云制造系统中基于能耗的服务组合关键技术研究
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摘要
当今,随着信息化技术、网络服务技术、语义技术、效用技术、云计算技术、物联网技术等的快速发展,敏捷制造、计算机集成制造、制造网格、云制造(Cloud Manufacturing, CloudM)等网络化制造模式相继出现,针对其他网络化制造模式面临的应用及推广问题,CloudM作为一种面向服务的网络化制造新模式,为用户提供从产品设计、制造、实验、仿真、维护等制造全生命周期过程的、可随时获取的、按需使用的、安全可靠的、优质廉价的服务。
服务组合是云制造系统实施的关键性问题之一,现有对服务组合优选问题(Service Composition and Optimal Selection, SCOS)的研究工作集中在基于服务质量(Quality of Service, QoS)的基础上,为用户提供优质服务,而对如何为用户提供优质低耗的服务研究不足,没有相关的系统理论和方法。主要体现在下面几个方面：(1)如何评估服务能耗?(2)如何构建服务组合执行路径来满足用户复杂需求?(3)如何评估服务组合执行路径能耗及QoS?(4)如何设计在服务组合过程云企业、用户、云平台节能激励机制?(5)如何设计高效算法来解决多目标SCOS司题?(6)如何在相冲突的多目标优化中寻找平衡?(7)如何实现基于服务组合以减少组合优选时间和提高成功率。
本文针对以上的基于能耗的服务组合问题,在充分考虑云制造系统中服务组合的特定要求的基础上、从服务的能耗及组合服务的能耗出发、从基于案例库的优选算法初始化需求出发,对其中涉及的理论及关键技术进行研究,旨在为绿色云制造的落地应用奠定理论基础和提供关键技术。本文的主要研究工作如下：
(1)针对绿色云制造系统中服务组合的特点,对云制造系统中服务组合问题进行了描述和分析,提出了基于能耗和QOS的云制造服务组合系统框架,阐述了实现基于能耗及QoS的云制造服务组合关键技术。
(2)讨论了云制造资源和云制造服务的定义,结合CloudM服务组合及优选的需求,研究了服务QOS评估模型,重点研究了支持全生命周期的服务能耗评估模型,提出了云制造服务能耗综合评估框架、云制造服务能耗模型,设计了云制造服务综合能耗算法来评估单个服务能耗,并给出了服务创建阶段的能耗评估实例。
(3)对服务组合进行了描述,重点研究了基于能耗及QoS的云制造服务组合多目标优选模型(Multiple Objectives Service Composition and Optimal Selection Based on Energy Consumption and QoS, MOSCOS-ECQoS),包括服务组合基本构成模型、服务组合执行路径及服务组合执行路径QoS、能耗评估；设计了面向云制造服务组合的云制造节能激励机制。
(4)为给用户和系统选择优质低耗的服务,研究了基于群领导算法(Group Leader algorithm, GLA)-Pareto的服务组合优选方法、服务组合执行路径与GLA算法的映射关系；根据多目标优化Pareto解的基本概念,研究了MOSCOS-ECQoS问题的解,设计了GLA-Pareto算法的结构和实现流程,并进行实验仿真分析。
(5)研究了基于案例库的服务组合实现方案；给出了基于案例库的优选算法初始化实现技术,包括服务组合案例库结构、服务组合案例库设计、服务组合案例库更新；给出了基于案例库的服务组合实现流程,并进行实验仿真分析。
(6)开发出基于能耗的云制造服务组合原型系统,对本文提出的基于能耗的服务组合关键技术,包括QOS、能耗评估、多目标服务组合优选建模、优选算法设计、服务组合案例库设计等进行功能实现,并对论文的部分研究成果进行了验证。
Nowadays, with the development of informatization technology, web service, semantic Web, utility computing, cloud computing, and internet of things, computer integrated manufacturing, agile manufacturing, manufacturing grid, cloud manufacturing (CloudM) and other networked manufacturing modes are proposed and used widely. Based on the analysis of application and promotion problems in the existing mode, as a new generation service-oriented networked manufacturing mode, CloudM is to provide user with on-demand, always-ready, high-quality and low-consumption service, which is available from product design, manufacturing, testing, simulation and maintenance and other manufacturing lifecycle process.
Service composition is one of the key issues in implementing CloudM system. Exiting works on service composition are primarily based on quality of service (QoS) to provide high-quality service for user. Few works have been delivered on providing both high-quality and low-energy consumption service and no related theories and methods are proposed. The following problems must be addressed:(1) How to evaluate service energy consumption?(2) How to generate composed service execute path (CSEP) to satisfied complex user requirement?(3) How to evaluate CSEP energy consumption?(4) How to design energy-saving incentive mechanism for enterprise, user and CloudM platform inservice composition process?(5) How to design an efficient algorithm for multi-objective SCOS problem?(6)How to find right balance in conflicting multi-objectives?(7) How to realize service composition to decrease composition and selection times and increase success rate?
Considering the specific requirements of service composition in CloudM, this paper researches on the involving theories and technologies of service composition based on service energy consumption, composed service energy consumption and intelligent service composition, which provides the technical supports for the application of CloudM. The main works involving in this paper is as follows:
(1) In view of the characteristics of service composition in green CloudM, this paper analyses and descripts service composition in CloudM, proposed energy consumption and QoS aware service composition framework in CloudM, and elaborate key technologies to achieve energy consumption and QoS aware service composition in CloudM.
(2) The definitions of CloudM resource and service are given out. Combined with requirement of CloudM green service composition and selection, QoS evaluation model and energy consumption evaluation model supporting lifecycle process are researched. CloudM service energy consumption evaluation framework is proposed, as well as service energy consumption model.To evaluates single service, CloudM service energy consumption evaluation algorithm is design, and the case study is given out.
(3) Description of service composition is studied. Multiple objectives service composition and optimal selection model based on energy consumption and QoS (MOSCOS-ECQoS) is proposed, including service composition basic modes, CESP Qos andenergy consumption evaluation. Energy-saving incentive mechanism in service composition process is design.
(4) To provide user high-quality and low-energy consumption service, green service composition selection methods based on Group Leader algorithm-Pareto are researched. Mapping relationship between a CESP candidate and a GLA member is discusses. Based on concept of multi-objectives Pareto, solutions of MOSCOS-ECQoS are researched. The structure and process of GLA-Pareto algorithm are designed.The case study and simulation results indicate the proposed methods are valid and effective.
(5) Based oncase library, service composition implementation plan are proposed, including structure, design, update and process of service composition case library. The implementation and simulation results indicate that the proposed approaches are sound on promoting the success rate and speed of MOSCOS-ECQoS.
(6) To verifies the partly research results, this paper design prototype system of energy consumption aware service composition, the functions of key modules in the prototype system are realized, including QoS evaluation, energy consumption evaluation, multi-objectives optimal service selection modeling, optimal selection algorithm and service composition based on case library, et al.
服务组合是云制造系统实施的关键性问题之一,现有对服务组合优选问题(Service Composition and Optimal Selection, SCOS)的研究工作集中在基于服务质量(Quality of Service, QoS)的基础上,为用户提供优质服务,而对如何为用户提供优质低耗的服务研究不足,没有相关的系统理论和方法。主要体现在下面几个方面：(1)如何评估服务能耗?(2)如何构建服务组合执行路径来满足用户复杂需求?(3)如何评估服务组合执行路径能耗及QoS?(4)如何设计在服务组合过程云企业、用户、云平台节能激励机制?(5)如何设计高效算法来解决多目标SCOS司题?(6)如何在相冲突的多目标优化中寻找平衡?(7)如何实现基于服务组合以减少组合优选时间和提高成功率。
本文针对以上的基于能耗的服务组合问题,在充分考虑云制造系统中服务组合的特定要求的基础上、从服务的能耗及组合服务的能耗出发、从基于案例库的优选算法初始化需求出发,对其中涉及的理论及关键技术进行研究,旨在为绿色云制造的落地应用奠定理论基础和提供关键技术。本文的主要研究工作如下：
(1)针对绿色云制造系统中服务组合的特点,对云制造系统中服务组合问题进行了描述和分析,提出了基于能耗和QOS的云制造服务组合系统框架,阐述了实现基于能耗及QoS的云制造服务组合关键技术。
(2)讨论了云制造资源和云制造服务的定义,结合CloudM服务组合及优选的需求,研究了服务QOS评估模型,重点研究了支持全生命周期的服务能耗评估模型,提出了云制造服务能耗综合评估框架、云制造服务能耗模型,设计了云制造服务综合能耗算法来评估单个服务能耗,并给出了服务创建阶段的能耗评估实例。
(3)对服务组合进行了描述,重点研究了基于能耗及QoS的云制造服务组合多目标优选模型(Multiple Objectives Service Composition and Optimal Selection Based on Energy Consumption and QoS, MOSCOS-ECQoS),包括服务组合基本构成模型、服务组合执行路径及服务组合执行路径QoS、能耗评估；设计了面向云制造服务组合的云制造节能激励机制。
(4)为给用户和系统选择优质低耗的服务,研究了基于群领导算法(Group Leader algorithm, GLA)-Pareto的服务组合优选方法、服务组合执行路径与GLA算法的映射关系；根据多目标优化Pareto解的基本概念,研究了MOSCOS-ECQoS问题的解,设计了GLA-Pareto算法的结构和实现流程,并进行实验仿真分析。
(5)研究了基于案例库的服务组合实现方案；给出了基于案例库的优选算法初始化实现技术,包括服务组合案例库结构、服务组合案例库设计、服务组合案例库更新；给出了基于案例库的服务组合实现流程,并进行实验仿真分析。
(6)开发出基于能耗的云制造服务组合原型系统,对本文提出的基于能耗的服务组合关键技术,包括QOS、能耗评估、多目标服务组合优选建模、优选算法设计、服务组合案例库设计等进行功能实现,并对论文的部分研究成果进行了验证。
Nowadays, with the development of informatization technology, web service, semantic Web, utility computing, cloud computing, and internet of things, computer integrated manufacturing, agile manufacturing, manufacturing grid, cloud manufacturing (CloudM) and other networked manufacturing modes are proposed and used widely. Based on the analysis of application and promotion problems in the existing mode, as a new generation service-oriented networked manufacturing mode, CloudM is to provide user with on-demand, always-ready, high-quality and low-consumption service, which is available from product design, manufacturing, testing, simulation and maintenance and other manufacturing lifecycle process.
Service composition is one of the key issues in implementing CloudM system. Exiting works on service composition are primarily based on quality of service (QoS) to provide high-quality service for user. Few works have been delivered on providing both high-quality and low-energy consumption service and no related theories and methods are proposed. The following problems must be addressed:(1) How to evaluate service energy consumption?(2) How to generate composed service execute path (CSEP) to satisfied complex user requirement?(3) How to evaluate CSEP energy consumption?(4) How to design energy-saving incentive mechanism for enterprise, user and CloudM platform inservice composition process?(5) How to design an efficient algorithm for multi-objective SCOS problem?(6)How to find right balance in conflicting multi-objectives?(7) How to realize service composition to decrease composition and selection times and increase success rate?
Considering the specific requirements of service composition in CloudM, this paper researches on the involving theories and technologies of service composition based on service energy consumption, composed service energy consumption and intelligent service composition, which provides the technical supports for the application of CloudM. The main works involving in this paper is as follows:
(1) In view of the characteristics of service composition in green CloudM, this paper analyses and descripts service composition in CloudM, proposed energy consumption and QoS aware service composition framework in CloudM, and elaborate key technologies to achieve energy consumption and QoS aware service composition in CloudM.
(2) The definitions of CloudM resource and service are given out. Combined with requirement of CloudM green service composition and selection, QoS evaluation model and energy consumption evaluation model supporting lifecycle process are researched. CloudM service energy consumption evaluation framework is proposed, as well as service energy consumption model.To evaluates single service, CloudM service energy consumption evaluation algorithm is design, and the case study is given out.
(3) Description of service composition is studied. Multiple objectives service composition and optimal selection model based on energy consumption and QoS (MOSCOS-ECQoS) is proposed, including service composition basic modes, CESP Qos andenergy consumption evaluation. Energy-saving incentive mechanism in service composition process is design.
(4) To provide user high-quality and low-energy consumption service, green service composition selection methods based on Group Leader algorithm-Pareto are researched. Mapping relationship between a CESP candidate and a GLA member is discusses. Based on concept of multi-objectives Pareto, solutions of MOSCOS-ECQoS are researched. The structure and process of GLA-Pareto algorithm are designed.The case study and simulation results indicate the proposed methods are valid and effective.
(5) Based oncase library, service composition implementation plan are proposed, including structure, design, update and process of service composition case library. The implementation and simulation results indicate that the proposed approaches are sound on promoting the success rate and speed of MOSCOS-ECQoS.
(6) To verifies the partly research results, this paper design prototype system of energy consumption aware service composition, the functions of key modules in the prototype system are realized, including QoS evaluation, energy consumption evaluation, multi-objectives optimal service selection modeling, optimal selection algorithm and service composition based on case library, et al.
引文
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