信息物理融合系统优化调度理论与方法的研究
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摘要
信息物理融合系统(CPS, Cyber-Physical System)是信息计算和物理过程紧密结合与协作的网络化系统。CPS的特征可体现为：可靠感知、实时传输、普适计算、精确控制、可信服务。CPS强调物理世界与信息世界的深度融合与交互作用,CPS在对物理环境可靠感知的基础上,通过网络的实时传输,利用信息世界的普适计算和信息处理能力,实现对物理世界的精确控制,为人们提供可信高效的服务。
本文重点研究CPS系统的可靠感知与优化调度模型与方法。针对物理世界的复杂性与时变性,建立异构互联的CPS体系结构和情景感知模型,在对海量异构信息可靠感知的基础上,建立资源调度模型,通过优化算法实现资源的优化调度,实现动态资源的高效组织与分配,从而协同服务与资源的最优化配置。
本文取得的研究成果如下：
(1)针对复杂系统内部大量自治个体的时变性和自治性,CPS系统的高异构性、强关联性与动态性,设计了基于功能部件划分的CPS网络拓扑模型,详细分析了感知部件、信息部件、决策部件、执行部件之间的内在联系及各自实现功能。明确了CPS体系设计思想,设计了多重层次划分的CPS体系结构,包括：接入层、感知层、网络层、数据处理层、应用层。为CPS情景可靠感知与资源优化调度奠定了基础架构。
(2)针对海量多源异构的传感信息,提出了一种CPS-rCAF情景感知模型,该模型有效地结合了底层信息采集与上层应用的开发：向上可以对应用服务提供统一的情景信息应用接口,向下可以接入各种类型的异构传感器,有效屏蔽各种异类原始信息的差异性,为上层系统提供统一的规范的语义解释和情景信息。为解决情景处理过程的情景冲突问题,提出了一种情景防冲突算法,并仿真验证了其资源安排的合理性与高效性。
(3)提出了CPS资源能力的概念,并设计了基于能力描述的CPS资源调度模型和基于任务-资源协同调度的CPS数学规划模型。针对一类不确定性系统的预测问题,分别提出了一种基于随机重采样改进的粒子滤波算法和一种遗传优化的粒子滤波算法,并通过区域交通车流状态预测模型仿真和验证了上述优化算法在预测非线性问题上具有良好的预测效果。
(4)针对大规模多阶段系统的优化调度问题,提出了一种改进的蚁群优化算法,建立了区域交通灯信号滚动优化的决策模型,并通过改进的蚁群优化算法对其求解。仿真结果表明,相对于传统的感应式控制,交通延误率降低15%。
本文的创新性可概括为：
(1)通过关联矩阵表达CPS部件功能划分的CPS网络拓扑模型。
(2)基于资源与情景的极值原理的情景防冲突算法的设计。
(3)面向非确定条件,遗传算法优化粒子滤波的重采样过程,保持了粒子的多样性和降低粒子退化现象。
(4)提出一种基于遗传优化的动态空间蚁群优化算法,该算法将各阶段许可策略值反映为层状构造图中的有限节点集,其中不同层节点对应一个阶段的许可策略集合的子集,该子集可通过遗传优化算法进行动态筛选,以减小蚂蚁的搜索空间,提高了蚁群算法的效率。
CPS是近年国内外学术界和科学界的研究热点,本文以CPS的环境可靠感知与资源优化调度为主要研究内容,实现物理世界的复杂系统服务优化、资源最优配置。重点研究了CPS体系结构、CPS情景感知模型与防冲突算法、CPS优化调度算法三方面的内容,取得了良好的研究成果和创新性成果。
In the physical world, exists a class of complex systems, their feature includes massive scale, massive information dynamically heterogeneous, changes in environmental uncertainty, individual autonomy and independence, such as urban transport systems, electricity transmission and distribution systems, assembly line production system. But for a long time, the physical world and the world of information with each other fragmented, separate development, the prevalence of such a class of complex systems real-time physical environmental information collection difficult, poor coordination between the various aspects of the system's internal information management level is low, serious waste of resources. In order to achieve the integration of the interaction of the physical world and the world of information, the information about the physical integration of the system (Cyber-Physical System, CPS) emerged, CPS is calculated and physical processes are closely integrated with the collaboration of networked systems, CPS is based on environmental perceptiondepth integration of computing, communications and control capabilities. CPS its seen, credible, and controllable properties collaborative optimization scheduling an unparalleled advantage in a complex system of intelligent services and resources.CPS architecture, the CPS resource optimization scheduling upper layer application, is built on the basis of reliable physical environment perceived resource optimization scheduling can be summarized by the mathematical description of the optimization algorithm, at the appropriate time, in an uncertain environment factorsunder reasonably efficient real-time scheduling the CPS system resources (ie, physical components, such as sensors, controllers, actuators) to accomplish the task, to better serve the physical world. The optimal scheduling of resources is the main means of control of the CPS complex system, the the fusion main purpose of the world and the physical world. In summary, this paper based on the complex systems of the physical world, oriented resource optimization scheduling, to CPS for technical support, and focuses on the CPS architecture, situational awareness, and scene of anti-collision model, optimal scheduling algorithm content, complex system of physicalthe seamless integration of the world with the information world, achieve service optimization, optimal allocation of resources, and the purpose of improving the quality of physical environment and human society.
The research results achieved in this paper are as follows:
(1) For the complex system of massive autonomous individual's when degeneration and autonomous nature, the CPS system of high heterogeneous nature, the strong correlation with the dynamic nature and design of features divided the CPS network topology model, a detailed analysis of the perceived components, information componentsthe intrinsic link between the decision-making components, execution units, and their respective functions. Clear the CPS system design thinking, design multiple levels by CPS heterogeneous interconnect architecture, including:access layer perception layer, network layer, data processing layer, application layer. Reliable scenario for CPS perception laid the infrastructure and resource optimization scheduling.
(2) analysis of related research of context-aware model, a of CPS-rCAF the situational awareness model, the model effectively combines the underlying information acquisition and development of the upper application:up application services to provide a unified scenariothe application interface down to access various types of heterogeneous sensor, effectively shielding the differences of heterogeneous original information, semantic interpretation and scene information to provide a unified specification for the upper system. A scene anti-collision algorithm to resolve the problem of the conflict of the scene of the scenario process and simulation reasonable efficiency of resource arrangements.
(3) CPS system-aware real-time, dynamic control and information service requires reliable, efficient scheduling algorithm for real-time collaboration. Constructed an optimization model for a complex system based on improved particle swarm optimization algorithm resampling improve the weights of the particles, and to have gradually increased relatively large particle data to improve particle operator method, so as to meet the non-deterministic complexity scheduling optimization system. After regional transportation scheduling simulation results show that the good accuracy the algorithm on the overall regional traffic flow forecasting.
(4) To further enhance the operation speed of the above-described optimization scheduling algorithm, in order to ensure the small and medium-sized particles of the operation process is repositioned, thereby increasing the operation precision of the particles, by the genetic algorithm to optimize the resampling process of the particles, and applied to solving complexsystem in the area of traffic lights, rolling optimization scheduling problem, the simulation results show:the particle swarm algorithm and genetic algorithm combination has obvious advantages in the control of regional coordination in complex systems, improve traffic efficiency.
The innovation of this paper can be summarized as follows:
(1) Expression through the associated matrix the CPS components function by the CPS network topology model.
(2) Anti-collision algorithm based on the the extremum principle scene of resources and scenarios design.
(3) Oriented non-deterministic conditions, design the optimal scheduling algorithm based on resampling particle swarm optimization particle weights.
(4) Through genetic algorithm optimization particle resampling process, as local heuristic information to guide a particle swarm generated higher quality solution at each stage of the optimization phase in the phase delay caused by an alternative signal.
CPS is a research focus at home and abroad in recent years, the academic and scientific community, the environment of this article to CPS reliable perception and the optimal resource as the main research ideas, service optimization of complex systems of the physical world, the optimal allocation of resources. Focus on the CPS architecture of the CPS context-aware model with anti-collision algorithm, optimal scheduling algorithm three good research and innovative achievements.
本文重点研究CPS系统的可靠感知与优化调度模型与方法。针对物理世界的复杂性与时变性,建立异构互联的CPS体系结构和情景感知模型,在对海量异构信息可靠感知的基础上,建立资源调度模型,通过优化算法实现资源的优化调度,实现动态资源的高效组织与分配,从而协同服务与资源的最优化配置。
本文取得的研究成果如下：
(1)针对复杂系统内部大量自治个体的时变性和自治性,CPS系统的高异构性、强关联性与动态性,设计了基于功能部件划分的CPS网络拓扑模型,详细分析了感知部件、信息部件、决策部件、执行部件之间的内在联系及各自实现功能。明确了CPS体系设计思想,设计了多重层次划分的CPS体系结构,包括：接入层、感知层、网络层、数据处理层、应用层。为CPS情景可靠感知与资源优化调度奠定了基础架构。
(2)针对海量多源异构的传感信息,提出了一种CPS-rCAF情景感知模型,该模型有效地结合了底层信息采集与上层应用的开发：向上可以对应用服务提供统一的情景信息应用接口,向下可以接入各种类型的异构传感器,有效屏蔽各种异类原始信息的差异性,为上层系统提供统一的规范的语义解释和情景信息。为解决情景处理过程的情景冲突问题,提出了一种情景防冲突算法,并仿真验证了其资源安排的合理性与高效性。
(3)提出了CPS资源能力的概念,并设计了基于能力描述的CPS资源调度模型和基于任务-资源协同调度的CPS数学规划模型。针对一类不确定性系统的预测问题,分别提出了一种基于随机重采样改进的粒子滤波算法和一种遗传优化的粒子滤波算法,并通过区域交通车流状态预测模型仿真和验证了上述优化算法在预测非线性问题上具有良好的预测效果。
(4)针对大规模多阶段系统的优化调度问题,提出了一种改进的蚁群优化算法,建立了区域交通灯信号滚动优化的决策模型,并通过改进的蚁群优化算法对其求解。仿真结果表明,相对于传统的感应式控制,交通延误率降低15%。
本文的创新性可概括为：
(1)通过关联矩阵表达CPS部件功能划分的CPS网络拓扑模型。
(2)基于资源与情景的极值原理的情景防冲突算法的设计。
(3)面向非确定条件,遗传算法优化粒子滤波的重采样过程,保持了粒子的多样性和降低粒子退化现象。
(4)提出一种基于遗传优化的动态空间蚁群优化算法,该算法将各阶段许可策略值反映为层状构造图中的有限节点集,其中不同层节点对应一个阶段的许可策略集合的子集,该子集可通过遗传优化算法进行动态筛选,以减小蚂蚁的搜索空间,提高了蚁群算法的效率。
CPS是近年国内外学术界和科学界的研究热点,本文以CPS的环境可靠感知与资源优化调度为主要研究内容,实现物理世界的复杂系统服务优化、资源最优配置。重点研究了CPS体系结构、CPS情景感知模型与防冲突算法、CPS优化调度算法三方面的内容,取得了良好的研究成果和创新性成果。
In the physical world, exists a class of complex systems, their feature includes massive scale, massive information dynamically heterogeneous, changes in environmental uncertainty, individual autonomy and independence, such as urban transport systems, electricity transmission and distribution systems, assembly line production system. But for a long time, the physical world and the world of information with each other fragmented, separate development, the prevalence of such a class of complex systems real-time physical environmental information collection difficult, poor coordination between the various aspects of the system's internal information management level is low, serious waste of resources. In order to achieve the integration of the interaction of the physical world and the world of information, the information about the physical integration of the system (Cyber-Physical System, CPS) emerged, CPS is calculated and physical processes are closely integrated with the collaboration of networked systems, CPS is based on environmental perceptiondepth integration of computing, communications and control capabilities. CPS its seen, credible, and controllable properties collaborative optimization scheduling an unparalleled advantage in a complex system of intelligent services and resources.CPS architecture, the CPS resource optimization scheduling upper layer application, is built on the basis of reliable physical environment perceived resource optimization scheduling can be summarized by the mathematical description of the optimization algorithm, at the appropriate time, in an uncertain environment factorsunder reasonably efficient real-time scheduling the CPS system resources (ie, physical components, such as sensors, controllers, actuators) to accomplish the task, to better serve the physical world. The optimal scheduling of resources is the main means of control of the CPS complex system, the the fusion main purpose of the world and the physical world. In summary, this paper based on the complex systems of the physical world, oriented resource optimization scheduling, to CPS for technical support, and focuses on the CPS architecture, situational awareness, and scene of anti-collision model, optimal scheduling algorithm content, complex system of physicalthe seamless integration of the world with the information world, achieve service optimization, optimal allocation of resources, and the purpose of improving the quality of physical environment and human society.
The research results achieved in this paper are as follows:
(1) For the complex system of massive autonomous individual's when degeneration and autonomous nature, the CPS system of high heterogeneous nature, the strong correlation with the dynamic nature and design of features divided the CPS network topology model, a detailed analysis of the perceived components, information componentsthe intrinsic link between the decision-making components, execution units, and their respective functions. Clear the CPS system design thinking, design multiple levels by CPS heterogeneous interconnect architecture, including:access layer perception layer, network layer, data processing layer, application layer. Reliable scenario for CPS perception laid the infrastructure and resource optimization scheduling.
(2) analysis of related research of context-aware model, a of CPS-rCAF the situational awareness model, the model effectively combines the underlying information acquisition and development of the upper application:up application services to provide a unified scenariothe application interface down to access various types of heterogeneous sensor, effectively shielding the differences of heterogeneous original information, semantic interpretation and scene information to provide a unified specification for the upper system. A scene anti-collision algorithm to resolve the problem of the conflict of the scene of the scenario process and simulation reasonable efficiency of resource arrangements.
(3) CPS system-aware real-time, dynamic control and information service requires reliable, efficient scheduling algorithm for real-time collaboration. Constructed an optimization model for a complex system based on improved particle swarm optimization algorithm resampling improve the weights of the particles, and to have gradually increased relatively large particle data to improve particle operator method, so as to meet the non-deterministic complexity scheduling optimization system. After regional transportation scheduling simulation results show that the good accuracy the algorithm on the overall regional traffic flow forecasting.
(4) To further enhance the operation speed of the above-described optimization scheduling algorithm, in order to ensure the small and medium-sized particles of the operation process is repositioned, thereby increasing the operation precision of the particles, by the genetic algorithm to optimize the resampling process of the particles, and applied to solving complexsystem in the area of traffic lights, rolling optimization scheduling problem, the simulation results show:the particle swarm algorithm and genetic algorithm combination has obvious advantages in the control of regional coordination in complex systems, improve traffic efficiency.
The innovation of this paper can be summarized as follows:
(1) Expression through the associated matrix the CPS components function by the CPS network topology model.
(2) Anti-collision algorithm based on the the extremum principle scene of resources and scenarios design.
(3) Oriented non-deterministic conditions, design the optimal scheduling algorithm based on resampling particle swarm optimization particle weights.
(4) Through genetic algorithm optimization particle resampling process, as local heuristic information to guide a particle swarm generated higher quality solution at each stage of the optimization phase in the phase delay caused by an alternative signal.
CPS is a research focus at home and abroad in recent years, the academic and scientific community, the environment of this article to CPS reliable perception and the optimal resource as the main research ideas, service optimization of complex systems of the physical world, the optimal allocation of resources. Focus on the CPS architecture of the CPS context-aware model with anti-collision algorithm, optimal scheduling algorithm three good research and innovative achievements.
引文
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