动态服务组合中的若干关键技术研究
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摘要
随着网络技术的不断发展,动态服务组合技术逐渐成为当前的一大研究热点。动态服务组合技术以语义网为基础,要求网络具有语义功能,能够动态地发现、选择和组合服务。而目前增强语义的研究多集中在本体论方面,如对于领域知识建立相应的领域本体,对Web服务建立相应的服务本体等。因此“本体”技术的研究对于服务组合技术的研究而言至关重要。
另外,个性化的要求使得服务组合过程越来越重视用户的需求,提供满足用户个性化体验的服务越来越成为服务提供者努力的目标。而要在服务组合过程中组合出更具个性化、令用户满意的服务,就必须考虑用户的偏好。
本文针对以上两个问题展开研究工作,取得了以下研究成果:
1)提出一种基于属性语义关联的服务组合方法,该方法转换服务的输入、输出参数为服务的相关属性,建立属性语义关联规则进行服务组合,可直接应用推理引擎在本体之上进行推理,不需通过复杂的机制进行不同服务接口间的协调、统一,提高了服务组合的效率和成功率,属于轻量级的服务组合方法。同时建立的领域服务本体,能根据该本体的领域分类概念有效组织服务,不仅能区分不同服务间的功能,还能缩小服务选择时的搜索范围。
2)为使偏好描述适用于动态服务组合,提出一种属性分解的偏好本体表示方法PODDA。该方法增加了偏好描述的语义及语义关联,并把用户对服务的偏好分解为多个子偏好集合或属性偏好集合,对应本体的建立可从领域本体的概念层次关系中提取服务的子偏好集合,从概念间的关联度提取服务的属性偏好集合,从而能够充分利用领域本体中已存在的资源,且能更深入地表示出用户在多重约束下的偏好,使建立的偏好本体更合理和完整。为验证PODDA的有效性与合理性,建立了一个面向旅游领域的偏好本体对其进行了验证。
3)在以上偏好研究的基础上,对一类具有特殊性质——“边际效用递减”性质服务的推荐问题进行了研究。该研究借鉴经济学中的消费者行为理论,运用偏好、边际效用等方面的原理,对该类性质的单一服务推荐问题以及多个服务的组合服务推荐问题分别进行了研究。该方法可在一定预算前提下使得推荐的组合服务理论上达到效用最大化。
以上提出的个性化服务组合方法,需要在大量服务中选择满足用户需求的服务,这使得服务组合的效率急剧降低,急需要寻找有效的方法进行服务组合优化。为此,该研究提出两种服务选择和组合服务优化算法,一种针对用户QoS属性限制,一种引入用户偏好本体,增加偏好权重,使优化结果更适合用户的个性化需求。
4)提出一种多信息素动态更新的蚁群算法MPDACO,用于进行服务组合优化及适应服务组合优化过程中Web服务的动态性、不稳定性,以及多种QoS属性限制等问题。该算法可以适应服务组合优化过程中发生的服务无效、服务增加以及服务QoS变化等情况,为使算法能较快地收敛于最优解,在实验基础上对算法进行了改进。另外,还提出一种基于蚁群算法原理、启发式发现较好解的算法,用于提高大规模服务选择问题的效率,在较少的迭代次数下即可以获得较优解。
5)为解决引入用户偏好本体后大规模服务的选择问题、服务选择中的信息重用问题以及组合服务的个性化问题,提出一种基于蚁群算法的服务选择方法MSSACO。MSSACO在设立多种信息素的同时,增加相应权重表示用户对服务不同属性的偏好,提出的统一服务选择模型建立在对多种服务组合方法的研究基础之上,能根据服务的历史信息进行个性化的服务选择,并能适应服务组合流程的动态变化以及服务QoS的动态变化等。MSSACO还对蚁群算法的策略进行了改进,能探测优化过程是否正在向局部最优解收敛,并能及时采取措施改变运行方向,从而降低了算法收敛到局部最优解的概率。
With network technology's development, dynamic services composition technology is becoming one focus in research. Based on Semantic Web, Dynamic Service Composition technology requires that the network have semantic function, caple of discovering, selecting and composing services dynamically. Nevertheless, the research on how to enrich the web's semantics emphasizes on ontology, such as building relevant domain ontology for domain knowledge, building service ontology for Web service based on wide applications of SOA, etc. For this reason, the research on "ontology" is of vital importance for services composition technology.
In addition, the requirement for individuation makes users' needs be increasingly regarded in the process of services composition, and providing users with such services that meet their individualized experiences is becoming the objective of the provider. Thus users' preference must be taken into consideration if more individualized and satisfying services are to be composed in the services compositon.
Aiming at solving the above problems, this paper achieves the following results:
1) One services composition method based on attribute semantic association is advanced. This method converts the input and output parameters of the service into its relavant attributes, and builds the rule for attribute semantic association to make services compostion. Being able to reason based on ontology by using engine, and eliminating the complicated mediation between various service interfaces by using complex mechanism, this method promotes the efficiency and feasibility of the services composition, which makes it a light weight services composition method. Additionally, the domain services ontology that has been built can effectively organize services according to the domain classification concept of the ontology, differentiate the functions between various services, and reduce the searching space in services selection.
2) In order to apply preference description to the dynamic services composition, a method named PODDA is put forward. This method adds semantics to the service preference of the user and decomposed this preference into many sub preference sets or attribute preference sets. By abstracting sub preference sets from the relations of the domain ontology's concepts and services' attribute preference sets from the relations between the concepts, the building of the relevant ontology could better utilize the existing resource in domain ontology and express the user's preference under multiple restrictions more profoundly. In the end, a preference ontology on tourism is built to test the feasibility and rationality of PODDA.
3) On the basis of the above research on preference, we make an analysis of a service recommendation issue with a special feature—the law of Diminishing Marginal Utility. By using the theory of consumer's action in economics, and such concepts as preference and utility, as well as the law of Diminishing Marginal Utility, we make respective researches on single service recommendation and on multiple services composition recommendation. This method can theoretically maximize the utility of the composed services on the basis of a certain budget.
In the individualized service composition method mentioned above, we need to select in a great amount of services such ones that meet users' demands, which decreases the efficiency of services composition and make it urgent to find effective method to optimize service composition. Accordingly, this research puts forward two service selection and services composition optimization algorithms: one is for users' QoS attribute constraint, and the other introduces users' preference ontology and adds preference weight to make the optimized result more fit for the users' individualized needs.
4) In order to optimize services composition and to be adapted to the dynamic and instable web services, as well as the limitation of multi-QoS attributes in the process of services composition, we put forward an algorithm named Multi-pheromone and Dynamic Update Ant Colony Optimization Algorithm (MPDACO). This algorithm can fit for the service futility, service increase and QoS change in the process of services composition optimization. In addition, the algorithm is improved to accelerate convergence to optimized result based on experiment. In the end, we also put forward a method that is based on ACO and can find optimized result heuristically, to be applied to increase service selection efficiency when the volume is great.
5) In order to address the challenges from services selecting in great volume, the information reuse in services selection, and the individuation of the services composition, a method of services selection applying Ant Colony Optimization (MSSACO) is put forward. The MSSACO sets multiple pheromones and pheromone weights to note the preference to different properties of a service. Having a unified services selecting model that is based on a comprehensive analysis of different services composition methods, the MSSACO can make individualized services selection according to the record of a service, and can be adapted to the dynamic change of services composition process and QoS. Making some improvements on the strategies of ACO, the MSSACO can find if the optimization is converging to local optimized value, in which case can take measures to change its direction, and as a result reduce the probability of the algorithm to converge to local optimized value.
另外,个性化的要求使得服务组合过程越来越重视用户的需求,提供满足用户个性化体验的服务越来越成为服务提供者努力的目标。而要在服务组合过程中组合出更具个性化、令用户满意的服务,就必须考虑用户的偏好。
本文针对以上两个问题展开研究工作,取得了以下研究成果:
1)提出一种基于属性语义关联的服务组合方法,该方法转换服务的输入、输出参数为服务的相关属性,建立属性语义关联规则进行服务组合,可直接应用推理引擎在本体之上进行推理,不需通过复杂的机制进行不同服务接口间的协调、统一,提高了服务组合的效率和成功率,属于轻量级的服务组合方法。同时建立的领域服务本体,能根据该本体的领域分类概念有效组织服务,不仅能区分不同服务间的功能,还能缩小服务选择时的搜索范围。
2)为使偏好描述适用于动态服务组合,提出一种属性分解的偏好本体表示方法PODDA。该方法增加了偏好描述的语义及语义关联,并把用户对服务的偏好分解为多个子偏好集合或属性偏好集合,对应本体的建立可从领域本体的概念层次关系中提取服务的子偏好集合,从概念间的关联度提取服务的属性偏好集合,从而能够充分利用领域本体中已存在的资源,且能更深入地表示出用户在多重约束下的偏好,使建立的偏好本体更合理和完整。为验证PODDA的有效性与合理性,建立了一个面向旅游领域的偏好本体对其进行了验证。
3)在以上偏好研究的基础上,对一类具有特殊性质——“边际效用递减”性质服务的推荐问题进行了研究。该研究借鉴经济学中的消费者行为理论,运用偏好、边际效用等方面的原理,对该类性质的单一服务推荐问题以及多个服务的组合服务推荐问题分别进行了研究。该方法可在一定预算前提下使得推荐的组合服务理论上达到效用最大化。
以上提出的个性化服务组合方法,需要在大量服务中选择满足用户需求的服务,这使得服务组合的效率急剧降低,急需要寻找有效的方法进行服务组合优化。为此,该研究提出两种服务选择和组合服务优化算法,一种针对用户QoS属性限制,一种引入用户偏好本体,增加偏好权重,使优化结果更适合用户的个性化需求。
4)提出一种多信息素动态更新的蚁群算法MPDACO,用于进行服务组合优化及适应服务组合优化过程中Web服务的动态性、不稳定性,以及多种QoS属性限制等问题。该算法可以适应服务组合优化过程中发生的服务无效、服务增加以及服务QoS变化等情况,为使算法能较快地收敛于最优解,在实验基础上对算法进行了改进。另外,还提出一种基于蚁群算法原理、启发式发现较好解的算法,用于提高大规模服务选择问题的效率,在较少的迭代次数下即可以获得较优解。
5)为解决引入用户偏好本体后大规模服务的选择问题、服务选择中的信息重用问题以及组合服务的个性化问题,提出一种基于蚁群算法的服务选择方法MSSACO。MSSACO在设立多种信息素的同时,增加相应权重表示用户对服务不同属性的偏好,提出的统一服务选择模型建立在对多种服务组合方法的研究基础之上,能根据服务的历史信息进行个性化的服务选择,并能适应服务组合流程的动态变化以及服务QoS的动态变化等。MSSACO还对蚁群算法的策略进行了改进,能探测优化过程是否正在向局部最优解收敛,并能及时采取措施改变运行方向,从而降低了算法收敛到局部最优解的概率。
With network technology's development, dynamic services composition technology is becoming one focus in research. Based on Semantic Web, Dynamic Service Composition technology requires that the network have semantic function, caple of discovering, selecting and composing services dynamically. Nevertheless, the research on how to enrich the web's semantics emphasizes on ontology, such as building relevant domain ontology for domain knowledge, building service ontology for Web service based on wide applications of SOA, etc. For this reason, the research on "ontology" is of vital importance for services composition technology.
In addition, the requirement for individuation makes users' needs be increasingly regarded in the process of services composition, and providing users with such services that meet their individualized experiences is becoming the objective of the provider. Thus users' preference must be taken into consideration if more individualized and satisfying services are to be composed in the services compositon.
Aiming at solving the above problems, this paper achieves the following results:
1) One services composition method based on attribute semantic association is advanced. This method converts the input and output parameters of the service into its relavant attributes, and builds the rule for attribute semantic association to make services compostion. Being able to reason based on ontology by using engine, and eliminating the complicated mediation between various service interfaces by using complex mechanism, this method promotes the efficiency and feasibility of the services composition, which makes it a light weight services composition method. Additionally, the domain services ontology that has been built can effectively organize services according to the domain classification concept of the ontology, differentiate the functions between various services, and reduce the searching space in services selection.
2) In order to apply preference description to the dynamic services composition, a method named PODDA is put forward. This method adds semantics to the service preference of the user and decomposed this preference into many sub preference sets or attribute preference sets. By abstracting sub preference sets from the relations of the domain ontology's concepts and services' attribute preference sets from the relations between the concepts, the building of the relevant ontology could better utilize the existing resource in domain ontology and express the user's preference under multiple restrictions more profoundly. In the end, a preference ontology on tourism is built to test the feasibility and rationality of PODDA.
3) On the basis of the above research on preference, we make an analysis of a service recommendation issue with a special feature—the law of Diminishing Marginal Utility. By using the theory of consumer's action in economics, and such concepts as preference and utility, as well as the law of Diminishing Marginal Utility, we make respective researches on single service recommendation and on multiple services composition recommendation. This method can theoretically maximize the utility of the composed services on the basis of a certain budget.
In the individualized service composition method mentioned above, we need to select in a great amount of services such ones that meet users' demands, which decreases the efficiency of services composition and make it urgent to find effective method to optimize service composition. Accordingly, this research puts forward two service selection and services composition optimization algorithms: one is for users' QoS attribute constraint, and the other introduces users' preference ontology and adds preference weight to make the optimized result more fit for the users' individualized needs.
4) In order to optimize services composition and to be adapted to the dynamic and instable web services, as well as the limitation of multi-QoS attributes in the process of services composition, we put forward an algorithm named Multi-pheromone and Dynamic Update Ant Colony Optimization Algorithm (MPDACO). This algorithm can fit for the service futility, service increase and QoS change in the process of services composition optimization. In addition, the algorithm is improved to accelerate convergence to optimized result based on experiment. In the end, we also put forward a method that is based on ACO and can find optimized result heuristically, to be applied to increase service selection efficiency when the volume is great.
5) In order to address the challenges from services selecting in great volume, the information reuse in services selection, and the individuation of the services composition, a method of services selection applying Ant Colony Optimization (MSSACO) is put forward. The MSSACO sets multiple pheromones and pheromone weights to note the preference to different properties of a service. Having a unified services selecting model that is based on a comprehensive analysis of different services composition methods, the MSSACO can make individualized services selection according to the record of a service, and can be adapted to the dynamic change of services composition process and QoS. Making some improvements on the strategies of ACO, the MSSACO can find if the optimization is converging to local optimized value, in which case can take measures to change its direction, and as a result reduce the probability of the algorithm to converge to local optimized value.
引文
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