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Integration and sharing of remote sensing data in China

Zhou Chenghu,Ou Yang,Li Zengyuan

Strategic Study of CAE 2008, Volume 10, Issue 6,   Pages 51-55

Abstract:

With in-orbit operation satellites increasing and remote sensing data multiplying, integration and sharing of remote sensing data become the trend of the times. On the basis of analysis on the international development,the characteristics of globalization, systematization, standardization, and the network of the international development are further summed up. On the basis of the analysis and evaluation of existing remote sensing data resources and the integration and sharing status, some suggestions and ideas are further pointed out.

Keywords: remote sensing data     integration     sharing    

Dr.Hadoop: an infinite scalable metadata management for Hadoop—Howthe baby elephant becomes immortal

Dipayan DEV,Ripon PATGIRI

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 1,   Pages 15-31 doi: 10.1631/FITEE.1500015

Abstract:

In this Exa byte scale era, data increases at an exponential rate. This is in turn generating a massive amount of metadata in the file system. Hadoop is the most widely used framework to deal with big data. Due to this growth of huge amount of metadata, however, the efficiency of Hadoop is questioned numerous times by many researchers. Therefore, it is essential to create an efficient and scalable metadata management for Hadoop. Hash-based mapping and subtree partitioning are suitable in distributed metadata management schemes. Subtree partitioning does not uniformly distribute workload among the metadata servers, and metadata needs to be migrated to keep the load roughly balanced. Hash-based mapping suffers from a constraint on the locality of metadata, though it uniformly distributes the load among NameNodes, which are the metadata servers of Hadoop. In this paper, we present a circular metadata management mechanism named dynamic circular metadata splitting (DCMS). DCMS preserves metadata locality using consistent hashing and locality-preserving hashing, keeps replicated metadata for excellent reliability, and dynamically distributes metadata among the NameNodes to keep load balancing. NameNode is a centralized heart of the Hadoop. Keeping the directory tree of all files, failure of which causes the single point of failure (SPOF). DCMS removes Hadoop’s SPOF and provides an efficient and scalable metadata management. The new framework is named ‘Dr. Hadoop’ after the name of the authors.

Keywords: Hadoop     NameNode     Metadata     Locality-preserving hashing     Consistent hashing    

Perspectives on cross-domain visual analysis of cyber-physical-social big data Perspective

Wei Chen, Tianye Zhang, Haiyang Zhu, Xumeng Wang, Yunhai Wang,cloudseawang@gmail.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 12,   Pages 1551-1684 doi: 10.1631/FITEE.2100553

Abstract: The domain of cyber-physical-social (CPS) big data is generally defined as the set consisting of all the elements in its defined domain, including domains of data, objects, tasks, application scenarios, and subjects. Visual analytics is an emerging human-in-the-loop big data analytics paradigm that can exploit human perception to enhance human cognitive efficiency. In this paper, we explore the perspectives on cross-domain visual analysis of CPS big data. We also highlight new challenges brought by the cross-domain nature of CPS big data—data, subject, and task domains—and propose a novel visual analytics model and a suite of approaches to address these challenges.

Keywords: 可视分析;三元空间;大数据;跨域    

MDLB: a metadata dynamic load balancing mechanism based on reinforcement learning Research Articles

Zhao-qi Wu, Jin Wei, Fan Zhang, Wei Guo, Guang-wei Xie,17034203@qq.com

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900121

Abstract: With the growing amount of information and data, s have been widely used in many applications, including the Google File System, Amazon S3, Hadoop Distributed File System, and Ceph, in which load balancing of plays an important role in improving the input/output performance of the entire system. Unbalanced load on the server leads to a serious bottleneck problem for system performance. However, most existing load balancing strategies, which are based on subtree segmentation or hashing, lack good dynamics and adaptability. In this study, we propose a (MDLB) mechanism based on (RL). We learn that the algorithm and our RL-based strategy consist of three modules, i.e., the policy selection network, load balancing network, and parameter update network. Experimental results show that the proposed MDLB algorithm can adjust the load dynamically according to the performance of the servers, and that it has good adaptability in the case of sudden change of data volume.

Keywords: 面向对象的存储系统;元数据;动态负载均衡;强化学习;Q_learning    

Urban Big Data and the Development of City Intelligence Review

Yunhe Pan, Yun Tian, Xiaolong Liu, Dedao Gu, Gang Hua

Engineering 2016, Volume 2, Issue 2,   Pages 171-178 doi: 10.1016/J.ENG.2016.02.003

Abstract:

This study provides a definition for urban big data while exploring its features and applications of China’s city intelligence. The differences between city intelligence in China and the “smart city” concept in other countries are compared to highlight and contrast the unique definition and model for China’s city intelligence in this paper. Furthermore, this paper examines the role of urban big data in city intelligence by showing that it not only serves as the cornerstone of this trend as it also plays a core role in the diffusion of city intelligence technology and serves as an inexhaustible resource for the sustained development of city intelligence. This study also points out the challenges of shaping and developing of China’s urban big data. Considering the supporting and core role that urban big data plays in city intelligence, the study then expounds on the key points of urban big data, including infrastructure support, urban governance, public services, and economic and industrial development. Finally, this study points out that the utility of city intelligence as an ideal policy tool for advancing the goals of China’s urban development. In conclusion, it is imperative that China make full use of its unique advantages—including using the nation’s current state of development and resources, geographical advantages, and good human relations—in subjective and objective conditions to promote the development of city intelligence through the proper application of urban big data.

Keywords: Urban big data     City intelligence     Ternary space     Construction emphases    

Engineering DNA Materials for Sustainable Data Storage Using a DNA Movable-Type System Article

Zi-Yi Gong, Li-Fu Song, Guang-Sheng Pei, Yu-Fei Dong, Bing-Zhi Li, Ying-Jin Yuan

Engineering 2023, Volume 29, Issue 10,   Pages 130-136 doi: 10.1016/j.eng.2022.05.023

Abstract:

DNA molecules are green materials with great potential for high-density and long-term data storage. However, the current data-writing process of DNA data storage via DNA synthesis suffers from high costs and the production of hazards, limiting its practical applications. Here, we developed a DNA movable-type storage system that can utilize DNA fragments pre-produced by cell factories for data writing. In this system, these pre-generated DNA fragments, referred to herein as "DNA movable types," are used as basic writing units in a repetitive way. The process of data writing is achieved by the rapid assembly of these DNA movable types, thereby avoiding the costly and environmentally hazardous process of de novo DNA synthesis. With this system, we successfully encoded 24 bytes of digital information in DNA and read it back accurately by means of high-throughput sequencing and decoding, thereby demonstrating the feasibility of this system. Through its repetitive usage and biological assembly of DNA movable-type fragments, this system exhibits excellent potential for writing cost reduction, opening up a novel route toward an economical and sustainable digital data-storage technology.

Keywords: 合成生物学     DNA信息存储     DNA活字存储系统     经济性DNA数据存储    

ONFS: a hierarchical hybrid file system based on memory, SSD, andHDDfor high performance computers Article

Xin LIU, Yu-tong LU, Jie YU, Peng-fei WANG, Jie-ting WU, Ying LU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 12,   Pages 1940-1971 doi: 10.1631/FITEE.1700626

Abstract: With supercomputers developing towards exascale, the number of compute cores increases dramatically, making more complex and larger-scale applications possible. The input/output (I/O) requirements of large-scale applications, workflow applications, and their checkpointing include substantial bandwidth and an extremely low latency, posing a serious challenge to high performance computing (HPC) storage systems. Current hard disk drive (HDD) based underlying storage systems are becoming more and more incompetent to meet the requirements of next-generation exascale supercomputers. To rise to the challenge, we propose a hierarchical hybrid storage system, on-line and near-line file system (ONFS). It leverages dynamic random access memory (DRAM) and solid state drive (SSD) in compute nodes, and HDD in storage servers to build a three-level storage system in a unified namespace. It supports portable operating system interface (POSIX) semantics, and provides high bandwidth, low latency, and huge storage capacity. In this paper, we present the technical details on distributed metadata management, the strategy of memory borrow and return, data consistency, parallel access control, and mechanisms guiding downward and upward migration in ONFS. We implement an ONFS prototype on the TH-1A supercomputer, and conduct experiments to test its I/O performance and scalability. The results show that the bandwidths of single-thread and multi-thread ‘read’/‘write’ are 6-fold and 5-fold better than HDD-based Lustre, respectively. The I/O bandwidth of data-intensive applications in ONFS can be 6.35 times that in Lustre.

Keywords: High performance computing     Hierarchical hybrid storage system     Distributed metadata management     Data migration    

A Reconfigurable Data Glove for Reconstructing Physical and Virtual Grasps Article

Hangxin Liu,Zeyu Zhang,Ziyuan Jiao,Zhenliang Zhang,Minchen Li,Chenfanfu Jiang,Yixin Zhu,Song-Chun Zhu

Engineering 2024, Volume 32, Issue 1,   Pages 203-220 doi: 10.1016/j.eng.2023.01.009

Abstract:

In this work, we present a reconfigurable data glove design to capture different modes of human hand–object interactions, which are critical in training embodied artificial intelligence (AI) agents for fine manipulation tasks. To achieve various downstream tasks with distinct features, our reconfigurable data glove operates in three modes sharing a unified backbone design that reconstructs hand gestures in real time. In the tactile-sensing mode, the glove system aggregates manipulation force via customized force sensors made from a soft and thin piezoresistive material; this design minimizes interference during complex hand movements. The virtual reality (VR) mode enables real-time interaction in a physically plausible fashion: A caging-based approach is devised to determine stable grasps by detecting collision events. Leveraging a state-of-the-art finite element method, the simulation mode collects data on fine-grained four-dimensional manipulation events comprising hand and object motions in three-dimensional space and how the object's physical properties (e.g., stress and energy) change in accordance with manipulation over time. Notably, the glove system presented here is the first to use high-fidelity simulation to investigate the unobservable physical and causal factors behind manipulation actions. In a series of experiments, we characterize our data glove in terms of individual sensors and the overall system. More specifically, we evaluate the system's three modes by ① recording hand gestures and associated forces, ② improving manipulation fluency in VR, and ③ producing realistic simulation effects of various tool uses, respectively. Based on these three modes, our reconfigurable data glove collects and reconstructs fine-grained human grasp data in both physical and virtual environments, thereby opening up new avenues for the learning of manipulation skills for embodied AI agents.

Keywords: Data glove     Tactile sensing     Virtual reality     Physics-based simulation    

Sampling formulas for 2D quaternionic signals associated with various quaternion Fourier and linear canonical transforms Research Articles

Xiaoxiao HU, Dong CHENG, Kit Ian KOU,huxiaoxiao3650@163.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3,   Pages 463-478 doi: 10.1631/FITEE.2000499

Abstract: The main purpose of this paper is to study different types of sampling formulas of quaternionic functions, which are bandlimited under various quaternion Fourier and linear canonical transforms. We show that the quaternionic bandlimited functions can be reconstructed from their samples as well as the samples of their derivatives and Hilbert transforms. In addition, the relationships among different types of sampling formulas under various transforms are discussed. First, if the quaternionic function is bandlimited to a rectangle that is symmetric about the origin, then the sampling formulas under various are identical. If this rectangle is not symmetric about the origin, then the sampling formulas under various are different from each other. Second, using the relationship between the two-sided quaternion Fourier transform and the linear canonical transform, we derive sampling formulas under various . Third, of these sampling formulas are estimated. Finally, some simulations are provided to show how the sampling formulas can be used in applications.

Keywords: Quaternion Fourier transforms     Quaternion linear canonical transforms     Sampling theorem     Quaternion partial and total Hilbert transforms     Generalized quaternion partial and total Hilbert transforms     Truncation errors    

The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data

Yang Bingru,Tang Qing

Strategic Study of CAE 2003, Volume 5, Issue 1,   Pages 56-61

Abstract:

This paper discusses the macroscopic and important problem in the field of KDD. First, it is very difficult to describe the complex type data by general knowledge representation method. So the authors use pattern, which is defined as the vector in Hilbert Space, to represent the characteristic of complex type data. It also can be used to describe the rule of knowledge discovery. Second, the general structure model is constructed based on complex type data—DFSSM (discovery feature sub-space model ) following by the research on inner mechanism of knowledge discovery system. At last, the authors prove the practicability and validity of this general structure model i. e. DFSSM which can guide the knowledge discovery of textual data and image data (meteorological echogram data). It will beapplied in other complex type data in future.

Keywords: complex type data     data mining     text mining    

Big data storage technologies: a survey Review

Aisha SIDDIQA, Ahmad KARIM, Abdullah GANI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1040-1070 doi: 10.1631/FITEE.1500441

Abstract: There is a great thrust in industry toward the development of more feasible and viable tools for storing fast-growing volume, velocity, and diversity of data, termed ‘big data’. The structural shift of the storage mechanism from traditional data management systems to NoSQL technology is due to the intention of fulfilling big data storage requirements. However, the available big data storage technologies are inefficient to provide consistent, scalable, and available solutions for continuously growing heterogeneous data. Storage is the preliminary process of big data analytics for real-world applications such as scientific experiments, healthcare, social networks, and e-business. So far, Amazon, Google, and Apache are some of the industry standards in providing big data storage solutions, yet the literature does not report an in-depth survey of storage technologies available for big data, investigating the performance and magnitude gains of these technologies. The primary objective of this paper is to conduct a comprehensive investigation of state-of-the-art storage technologies available for big data. A well-defined taxonomy of big data storage technologies is presented to assist data analysts and researchers in understanding and selecting a storage mechanism that better fits their needs. To evaluate the performance of different storage architectures, we compare and analyze the existing approaches using Brewer’s CAP theorem. The significance and applications of storage technologies and support to other categories are discussed. Several future research challenges are highlighted with the intention to expedite the deployment of a reliable and scalable storage system.

Keywords: Big data     Big data storage     NoSQL databases     Distributed databases     CAP theorem     Scalability     Consistency- partition resilience     Availability-partition resilience    

Prompting the construction of national land observation data center and improving data sharing

Guo Jianning,Lu Shuning,Zhao Xiang

Strategic Study of CAE 2008, Volume 10, Issue 6,   Pages 70-75

Abstract:

This paper discussed the developing trend of the foreign land observation data processing center and the problems of our country land observation data management. The developing trend of the foreign land observation data processing center are: building up the concentrative data processing center and providing comprehensive service;building up the data sharing mechanism, improving the data sharing and servicing;reforming and integrating data resources. In order to improve the land observation data sharing and applications, it is necessary to build up the national land observation data center. The construction of the national land observation data center includes the facility of comprehensive data processing, archiving, distributing and service and so on. The national land observation data center will improve the land observation data sharing and application; satisfy the requirement of land observation data.

Keywords: satellite of remote sensing     land observation     data sharing     data center    

View and Comments on the Data Ecosystem: “Ocean of Data”

Zi-Kui Liu

Engineering 2020, Volume 6, Issue 6,   Pages 604-608 doi: 10.1016/j.eng.2020.04.009

Conception and Exploration of Using Data as a Service in Tunnel Construction with the NATM Article

Bowen Du, Yanliang Du, Fei Xu, Peng He

Engineering 2018, Volume 4, Issue 1,   Pages 123-130 doi: 10.1016/j.eng.2017.07.002

Abstract:

The New Austrian Tunneling Method (NATM) has been widely used in the construction of mountain tunnels, urban metro lines, underground storage tanks, underground power houses, mining roadways, and so on. The variation patterns of advance geological prediction data, stress–strain data of supporting structures, and deformation data of the surrounding rock are vitally important in assessing the rationality and reliability of construction schemes, and provide essential information to ensure the safety and scheduling of tunnel construction. However, as the quantity of these data increases significantly, the uncertainty and discreteness of the mass data make it extremely difficult to produce a reasonable construction scheme; they also reduce the forecast accuracy of accidents and dangerous situations, creating huge challenges in tunnel construction safety. In order to solve this problem, a novel data service system is proposed that uses data-association technology and the NATM, with the support of a big data environment. This system can integrate data resources from distributed monitoring sensors during the construction process, and then identify associations and build relations among data resources under the same construction conditions. These data associations and relations are then stored in a data pool. With the development and supplementation of the data pool, similar relations can then be used under similar conditions, in order to provide data references for construction schematic designs and resource allocation. The proposed data service system also provides valuable guidance for the construction of similar projects

Keywords: New Austrian Tunneling Method     Big data environments     Data as a service     Tunnel construction    

Title Author Date Type Operation

Integration and sharing of remote sensing data in China

Zhou Chenghu,Ou Yang,Li Zengyuan

Journal Article

Dr.Hadoop: an infinite scalable metadata management for Hadoop—Howthe baby elephant becomes immortal

Dipayan DEV,Ripon PATGIRI

Journal Article

Perspectives on cross-domain visual analysis of cyber-physical-social big data

Wei Chen, Tianye Zhang, Haiyang Zhu, Xumeng Wang, Yunhai Wang,cloudseawang@gmail.com

Journal Article

MDLB: a metadata dynamic load balancing mechanism based on reinforcement learning

Zhao-qi Wu, Jin Wei, Fan Zhang, Wei Guo, Guang-wei Xie,17034203@qq.com

Journal Article

Urban Big Data and the Development of City Intelligence

Yunhe Pan, Yun Tian, Xiaolong Liu, Dedao Gu, Gang Hua

Journal Article

Engineering DNA Materials for Sustainable Data Storage Using a DNA Movable-Type System

Zi-Yi Gong, Li-Fu Song, Guang-Sheng Pei, Yu-Fei Dong, Bing-Zhi Li, Ying-Jin Yuan

Journal Article

ONFS: a hierarchical hybrid file system based on memory, SSD, andHDDfor high performance computers

Xin LIU, Yu-tong LU, Jie YU, Peng-fei WANG, Jie-ting WU, Ying LU

Journal Article

A Reconfigurable Data Glove for Reconstructing Physical and Virtual Grasps

Hangxin Liu,Zeyu Zhang,Ziyuan Jiao,Zhenliang Zhang,Minchen Li,Chenfanfu Jiang,Yixin Zhu,Song-Chun Zhu

Journal Article

Sampling formulas for 2D quaternionic signals associated with various quaternion Fourier and linear canonical transforms

Xiaoxiao HU, Dong CHENG, Kit Ian KOU,huxiaoxiao3650@163.com

Journal Article

The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data

Yang Bingru,Tang Qing

Journal Article

Big data storage technologies: a survey

Aisha SIDDIQA, Ahmad KARIM, Abdullah GANI

Journal Article

Prompting the construction of national land observation data center and improving data sharing

Guo Jianning,Lu Shuning,Zhao Xiang

Journal Article

Chinese Academy of Engineering Issued the Implementation Measures for the Selection of Academicians in 2003

Journal Article

View and Comments on the Data Ecosystem: “Ocean of Data”

Zi-Kui Liu

Journal Article

Conception and Exploration of Using Data as a Service in Tunnel Construction with the NATM

Bowen Du, Yanliang Du, Fei Xu, Peng He

Journal Article