Production logistics(PL)is considered as a critical factor that affects the efficiency and cost of production operations in discrete manufacturing systems.To effectively utilize manufacturing big data to improve PL ef...Production logistics(PL)is considered as a critical factor that affects the efficiency and cost of production operations in discrete manufacturing systems.To effectively utilize manufacturing big data to improve PL efficiency and promote job shop floor economic benefits,this study proposes a PL trajectory analysis and optimization decision making method driven by a manufacturing task data chain(MTDC).First,the manufacturing task chain(MTC)is defined to characterize the discrete production process of a product.To handle manufacturing big data,the MTC data paradigm is designed,and the MTDC is established.Then,the logistics trajectory model is presented,where the various types of logistics trajectories are extracted using the MTC as the search engine for the MTDC.Based on this,a logistics efficiency evaluation indicator system is proposed to support the optimization decision making for the PL.Finally,a case study is applied to verify the proposed method,and the method determines the PL optimization decisions for PL efficiency without changing the layout and workshop equipment,which can assist managers in implementing the optimization decisions.展开更多
How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data cente...How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data centers. The winner tree is introduced to make the data nodes as the leaf nodes of the tree and the final winner on the purpose of reducing energy consumption is selected. The complexity of large-scale cloud data centers is fully consider, and the task comparson coefficient is defined to make task scheduling strategy more reasonable. Experiments and performance analysis show that the proposed algorithm can effectively improve the node utilization, and reduce the overall power consumption of the cloud data center.展开更多
Data quality has exerted important influence over the application of grain big data, so data cleaning is a necessary and important work. In MapReduce frame, parallel technique is often used to execute data cleaning in...Data quality has exerted important influence over the application of grain big data, so data cleaning is a necessary and important work. In MapReduce frame, parallel technique is often used to execute data cleaning in high scalability mode, but due to the lack of effective design, there are amounts of computing redundancy in the process of data cleaning, which results in lower performance. In this research, we found that some tasks often are carried out multiple times on same input files, or require same operation results in the process of data cleaning. For this problem, we proposed a new optimization technique that is based on task merge. By merging simple or redundancy computations on same input files, the number of the loop computation in MapReduce can be reduced greatly. The experiment shows, by this means, the overall system runtime is significantly reduced, which proves that the process of data cleaning is optimized. In this paper, we optimized several modules of data cleaning such as entity identification, inconsistent data restoration, and missing value filling. Experimental results show that the proposed method in this paper can increase efficiency for grain big data cleaning.展开更多
Task duplication has been widely adopted to mitigate the impact of stragglers that run much longer than normal tasks. However,task duplication on data pipelining case would generate excessive traffic over the datacent...Task duplication has been widely adopted to mitigate the impact of stragglers that run much longer than normal tasks. However,task duplication on data pipelining case would generate excessive traffic over the datacenter networks. In this paper, we study minimizing the traffic cost for data pipelining task replications and design a controller that chooses the data generated by the first finished task and discards data generated later by other replications belonging to the same task. Each task replication communicates with the controller when it finishes a data processing, which causes additional network overhead. Hence, we try to reduce the network overhead and make a trade-off between the delay of data block and the network overhead. Finally, extensive simulation results demonstrate that our proposal can minimize network traffic cost under data pipelining case.展开更多
为满足训练的信息化需求,设计了灵活通用的数据协议和虚实结合的信息引接系统。基于中间件的分层设计思路,实现了外部信息接收、对内信息转发、通信协议解析与转换、信息对接联调、数据文件记录、配置管理以及信息流量统计等功能;采用了...为满足训练的信息化需求,设计了灵活通用的数据协议和虚实结合的信息引接系统。基于中间件的分层设计思路,实现了外部信息接收、对内信息转发、通信协议解析与转换、信息对接联调、数据文件记录、配置管理以及信息流量统计等功能;采用了MVC软件架构模式,选用Visual Studio 2015作为开发工具,以Oracle数据库作为底层支撑,构建了实装信息及虚拟目标信息接收模块、建立数据映射关系模块、读取数据库方案模块、基础通信接收内部航迹模块、数据包发送模块。实际应用效果表明,该系统能够屏蔽外部装备系统、仿真系统和网络协议之间的差异,提供互联互通,适应虚实结合的训练任务,提高保障能力。该系统具有良好的适应性和可扩展性,可以满足信息化条件下系统的应用和发展需要。展开更多
基金supported by The University Discipline(Professional)Top-notch Talent Academic Funding Project of Anhui Provincethe General Project of National Natural Science Foundation of Anhui Province.
文摘Production logistics(PL)is considered as a critical factor that affects the efficiency and cost of production operations in discrete manufacturing systems.To effectively utilize manufacturing big data to improve PL efficiency and promote job shop floor economic benefits,this study proposes a PL trajectory analysis and optimization decision making method driven by a manufacturing task data chain(MTDC).First,the manufacturing task chain(MTC)is defined to characterize the discrete production process of a product.To handle manufacturing big data,the MTC data paradigm is designed,and the MTDC is established.Then,the logistics trajectory model is presented,where the various types of logistics trajectories are extracted using the MTC as the search engine for the MTDC.Based on this,a logistics efficiency evaluation indicator system is proposed to support the optimization decision making for the PL.Finally,a case study is applied to verify the proposed method,and the method determines the PL optimization decisions for PL efficiency without changing the layout and workshop equipment,which can assist managers in implementing the optimization decisions.
基金supported by the National Natural Science Foundation of China(6120200461272084)+9 种基金the National Key Basic Research Program of China(973 Program)(2011CB302903)the Specialized Research Fund for the Doctoral Program of Higher Education(2009322312000120113223110003)the China Postdoctoral Science Foundation Funded Project(2011M5000952012T50514)the Natural Science Foundation of Jiangsu Province(BK2011754BK2009426)the Jiangsu Postdoctoral Science Foundation Funded Project(1102103C)the Natural Science Fund of Higher Education of Jiangsu Province(12KJB520007)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(yx002001)
文摘How to effectively reduce the energy consumption of large-scale data centers is a key issue in cloud computing. This paper presents a novel low-power task scheduling algorithm （L3SA） for large-scale cloud data centers. The winner tree is introduced to make the data nodes as the leaf nodes of the tree and the final winner on the purpose of reducing energy consumption is selected. The complexity of large-scale cloud data centers is fully consider, and the task comparson coefficient is defined to make task scheduling strategy more reasonable. Experiments and performance analysis show that the proposed algorithm can effectively improve the node utilization, and reduce the overall power consumption of the cloud data center.
文摘Data quality has exerted important influence over the application of grain big data, so data cleaning is a necessary and important work. In MapReduce frame, parallel technique is often used to execute data cleaning in high scalability mode, but due to the lack of effective design, there are amounts of computing redundancy in the process of data cleaning, which results in lower performance. In this research, we found that some tasks often are carried out multiple times on same input files, or require same operation results in the process of data cleaning. For this problem, we proposed a new optimization technique that is based on task merge. By merging simple or redundancy computations on same input files, the number of the loop computation in MapReduce can be reduced greatly. The experiment shows, by this means, the overall system runtime is significantly reduced, which proves that the process of data cleaning is optimized. In this paper, we optimized several modules of data cleaning such as entity identification, inconsistent data restoration, and missing value filling. Experimental results show that the proposed method in this paper can increase efficiency for grain big data cleaning.
文摘Task duplication has been widely adopted to mitigate the impact of stragglers that run much longer than normal tasks. However,task duplication on data pipelining case would generate excessive traffic over the datacenter networks. In this paper, we study minimizing the traffic cost for data pipelining task replications and design a controller that chooses the data generated by the first finished task and discards data generated later by other replications belonging to the same task. Each task replication communicates with the controller when it finishes a data processing, which causes additional network overhead. Hence, we try to reduce the network overhead and make a trade-off between the delay of data block and the network overhead. Finally, extensive simulation results demonstrate that our proposal can minimize network traffic cost under data pipelining case.
文摘为满足训练的信息化需求,设计了灵活通用的数据协议和虚实结合的信息引接系统。基于中间件的分层设计思路,实现了外部信息接收、对内信息转发、通信协议解析与转换、信息对接联调、数据文件记录、配置管理以及信息流量统计等功能;采用了MVC软件架构模式,选用Visual Studio 2015作为开发工具,以Oracle数据库作为底层支撑,构建了实装信息及虚拟目标信息接收模块、建立数据映射关系模块、读取数据库方案模块、基础通信接收内部航迹模块、数据包发送模块。实际应用效果表明,该系统能够屏蔽外部装备系统、仿真系统和网络协议之间的差异,提供互联互通,适应虚实结合的训练任务,提高保障能力。该系统具有良好的适应性和可扩展性,可以满足信息化条件下系统的应用和发展需要。
