoS预测以及QoS的运行时保障三个关键问题展开讨论。具体研究内容包括：
1.分析了对Web服务QoS进行动态建模的必要性。针对现实中常见的服务部署环境要素呈现周期时变性的现象,提出了一种服务QOS周期模型定义；针对采用灵活QoS控制机制的复杂服务系统,提出了一种服务生存性模型定义。
2.提出了一种服务QoS动态建模方法。该方法基于混合高斯隐马尔科夫模型。通过对服务运行日志的分析得到QOS观测向量序列,利用隐马尔科夫经典算法获取服务QoS随时间而变化的合理分割,并以此为依据,建立服务QoS周期模型以及生存性模型。
3.研究了基于QoS周期模型的组合服务QoS预测算法。针对由顺序、同步并行、异步并行、选择、循环等模式构成的组合服务,从组合服务周期长度预测,单.个调用时问点QoS预测以及组合服务QoS周期模式建立三个方面提出了相应解决方案。并基十服务响应时间与QOS周期长度之间的两种约束关系,分别提出了分段聚合和单向约简两种算法。
4.研究组合服务运行时的QoS保障问题。具体而言,针对运行时的会话型成员服务失效或QoS下降等现象,提出了一种基于适配的服务替换方案自动生成方法。该方法基于图规划技术,首先将服务适配问题映射为图规划问题,继而通过生成层次规划图以及后向链接搜索策略提取有效的适配方案,从而解决会话型服务接口不相容以及会话协议不相容这两类问题。
Service-Oriented Architecture (SOA), as the new generation software archi-tecture, serves the purpose of responding quickly to the changing environmen-tal conditions in multiple fields, such as system integration. E-Commerce and E-Administration. Therefore, SOA is gaining increasing attention in both academic and practice areas. In SOA, services with standard interfaces provided by different organizations can be rapidly composed and reused, effectively supporting resource sharing and application integration under a distributed and heterogeneous environ-ment.
Autonomous.loosely coupled and highly interoperable in nature. web services become the preferred standards-based way to realize SOA. With the widespread application of SOA. a great many web services with the same, similar or overlapping functionalities are available on Internet. Consequently, the non-functional feature of a service, in particular Quality of Service (QoS), becomes the key criterion for service selection and composition. Due to the complex and dynamic nature of the distributed environment, the management of QoS should be incorporated into the entire lifecycle of a service in order to satisfy the requirements of service customers. Several key issues of QoS management, including QoS prediction, QoS-based service selection, QoS monitoring and QoS assurance, are intensively under investigation.
To build an appropriate QoS model lays the groundwork for further studies. Existing solutions model service QoSs either as deterministic values or probabilistic distributions. And different QoS metrics are modeled independently. Although probability-based QoS models reflect certain dynamic features of QoS, all these work overlooked an important aspect in QoS modeling, time. Most QoS metrics, such as response time, availability, are time dependent, e.g., they can change with time dramatically. Moreover, different QoS metrics always correlate when considering the influence of time. Existing works underestimate the importance of time on QoS, leading to the lose of accuracy on QoS modeling. Therefore, it is highly desirable to establish QoS models that, reveal the timing relationship of QoS and to carry out the corresponding QoS researches based on the new QoS model.
Another attractive issue is service substitution, which is an effective way to cope with service failure or QoS degradation. Since it is not realistic to find totally equiva-lent substitutive service in practice, the mechanism of adaptive service substitution gains much attention recently. Specifically, the adaptive substitution method for conversational services, i.e., how to rapidly develop adaptors to resolve mismatches both at interface level and protocol level, has become the focus of intense research.
In this thesis, we mainly concentrate on QoS modeling, QoS prediction and QoS assurance. The main contributions include:
1. We demonstrate the necessity of dynamic QoS modeling for web services. A Cycle QoS Model(CQM) is proposed to capture the periodically changing QoS patterns. We also define a service survivability model for complex service systems that adopt agile QoS management mechanisms.
2. We propose a dynamic QoS modeling method for web services based on Hidden Markov Model(HMM). A QoS observation vector sequence is acquired by analyzing the service log. Then we apply traditional HMM algorithms to get the reasonable time segmentation for the changing QoS, and based on which, we can set up the Cycle QoS Model or service survivability model eventually.
3. We investigate the QoS prediction algorithms for composite services based on the proposed CQM. The composition patterns we focus on include sequential, synchronized parallel, asynchronized parallel, conditional and loop patterns. Three problems can be solved:(1)determining the time cycle of a composite service;(2) estimating the QoS of the composite service if it is invoked at a certain time point;(3)obtaining the CQM of the composite service. Specifically, according to the two kinds of constraint relationship between the service response time and the length of QoS cycle, two QoS prediction algorithms are proposed respectively. including the segmental QoS aggregation algorithm and the one-way QoS reduction algorithm.
4. We address the run-time QoS assurance mechanisms. In detail, we propose an automatic approach to generate adaptors to support substitution for conversational services. The approach is based on graph planning techniques in which service sub-stitution is encoded as a graph planning problem. Then a solution can be achieved by constructing a leveled graph followed by a backward chaining graph exploring. The interface and protocol incompatibility between the conversational services can be solved consequently.
Web服务以其自治、松耦合、以及良好的互操作性,成为当前SOA的重要实现标准之一。伴随着SOA的应用普及,Internet上涌现出大量功能相同、相似或重叠的Web服务。因此,服务的非功能属性,特别是服务质量(Quality of Service, QoS),成为服务组合及服务选择的关键标准。鉴于分布式环境的复杂多变,为保证服务的QoS满足用户需求,需要将QoS管理穿于服务的整个生命周期。其中,组合服务的设计时QoS预测,基于QoS的服务选择,运行时的QoS监控及保障是QoS管理涉及的重要研究课题。
建立合适的Web服务QoS数学模型是开展相关研究课题的基础与前提。现有研究工作通常利用固定单值或概率分布描述QoS属性,且针对不同的QoS指标分别独立建模。利用概率分布函数描述服务QoS在一定程度上反映了QoS的动态特性,但是现有方法究其本质均可归结于静态建模的范畴。现实中,服务的QoS通常随时间而变化,且在时间要素的作用下,不同的QOS属性之间存在一定的相关性。现有QoS模型忽视了时间要素对服务QoS带来的重大影响,直接导致了建模精确度的缺失,并继而影响到预测、服务选择等后续研究课题的实施效果。因此,弥补既有研究的不足,揭示服务QoS的时间相关性、建立动态QoS模型并展开相关研究具备理论及现实意义。
另外,在组合服务运行过程中,服务发现及服务替换机制是应对成员服务失效或QOS水平下降等不利因素的关键举措。由于现实中通常难以找到完全符合需求的可替代服务,基于适配的服务替换成为研究热点之一。尤其是对于会话型服务,如何迅速获取服务接口层面及会话协议层面的适配方案,以敏捷应对服务替换的需求,近年来引起了学术界的诸多关注。
本文在分析现有QoS研究成果的基础上,围绕QOS建模、组合服务QoS预测以及QoS的运行时保障三个关键问题展开讨论。具体研究内容包括：
1.分析了对Web服务QoS进行动态建模的必要性。针对现实中常见的服务部署环境要素呈现周期时变性的现象,提出了一种服务QOS周期模型定义；针对采用灵活QoS控制机制的复杂服务系统,提出了一种服务生存性模型定义。
2.提出了一种服务QoS动态建模方法。该方法基于混合高斯隐马尔科夫模型。通过对服务运行日志的分析得到QOS观测向量序列,利用隐马尔科夫经典算法获取服务QoS随时间而变化的合理分割,并以此为依据,建立服务QoS周期模型以及生存性模型。
3.研究了基于QoS周期模型的组合服务QoS预测算法。针对由顺序、同步并行、异步并行、选择、循环等模式构成的组合服务,从组合服务周期长度预测,单.个调用时问点QoS预测以及组合服务QoS周期模式建立三个方面提出了相应解决方案。并基十服务响应时间与QOS周期长度之间的两种约束关系,分别提出了分段聚合和单向约简两种算法。
4.研究组合服务运行时的QoS保障问题。具体而言,针对运行时的会话型成员服务失效或QoS下降等现象,提出了一种基于适配的服务替换方案自动生成方法。该方法基于图规划技术,首先将服务适配问题映射为图规划问题,继而通过生成层次规划图以及后向链接搜索策略提取有效的适配方案,从而解决会话型服务接口不相容以及会话协议不相容这两类问题。
Service-Oriented Architecture (SOA), as the new generation software archi-tecture, serves the purpose of responding quickly to the changing environmen-tal conditions in multiple fields, such as system integration. E-Commerce and E-Administration. Therefore, SOA is gaining increasing attention in both academic and practice areas. In SOA, services with standard interfaces provided by different organizations can be rapidly composed and reused, effectively supporting resource sharing and application integration under a distributed and heterogeneous environ-ment.
Autonomous.loosely coupled and highly interoperable in nature. web services become the preferred standards-based way to realize SOA. With the widespread application of SOA. a great many web services with the same, similar or overlapping functionalities are available on Internet. Consequently, the non-functional feature of a service, in particular Quality of Service (QoS), becomes the key criterion for service selection and composition. Due to the complex and dynamic nature of the distributed environment, the management of QoS should be incorporated into the entire lifecycle of a service in order to satisfy the requirements of service customers. Several key issues of QoS management, including QoS prediction, QoS-based service selection, QoS monitoring and QoS assurance, are intensively under investigation.
To build an appropriate QoS model lays the groundwork for further studies. Existing solutions model service QoSs either as deterministic values or probabilistic distributions. And different QoS metrics are modeled independently. Although probability-based QoS models reflect certain dynamic features of QoS, all these work overlooked an important aspect in QoS modeling, time. Most QoS metrics, such as response time, availability, are time dependent, e.g., they can change with time dramatically. Moreover, different QoS metrics always correlate when considering the influence of time. Existing works underestimate the importance of time on QoS, leading to the lose of accuracy on QoS modeling. Therefore, it is highly desirable to establish QoS models that, reveal the timing relationship of QoS and to carry out the corresponding QoS researches based on the new QoS model.
Another attractive issue is service substitution, which is an effective way to cope with service failure or QoS degradation. Since it is not realistic to find totally equiva-lent substitutive service in practice, the mechanism of adaptive service substitution gains much attention recently. Specifically, the adaptive substitution method for conversational services, i.e., how to rapidly develop adaptors to resolve mismatches both at interface level and protocol level, has become the focus of intense research.
In this thesis, we mainly concentrate on QoS modeling, QoS prediction and QoS assurance. The main contributions include:
1. We demonstrate the necessity of dynamic QoS modeling for web services. A Cycle QoS Model(CQM) is proposed to capture the periodically changing QoS patterns. We also define a service survivability model for complex service systems that adopt agile QoS management mechanisms.
2. We propose a dynamic QoS modeling method for web services based on Hidden Markov Model(HMM). A QoS observation vector sequence is acquired by analyzing the service log. Then we apply traditional HMM algorithms to get the reasonable time segmentation for the changing QoS, and based on which, we can set up the Cycle QoS Model or service survivability model eventually.
3. We investigate the QoS prediction algorithms for composite services based on the proposed CQM. The composition patterns we focus on include sequential, synchronized parallel, asynchronized parallel, conditional and loop patterns. Three problems can be solved:(1)determining the time cycle of a composite service;(2) estimating the QoS of the composite service if it is invoked at a certain time point;(3)obtaining the CQM of the composite service. Specifically, according to the two kinds of constraint relationship between the service response time and the length of QoS cycle, two QoS prediction algorithms are proposed respectively. including the segmental QoS aggregation algorithm and the one-way QoS reduction algorithm.
4. We address the run-time QoS assurance mechanisms. In detail, we propose an automatic approach to generate adaptors to support substitution for conversational services. The approach is based on graph planning techniques in which service sub-stitution is encoded as a graph planning problem. Then a solution can be achieved by constructing a leveled graph followed by a backward chaining graph exploring. The interface and protocol incompatibility between the conversational services can be solved consequently.
引文
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