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| 1 | 云计算影响下的图书馆信息服务研究显示文摘云计算是分布式处理、并行处理和网格计算的发展,是一种基于互联网的超级计算模式,其基本原理为多台PC机或服务器连接成'云',终端通过'云计算'的七种服务形式来实现超级存储和超级计算,亚马逊、IBM、微软、谷歌、瑞星、阿里巴巴等已开展了对'云'的研发与服务。'云'具有较高的数据存储能力和安全性,能为图书馆提供一个泛在的能随时更新资源的信息服务平台,降低用户的信息获取成本,提高图书馆信息资源的利用率,延伸图书馆的信息服务。 | 魏志鹏 李慧佳 祖央 | 2010 | 图书馆2010，，2： | 40 |
| 2 | Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing显示文摘The rapid growth of mobile internet services has yielded a variety of computation-intensive applications such as virtual/augmented reality. Mobile Edge Computing (MEC), which enables mobile terminals to offload computation tasks to servers located at the edge of the cellular networks, has been considered as an efficient approach to relieve the heavy computational burdens and realize an efficient computation offloading. Driven by the consequent requirement for proper resource allocations for computation offloading via MEC, in this paper, we propose a Deep-Q Network (DQN) based task offloading and resource allocation algorithm for the MEC. Specifically, we consider a MEC system in which every mobile terminal has multiple tasks offloaded to the edge server and design a joint task offloading decision and bandwidth allocation optimization to minimize the overall offloading cost in terms of energy cost, computation cost, and delay cost. Although the proposed optimization problem is a mixed integer nonlinear programming in nature, we exploit an emerging DQN technique to solve it. Extensive numerical results show that our proposed DQN-based approach can achieve the near-optimal performance。 | Liang Huang Xu Feng Cheng Zhang Liping Qian Yuan Wu | 2019 | Digital Communications and Networks2019，5，1： | 25 |
| 3 | OpenRS-Cloud:A remote sensing image processing platform based on cloud computing environment显示文摘This paper explores the use of cloud computing for remote sensing image processing.The main contribution of our work is to develop a remote sensing image processing platform based on cloud computing technology(OpenRS-Cloud).This paper focuses on enabling methodical investigations into the development pattern,computational model,data management and service model exploring this novel distributed computing model.The experimental INSAR processing flow is implemented to verify the efficiency and feasibility of OpenRS-Cloud platform.The results show that cloud computing is well suited for computationally-intensive and data-intensive remote sensing services. | GUO Wei,GONG JianYa,JIANG WanShou,LIU Yi & SHE Bing State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430074,China | 2010 | Science China(Technological Sciences)2010，53，S1： | 24 |
| 4 | Blockchain: a secure, decentralized, trusted cyber infrastructure solution for future energy systems显示文摘Modern power systems are rapidly evolving into complex cyber-physical systems. The increasingly complex interaction among different energy entities calls for a secure, efficient, and robust cyber infrastructure. As an emerging distributed computing technology, Blockchain provides a secure environment to support such interactions.This paper gives a prospective on using Blockchain as a secure, distributed cyber infrastructure for the future grid.Firstly, the basic principles of Blockchain and its state-ofthe-art are introduced. Then, a Blockchain based smart grid cyber-physical infrastructure model is proposed. Afterwards, some promising application domains of Blockchain in future grids are presented. Following this, some potential challenges are discussed. | Zhaoyang DONG Fengji LUO Gaoqi LIANG | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，5： | 24 |
| 5 | Energy-Efficient Computation Offloading and Resource Allocation in Fog Computing for Internet of Everything显示文摘With the dawning of the Internet of Everything(IoE) era, more and more novel applications are being deployed. However, resource constrained devices cannot fulfill the resource-requirements of these applications. This paper investigates the computation offloading problem of the coexistence and synergy between fog computing and cloud computing in IoE by jointly optimizing the offloading decisions, the allocation of computation resource and transmit power. Specifically, we propose an energy-efficient computation offloading and resource allocation(ECORA) scheme to minimize the system cost. The simulation results verify the proposed scheme can effectively decrease the system cost by up to 50% compared with the existing schemes, especially for the scenario that the computation resource of fog computing is relatively small or the number of devices increases. | Qiuping Li Junhui Zhao Yi Gong Qingmiao Zhang | 2019 | China Communications2019，16，3： | 19 |
| 6 | A Deep Learning Based Energy-Efficient Computational Offloading Method in Internet of Vehicles显示文摘With the emergence of advanced vehicular applications, the challenge of satisfying computational and communication demands of vehicles has become increasingly prominent. Fog computing is a potential solution to improve advanced vehicular services by enabling computational offloading at the edge of network. In this paper, we propose a fog-cloud computational offloading algorithm in Internet of Vehicles(IoV) to both minimize the power consumption of vehicles and that of the computational facilities. First, we establish the system model, and then formulate the offloading problem as an optimization problem, which is NP-hard. After that, we propose a heuristic algorithm to solve the offloading problem gradually. Specifically, we design a predictive combination transmission mode for vehicles, and establish a deep learning model for computational facilities to obtain the optimal workload allocation. Simulation results demonstrate the superiority of our algorithm in energy efficiency and network latency. | Xiaojie Wang Xiang Wei Lei Wang | 2019 | China Communications2019，16，3： | 15 |
| 7 | Energy-efficient Virtual Machine Allocation Technique Using Flower Pollination Algorithm in Cloud Datacenter:A Panacea to Green Computing显示文摘Cloud computing has attracted significant interest due to the increasing service demands from organizations offloading computationally intensive tasks to datacenters.Meanwhile,datacenter infrastructure comprises hardware resources that consume high amount of energy and give out carbon emissions at hazardous levels.In cloud datacenter,Virtual Machines(VMs)need to be allocated on various Physical Machines(PMs)in order to minimize resource wastage and increase energy efficiency.Resource allocation problem is NP-hard.Hence finding an exact solution is complicated especially for large-scale datacenters.In this con text,this paper proposes an Energy-oriented Flower Pollination Algorithm(E-FPA)for VM allocation in cloud datacenter environments.A system framework for the scheme was developed to enable energy-oriented allocation of various VMs on a PM.The allocation uses a strategy called Dynamic Switching Probability(DSP).The framework finds a near optimal solution quickly and balances the exploration of the global search and exploitation of the local search.It considers a processor,storage,and memory constraints of a PM while prioritizing energy-oriented allocation for a set of VMs.Simulations performed on MultiRecCloudSim utilizing planet workload show that the E-FPA outperforms the Genetic Algorithm for Power-Aware(GAPA)by 21.8%,Order of Exchange Migration(OEM)ant colony system by 21.5%,and First Fit Decreasing(FFD)by 24.9%.Therefore,E-FPA significantly improves datacenter performance and thus,enhances environmental sustainability. | Mohammed Joda Usman Abdul Samad Ismail Hassan Chizari Gaddafi Abdul-Salaam Ali Muhammad Usman Abdulsalam Yau Gital Omprakash Kaiwartya Ahmed Aliyu | 2019 | Journal of Bionic Engineering2019，16，2： | 13 |
| 8 | Trust Access Authentication in Vehicular Network Based on Blockchain显示文摘Data sharing and privacy securing present extensive opportunities and challenges in vehicular network.This paper introducestrust access authentication scheme’as a mechanism to achieve real-time monitoring and promote collaborative sharing for vehicles.Blockchain,which can provide secure authentication and protected privacy,is a crucial technology.However,traditional cloud computing performs poorly in supplying low-latency and fast-response services for moving vehicles.In this situation,edge computing enabled Blockchain network appeals to be a promising method,where moving vehicles can access storage or computing resource and get authenticated from Blockchain edge nodes directly.In this paper,a hierarchical architecture is proposed consist of vehicular network layer,Blockchain edge layer and Blockchain network layer.Through a authentication mechanism adopting digital signature algorithm,it achieves trusted authentication and ensures valid verification.Moreover,a caching scheme based on many-to-many matching is proposed to minimize average delivery delay of vehicles.Simulation results prove that the proposed caching scheme has a better performance than existing schemes based on central-ized model or edge caching strategy in terms of hit ratio and average delay. | Shaoyong Guo Xing Hu Ziqiang Zhou Xinyan Wang Feng Qi Lifang Gao | 2019 | China Communications2019，16，6： | 10 |
| 9 | Spectral element analysis on the characteristics of seismic wave propagation triggered by Wenchuan M_s8.0 earthquake显示文摘The 2008 Wenchuan earthquake occurred in an active earthquake zone, i.e., Longmenshan tectonic zone. Seismic waves triggered by this earthquake can be used to explore the characteristics of the fault rupture process and the hierarchical structure of the Earth's interior. We employ spectral element method incorporated with large-scale parallel computing technology, to investigate the characteristics of seismic wave propagation excited by Wenchuan earthquake. We calculate synthetic seismograms with one-point source model and three-point source model respectively. The AK135 model is employed as a prototype of our numerical global Earth model. The Earth's ellipticity, Earth’s medium attenuation, and topography data are taken into consideration. These wave propagation processes are simulated by solving three-dimensional elastic wave governing equations. Three-dimensional visualization of our numerical results displays the profile of the seismic wave propagation. The three-point source, which is proposed from the latest investigations through field observation and reverse estimation, can better demonstrate the spatial and temporal characteristics of the source rupture process than the one-point source. We take comparison of synthetic seismograms with observational data recorded at 16 observatory stations. Primary results show that the synthetic seismograms calculated from three-point source agree well with the observations. This can further reveal that the source rupture process of Wenchuan earthquake is a multi-rupture process, which is composed by at least three or more stages of rupture processes. | YAN ZhenZhen ZHANG Huai YANG ChangChun SHI YaoLin | 2009 | Science China Earth Sciences2009，52，6： | 9 |
| 10 | Molecular dynamics simulation of complex multiphase flow on a computer cluster with GPUs显示文摘Compute Unified Device Architecture (CUDA) was used to design and implement molecular dynamics (MD) simulations on graphics processing units (GPU). With an NVIDIA Tesla C870, a 20-60 fold speedup over that of one core of the Intel Xeon 5430 CPU was achieved, reaching up to 150 Gflops. MD simulation of cavity flow and particle-bubble interaction in liquid was implemented on multiple GPUs using a message passing interface (MPI). Up to 200 GPUs were tested on a special network topology, which achieves good scalability. The capability of GPU clusters for large-scale molecular dynamics simulation of meso-scale flow behavior was, therefore, uncovered. | CHEN FeiGuo GE Wei LI JingHai | 2009 | Science China Chemistry2009，52，3： | 9 |
| 11 | 基于HPCC和层次分析法的高性能计算系统评价模型显示文摘HPCC(high performance computing challenge)基准是由DARPA的HPCS(high productivity computing system)项目所发布的评价高性能计算系统的测试基准程序,自推出至今,受到工业界和学术界的广泛关注.但是,HPCC仍有不尽如人意之处,主要表现在其测试结果是若干个指标项,需要测试者和决策者根据这些测试指标项进行分析和评估,缺少一个整体的、直观而统一的评价结果.提出一种基于HPCC和层次分析法的高性能计算系统评价模型——AHPCC(a high performance computer system evaluation model based on HPCC),当系统通过运行HPCC得到测试结果后,使用AHPCC模型对这些测试参数按系统应用目标建立层次结构图,并最终计算得到各系统关于特定应用目标的单一分数.以12个已测出HPCC性能参数的系统为例,使用AHPCC模型计算并分析了系统评价结果.实验结果表明,AHPCC模型提供了实际系统的统一而直观的评价指标,其评价结果符合高性能系统的设计和应用特点. | 刘川意 汪东升 | 2007 | 软件学报2007，18，4： | 9 |
| 12 | A DNA Computing Model for the Graph Vertex Coloring Problem Based on a Probe Graph显示文摘 | Jin xu Xiaoli Qiang Kai Zhang Cheng Zhang Jing Yang | 2018 | Engineering2018，4，1： | 8 |
| 13 | An Effective and Secure Access Control System Scheme in the Cloud显示文摘Cloud computing services have got rapid development in the field of the lightweight terminal, especially wireless communications. The comprehensive access control system framework is proposed for the cloud. A kind of access control scheme based on attribute encryption is designed, in which lightweight devices can safely use cloud computing resources to outsource encrypt/decrypt operations, and not worry for exposing terminal sensitive data.The scheme is verified by performance evaluation about the security, computing, storage, to ensure the legitimate interests of users in the cloud. | NIU Shaozhang TU Shanshan Huang Yongfeng | 2015 | Chinese Journal of Electronics2015，24，3： | 8 |
| 14 | A new grid-associated algorithm in the distributed hydrological model simulations显示文摘This paper presents a new grid-associated algorithm to improve the performance of a D8 algorithm based distributed hydrological model computation.The algorithm is based on the well known single-flow D8 algorithm of grid flow.This algorithm allocates calculation priorities according to the distance between the units and the outlet,then carries out the ergodic computations of the hydrological units according to the priority division.For the parallelized algorithm,a standard thread-level shared memory system for parallel programming(OpenMP-Open specifications for Multi Processing) was introduced,and the parallel coding was implemented in C lan-guage.A case study showed that the absolute speed-up ratio of the grid-associated algorithm is 1.64 over the original D8 algorithm,and the linear speed-up ratio of the parallel associated algorithm is 2.42 under 4 cores.The parallel grid-associated algorithm can be applied to a variety of research fields that use the grid method. | XU Rui1,2,HUANG XiaoXue1,LUO Lin1 & LI ShaoCai3 1 State Key Laboratory of Hydraulics and Mountain River Engineering College of Architecture and Environment,Sichuan University,Chengdu 610065,China 2 College of Electronic Engineering,Guilin University of Electronic Technology,Guilin 541004,China 3 College of Life Sciences,Sichuan University,Chengdu 610065,China | 2010 | Science China(Technological Sciences)2010，53，1： | 8 |
| 15 | An N/4 fixed-point duality quantum search algorithm显示文摘Here a fixed-point duality quantum search algorithm is proposed.This algorithm uses iteratively non-unitary operations and measurements to search an unsorted database.Once the marked item is found,the algorithm stops automatically.This algorithm uses a constant non-unitary operator,and requires N/4 steps on average(N is the number of data from the database) to locate the marked state.The implementation of this algorithm in a usual quantum computer is also demonstrated. | HAO Liang1,LIU Dan2 & LONG GuiLu1,3 1Key Laboratory for Atomic and Molecular NanoSciences and Department of Physics,Tsinghua University,Beijing 100084,China 2School of Sciences,Dalian Nationalities University,Dalian 116600,China 3Tsinghua National Laboratory for Information Science and Technology,Beijing 100084,China | 2010 | Science China(Physics,Mechanics & Astronomy)2010，53，9： | 8 |
| 16 | Stream-computing of High Accuracy On-board Real-time Cloud Detection for High Resolution Optical Satellite Imagery显示文摘This paper focuses on the time efficiency for machine vision and intelligent photogrammetry, especially high accuracy on-board real-time cloud detection method. With the development of technology, the data acquisition ability is growing continuously and the volume of raw data is increasing explosively. Meanwhile, because of the higher requirement of data accuracy, the computation load is also becoming heavier. This situation makes time efficiency extremely important. Moreover, the cloud cover rate of optical satellite imagery is up to approximately 50%, which is seriously restricting the applications of on-board intelligent photogrammetry services. To meet the on-board cloud detection requirements and offer valid input data to subsequent processing, this paper presents a stream-computing of high accuracy on-board real-time cloud detection solution which follows the “bottom-up” understanding strategy of machine vision and uses multiple embedded GPU with significant potential to be applied on-board. Without external memory, the data parallel pipeline system based on multiple processing modules of this solution could afford the “stream-in, processing, stream-out” real-time stream computing. In experiments, images of GF-2 satellite are used to validate the accuracy and performance of this approach, and the experimental results show that this solution could not only bring up cloud detection accuracy, but also match the on-board real-time processing requirements. | Mi WANG Zhiqi ZHANG Zhipeng DONG Shuying JIN Hongbo SU | 2019 | Journal of Geodesy and Geoinformation Science2019，2，2： | 7 |
| 17 | Mobile-Edge Computing Framework with Data Compression for Wireless Network in Energy Internet显示文摘Under the situations of energy dilemma, energy Internet has become one of the most important technologies in international academic and industrial areas. However, massive small data from users, which are too scattered and unsuitable for compression, can easily exhaust computational resources and lower random access possibility, thereby reducing system performance. Moreover, electric substations are sensitive to transmission latency of user data, such as controlling information. However, the traditional energy Internet usually could not meet requirements. Integrating mobile-edge computing makes energy Internet convenient for data acquisition,processing, management, and accessing. In this paper, we propose a novel framework for energy Internet to improve random access possibility and reduce transmission latency. This framework utilizes the local area network to collect data from users and makes conducting data compression for energy Internet possible. Simulation results show that this architecture can enhance random access possibility by a large margin and reduce transmission latency without extra energy consumption overhead. | Luning Liu Xin Chen Zhaoming Lu Luhan Wang Xiangming Wen | 2019 | Tsinghua Science and Technology2019，24，3： | 7 |
| 18 | Mobile Web Augmented Reality in 5G and Beyond:Challenges, Opportunities, and Future Directions显示文摘The popularity of wearable devices and smartphones has fueled the development of Mobile Augmented Reality(MAR),which provides immersive experiences over the real world using techniques,such as computer vision and deep learning.However,the hardware-specific MAR is costly and heavy,and the App-based MAR requires an additional download and installation and it also lacks cross-platform ability.These limitations hamper the pervasive promotion of MAR.This paper argues that mobile Web AR(MWAR)holds the potential to become a practical and pervasive solution that can effectively scale to millions of end-users because MWAR can be developed as a lightweight,cross-platform,and low-cost solution for end-to-end delivery of MAR.The main challenges for making MWAR a reality lie in the low efficiency for dense computing in Web browsers,a large delay for real-time interactions over mobile networks,and the lack of standardization.The good news is that the newly emerging 5G and Beyond 5G(B5G)cellular networks can mitigate these issues to some extent via techniques such as network slicing,device-to-device communication,and mobile edge computing.In this paper,we first give an overview of the challenges and opportunities of MWAR in the 5G era.Then we describe our design and development of a generic service-oriented framework(called MWAR5)to provide a scalable,flexible,and easy to deploy MWAR solution.We evaluate the performance of our MWAR5 system in an actually deployed 5G trial network under the collaborative configurations,which shows encouraging results.Moreover,we also share the experiences and insights from our development and deployment,including some exciting future directions of MWAR over 5G and B5G networks. | Xiuquan Qiao Pei Ren Guoshun Nan Ling Liu Schahram Dustdar Junliang Chen | 2019 | China Communications2019，16，9： | 7 |
| 19 | Intelligent metasurfaces:control,communication and computing显示文摘Controlling electromagnetic waves and information simultaneously by information metasurfaces is of central importance in modern society.Intelligent metasurfaces are smart platforms to manipulate the wave-information-matter interactions without manual intervention by synergizing engineered ultrathin structures with active devices and algorithms,which evolve from the passive composite materials for tailoring wave-matter interactions that cannot be achieved in nature.Here,we review the recent progress of intelligent metasurfaces in wave-information-matter controls by providing the historical background and underlying physical mechanisms.Then we explore the application of intelligent metasurfaces in developing novel wireless communication architectures,with particular emphasis on metasurface-modulated backscatter wireless communications.We also explore the wave-based computing by using the intelligent metasurfaces,focusing on the emerging research direction in intelligent sensing.Finally,we comment on the challenges and highlight the potential routes for the further developments of the intelligent metasurfaces for controls,communications and computing. | Lianlin Li Hanting Zhao Che Liu Long Li Tie Jun Cui | 2022 | eLight2022，2，1： | 7 |
| 20 | Identifying Pb-free perovskites for solar cells by machine learning显示文摘Recent advances in computing power have enabled the generation of large datasets for materials,enabling data-driven approaches to problem-solving in materials science,including materials discovery.Machine learning is a primary tool for manipulating such large datasets,predicting unknown material properties and uncovering relationships between structure and property.Among state-of-the-art machine learning algorithms,gradient-boosted regression trees(GBRT)are known to provide highly accurate predictions,as well as interpretable analysis based on the importance of features.Here,in a search for lead-free perovskites for use in solar cells,we applied the GBRT algorithm to a dataset of electronic structures for candidate halide double perovskites to predict heat of formation and bandgap.Statistical analysis of the selected features identifies design guidelines for the discovery of new lead-free perovskites. | Jino Im Seongwon Lee Tae-Wook Ko Hyun Woo Kim YunKyong Hyon Hyunju Chang | 2019 | npj Computational Materials2019，，1： | 6 |
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