面向多雷达数据融合的并行数据编排框架研究

在多雷达数据融合中,数据编排方式是多雷达组网系统成败的关键因素之一。随着数据融合系统中处理容量的迅速增长,串行数据编排融合框架已经不能满足多雷达组网需求。文中针对大容量数据融合系统提出了一种并行数据编排框架,使用OpenMP 并行技术进行了实现。仿真结果表明,并行数据编排框架相比较于串行处理方式具有较高的加速比,实时性高,满足了大规模多雷达组网的需求,并且具有良好的扩展性。     

一种流数据立方体分析挖掘框架

流数据是目前一种重要的数据展现形式,对流数据进行OLAM(联机分析挖掘)操作可为分析人员提供多层次的数据视图。但OLAM要求在不同粒度中实现对数据的聚合操作,而流式数据内含时态特性和持续到达特性,使得数据无法被多次重复操作。使用传统OLAP(联机分析处理)方法无法生成部分物化视图且流数据规模宏大,受限于存储空间大小而无法保存全部数据单元信息。针对上述问题,提出了一种基于概要技术的流数据OLAM框架——sketch cube(概要立方体),该框架把任意维度组合映射成唯一自然数,根据上下限单调原则对维度组合裁剪,在类线性空间中保存有效数据单元信息,并构建时间序列索引提高检索效率。通过理论分析给出使用sketch cube的前提条件,同时通过真实海量流数据实验分析表明,sketch sube在有效性、存储空间效率和正确率上可以满足实时挖掘的需求。     

基于移动Agent的无线传感器网络数据管理框架

无线传感器网络是一种全新的技术,能够广泛应用于恶劣环境和军事领域。传感器网络在数据获取过程中,为了减少数据的处理耗能、降低延迟,需要采用数据管理技术。分析和介绍了传感器网络集中式与分布式处理两种数据管理模型结构,提出了一种基于移动Agent的无线传感器网络数据管理框架。     

Dynamic Data Migration in Hybrid Main Memories for In‐Memory Big Data Storage

For memory‐based big data storage, using hybrid memories consisting of both dynamic random‐access memory (DRAM) and non‐volatile random‐access memories (NVRAMs) is a promising approach. DRAM supports low access time but consumes much energy, whereas NVRAMs have high access time but do not need energy to retain data. In this paper, we propose a new data migration method that can dynamically move data pages into the most appropriate memories to exploit their strengths and alleviate their weaknesses. We predict the access frequency values of the data pages and then measure comprehensively the gains and costs of each placement choice based on these predicted values. Next, we compute the potential benefits of all choices for each candidate page to make page migration decisions. Extensive experiments show that our method improves over the existing ones the access response time by as much as a factor of four, with similar rates of energy consumption.     

一种有效降低误差扩散的数据分割方法

提出一种有效降低误差扩散的数据分割方法.该方法改进了H.264划分子流的做法,采用当前编码宏块被错误解码时对下一编码帧产生的误差扩散程度来判别该宏块的优先级,以此划分不同的传输子流.在给定网络带宽和丢包率的情况下,采用率失真优化的码率分配算法对不同传输子流分别施以不同的信道编码保护力度,以保证在相同传输条件下,优先级高的宏块被正确接收的概率最大化,使重建视频流的质量达到最优.该方法实现简单,对宏块的分类更加合理,有效降低了由于包丢失引起的误差扩散效应,改善了重建视频的质量.实验结果表明在相同的带宽和丢包率条件下,本文方法比H.264方法提高视频接收质量大约0.3~0.6dB.     

A Service Management Framework for M-Commerce Applications

Mobile commerce (m-commerce) refers to an ability to conduct wireless commerce transactions using mobile applications in mobile devices. M-commerce applications can range from as simple as an address book synchronization to as complicated as credit card transactions. M-commerce is expected to grow dramatically in the near future supporting simple to complex commerce transactions. Even though the Wireless Application Protocol (WAP) is designed to facilitate the development of wireless applications, it will not be sufficient to handle complex business transactions that require cooperation of different service applications. In order to handle these complex mobile commerce transactions efficiently, an intelligent, robust and scalable framework that provides diverse m-commerce services is required. This paper describes in detail such an m-commerce framework based on the Java Intelligent Network Infrastructure (JINI) and Wireless Applications Protocol (WAP).     

A Prototype Processing-In-Memory (PIM) Chip for the Data-Intensive Architecture (DIVA) System

The Data-Intensive Architecture (DIVA) system employs Processing-In-Memory (PIM) chips as smart-memory coprocessors. This architecture exploits inherent memory bandwidth both on chip and across the system to target several classes of bandwidth-limited applications, including multimedia applications and pointer-based and sparse-matrix computations. The DIVA project has built a prototype development system using PIM chips in place of standard DRAMs to demonstrate these concepts. We have recently ported several demonstration kernels to this platform and have exhibited a speedup of 35X on a matrix transpose operation.This paper focuses on the 32-bit scalar and 256-bit WideWord integer processing components of the first DIVA prototype PIM chip, which was fabricated in TSMC 0.18 m technology. In conjunction with other publications, this paper demonstrates that impressive gains can be achieved with very little smart logic added to memory devices. A second PIM prototype that includes WideWord floating-point capability is scheduled to tape out in August 2003.Jeffrey Draper is a Research Assistant Professor in the Department of Electrical Engineering at the University of Southern California. He holds this appointment in conjunction with a Project Leader position at the Information Sciences Institute of the University of Southern California. Dr. Drapers research group has participated in many DARPA-sponsored large-scale VLSI development efforts. He is a member of the IEEE Computer Society and has conducted research in the areas of processing-in-memory architectures, thermal management, VLSI, interconnection networks, and modeling/performance evaluation. Dr. Draper received a BSEE from Texas A&M University and an MS and PhD from the University of Texas at Austin.J. Tim Barrett is a Senior Electrical Engineer at the Information Sciences Institute of the University of Southern California. Mr. Barrett has managed, designed and implemented the hardware, low-level software and integration of many computer systems. Applications of these systems include scalable supercomputers at USC Information Sciences Institute, the long distance telephone switch at AT&T Bell Labs, building energy management at Barber-Colman Company, and laser entertainment performance instruments at Aura Technologies and Laser Images Inc. He is a member of IEEE Solid State Circuits Society and received his MSCS from the University of Illinois Chicago and BSEE from the University of Iowa.Jeff Sondeen is a Research Associate at the Information Sciences Institute of the University of Southern California, where he supports and maintains CAD technology files, libraries, and tools for implementing VLSI designs. Previously he has worked at Silicon Compilers and Hewlett-Packard in CAD tool and test chip development. He received an MSEE from the University of Michigan.Sumit Mediratta is currently pursuing a PhD in Electrical Engineering at the University of Southern California. He received a Bachelor of Engineering degree in Electronics and Telecommunication from the Shri Govind Ram Sekseria Institute of Technology and Science, India. His research interests include interconnection networks, VLSI, processing-in-memory architectures, high-speed data communication and synchronization techniques and network interfaces for high-performance architectures.Chang Woo Kang received a BS in electrical engineering from Chung-ang University, Seoul, South Korea, in 1997 and an MS in electrical engineering from the University of Southern California, Los Angeles, in 1999. He is currently pursuing a PhD in electrical engineering at the University of Southern California. His research includes VLSI system design and algorithms for low-power logic synthesis and physical design.Ihn Kim is a PhD student in the Department of Electrical Engineering at the University of Southern California. He is also a Staff Engineer at QLogic. His research interests include user-level network interface, network processor architectures, and modeling/performance evaluation of system area networks. He is a member of the IEEE Computer Society. He received an MS at KAIST (Korea Advanced Institute of Science and Technology).Gokhan Daglikoca is an Application Engineer at Cadence Design Systems, Inc, where he specializes in High-Performance ASIC and Microprocessor Design Methodologies. He is a member of IEEE. Gokhan Daglikoca received a BS from Istanbul Technical University and an MS from the University of Southern California.     

利用VC++实现GPS全球定位系统定位数据的提取

随着计算机技术、通信技术和信息技术的不断发展。各个行业已逐渐认识到了利用这些高新技术来实现高速采集、处理数据和精简工作任务的巨大潜力。美国建立的全球定位系统作为一种精密的授时、测距、导航、定位系统，已经开始在军事、交通等领域得到越来越广泛的应用。但如何将GPS技术与现代计算机技术有效地结合起来，以实现快速、准确的定位，始终是研究的热点问题。本文提出了一种在VC^ 环境下，实现对GPS全球定位系统定位信息的接收以及对各定位参数数据的提取。     

Methodology for Refinement and Optimisation of Dynamic Memory Management for Embedded Systems in Multimedia Applications

In multimedia applications, run-time memory management support has to allow real-time memory de/allocation, retrieving and processing of data. Thus, its implementation must be designed to combine high speed, low power, large data storage capacity and a high memory bandwidth. In this paper, we assess the performance of our new system-level exploration methodology to optimise the memory management of typical multimedia applications in an extensively used 3D reconstruction image system [1, 2]. This methodology is based on an analysis of the number of memory accesses, normalised memory footprint¹ and energy estimations for the system studied. This results in an improvement of normalised memory footprint up to 44.2% and the estimated energy dissipation up to 22.6% over conventional static memory implementations in an optimised version of the driver application. Finally, our final version is able to scale perfectly the memory consumed in the system for a wide range of input parameters whereas the statically optimised version is unable to do this.The original version of this paper first appeared in the Proceedings of Signal Processing Systems 2003.Marc Leeman has as professional research interests hardware/software co-design, code optimisation in general and optimisation of dynamic data types and dynamic memory management for low power embedded systems in particular. Personal interests include Open and Free software development, software configuration and GNU/Debian package maintenance. He received an engineering degree, a master in artificial intelligence and a Ph.D. in electrical engineering in 1997, 1998 and 2004 respectively, all at the K.U. Leuven. He is a member of the IEEE Computer Society. Currently, he works as an R&D Engineer for Barco Control-rooms Division (BCD) on hardware/software co-design for streaming video products.David Atienza received the M.Sc. degree in Computer Sciences from the Complutense University of Madrid (UCM), Spain in 2001. Since then he has joined the Department of Computer Architecture and Automation of Complutense University of Madrid as a sandwich Ph.D. student half-time at the Inter-university Micro-Electronics Centre (IMEC), Heverlee, Belgium. His research interests include optimisation of dynamic memory management on multimedia and wireless network applications for low power and high performance embedded systems, computer architecture and high-level design automation.Geert Deconinck is Associate Professor (hoofddocent) at the K.U. Leuven (Belgium) since 2003 and staff member of the research group ELECTA (Electrical Energy and Computing Architectures). His research interests include the design and assessment of software-based solutions to meet dependability, real-time, and cost constraints for embedded systems. In this field, he has authored and co-authored more than 120 publications in international journals and conference proceedings. He received his M.Sc. in Electrical Engineering and his Ph.D. in Applied Sciences from the K.U. Leuven, Belgium in 1991 and 1996 respectively. He was a visiting professor (bijzonder gastdocent) at the K.U. Leuven in 1999–2003. - Flanders (Belgium) in the period 1997–2003.Vincenzo De Florio received his MSc degree in computer science in 1987 and his PhD degree in engineering in 2000, respectively from the University of Bari, Italy, and the University of Leuven, Belgium. He is currently post-doctoral researcher at the University of Antwerp, where he is doing research on adaptive and dependable mobile applications. Previously he had been researcher and lecturer with Tecnopolis/SASIAM (ECMI School for Advanced Studies in Industrial and Applied Mathematics) and member of Tecnopolis/Robotic lab, where he was responsible for design of parallel robotic vision applications. Currently he is also a reviewer for several conferences and for the Journal of System Architectures.José M. Mendías received the M.Sc. and Ph.D. degrees in physics from the Complutense University of Madrid in 1992 and 1998, respectively. He joined the Department of Computer Architecture and Systems Engineering, Complutense University in 1992 as a lecturer, and became an associate professor in 2001. Since 2002, he is Vice-dean of the Computer Science Faculty at the same University. His current research interests include design automation, computer architecture and formal methods.Chantal Ykman-Couvreur is born in 1956. She received the mathematics degree from the Facultes Universitaires Notre-Dame de la Paix of Namur in 1979. She first worked at PHILIPS Research Laboratory of Belgium, from 1979 until 1991. Her main activities were concentrated on information theory and coding, cryptography and multi-level logic synthesis for VLSI circuits. Then, she joined IMEC, where she was responsible at IMEC for the dynamic memory management and the system-level design flow in the Matisse compiler for network protocol components (ATM, Internet Protocol, etc). Currently, she works on the task concurrency management design flow in the Matador project.Francky Catthoor received the engineering degree and a Ph.D. in electrical engineering from the Katholieke Universiteit Leuven, Belgium in 1982 and 1987 respectively. Since 1987, he has headed several research domains in the area of high-level and system synthesis techniques and architectural methodologies, all within the Design Technology for Integrated Information and Telecom Systems (DESICS—formerly VSDM) division at the Inter-university Micro-Electronics Centre (IMEC), Heverlee, Belgium. Currently he is an IMEC fellow. He is part-time full professor at the EE department of the K.U. Leuven.In 1986 he received the Young Scientist Award from the Marconi International Fellowship Council. He has been associate editor for several IEEE and ACM journals, like Transactions on VLSI Signal Processing, Transactions on Multi-media, and ACM TODAES. He was the program chair of several conferences including ISSS97 and SIPS01.Rudy Lauwereins is vice-president of IMEC, Belgiums Interuniversity Micro-Electronic Centre, which performs research and development, ahead of industrial needs by 3 to 10 years, in microelectronics, nano-technology, enabling design methods and technologies for ICT systems. He leads the DESICS division of 185 researchers, currently focused on the development of re-configurable architectures, design methods and tools for wireless and multimedia applications. He is also a part-time Professor at the Katholieke Universiteit Leuven, Belgium. He had obtained a Ph.D. in Electrical Engineering in 1989. Rudy Lauwereins served in numerous international program committees and organisational committees, and gave many invited and keynote speeches. He is vice-chair of the board of DSP Valley and member of the board of several spin-off companies. He is a senior member of the IEEE.     

移动互联网流量经营数据分析与案例研究

针对电信业进入3G时代的经营特点和现状,本文提出流量经营是当前发展3G业务的关键.研究了支撑流量经营的数据分析方法,并结合实际应用案例,通过数据挖掘探析流量经营蕴涵的附加价值,为国内电信运营商建立有效的流量经营模式提供了参考.     

不确定数据流自适应并行连接算法及应用

不确定数据流对处理过程有独特的需求,如存储空间有限、响应时间很短、需要连续处理、数据无限等,这对数据流的处理算法,特别是耗时、耗内存较多的连接操作提出了挑战。针对大规模不确定数据流并行连接所存在的速度较慢和内存消耗大的问题,提出了多核处理器上不确定数据流并行连接和内存溢出时自适应处理的一系列算法,能够高速在线处理并发不确定数据流。在此基础上,针对道路各个卡口监控到的不确定数据流,提出一种实时发现套牌车的方法。实验采用真实数据、均匀数据、高斯数据进行评估,证明算法具有良好的性能,其处理速度比内存数据库Timesten速度提高2~8倍,能够满足实时交通套牌车监控的需求。     

An Algorithm of Programming Data Flow Analysis Based on Data Flow Expresion

１ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅｓｔａｔｅｍｅｎｔｓｉｎｐｒｏｇｒａｍｓｈａｖｅｔｈｒｅｅｋｉｎｄｓｏｆｉｎｆｌｕｅｎｃｅｓｏｎｖａｒｉａｂｌｅｓｔｏｔａｌｙ：ｄｅｆｉｎｉｎｇｖａｒｉａｂｌｅｓ，ｍａｋｉｎｇｔｈｅｖａｒｉａｂｌｅｓｈａｖｅｄｅｆｉｎ...     

基于Visual C++的惯性导航数据采集系统

针对光纤陀螺惯性导航系统开发了一套基于VC平台的数据采集系统,包括串口通信、数据存储和实时显示3个主要功能模块.串口通信模块中利用Visual C++的MSComm控件实现了光纤陀螺惯性导航系统与PC机的串口通信;在数据存储和实时显示模块中实现了光纤陀螺惯性导航系统输出的加速度、角速度和姿态数据的自动存储与实时显示.该系统经过多次测试,性能稳定可靠,可用于工程实践中.     

一种视频编码数据分割方案

数据分割是在无线移动信道等传输视频码流时用于抵御信道误码、提高编码比特流健壮性的一种机制.在对现在流行的视频编码标准中数据分割方案进行研究的基础上,文中提出了一种视频编码中数据分割的新方案.在该方案中,运动矢量信息和头信息分割于不同部分;而且运动矢量的水平和垂直分量也可以分割到不同的部分,从而可以更好地抵御信道误码.在这种分割方案下,又提出了可以改进运动矢量编码效率的新编码方法.实验表明该方法对具有尖峰概率密度函数的情形尤为有效.采用文中数据分割方案具有抗信道误码能力强、运动矢量编码比特位数少、编码效率高等优点.     

大数据技术的应用现状与展望

梳理了大数据研究的4项关键技术:“数据的采集、预处理与存储”、“数据的分析与挖掘”、“数据的隐私保护”、“数据中心体系结构”,挖掘和展示了国内外大数据研究的热点,以期对该领域的研究有一个系统而全面的认识.从处理平台、分析产品、标准化3个方面介绍了大数据技术应用的现状,并列举了大数据现有的产品应用及各行业应用案例.最后,从大数据的分析策略、深度学习、隐私保护和数据质量几个方面揭示了大数据研究存在的挑战和机遇,以期为后续大数据技术应用的发展提供参考.     

一种实时可靠的视频交通流量检测方法

讨论了一种基于视频的交通流量统计方法,提出了相应的算法.采用叠加平均的方法从一系列图像序列中提取出静止背景,并通过减背景的方法提取出运动车辆并对其进行相应的处理,然后用聚类分析的方法对其进行车辆计数分析,并对背景进行自适应更新.实验证明该方法具有较好的性能,满足实时性处理的要求,稳定性较高.     

云数据安全研究进展

云数据安全问题是制约云计算发展的重要因素之一.该文综述了云数据安全方面的研究进展,将云数据安全所涉及的云身份认证、云访问控制、云数据安全计算、虚拟化安全技术、云数据存储安全、云数据安全删除、云信息流控制、云数据安全审计、云数据隐私保护及云业务可持续性保障10方面相关研究工作纳入到物理资源层、虚拟组件层及云服务层所构成的云架构中进行总结和分析;并给出了相关技术的未来发展趋势.     

云数据安全研究进展

云数据安全问题是制约云计算发展的重要因素之一。该文综述了云数据安全方面的研究进展,将云数据安全所涉及的云身份认证、云访问控制、云数据安全计算、虚拟化安全技术、云数据存储安全、云数据安全删除、云信息流控制、云数据安全审计、云数据隐私保护及云业务可持续性保障10方面相关研究工作纳入到物理资源层、虚拟组件层及云服务层所构成的...     

A Distributed In-Memory Database Solution for Mass Data Applications

In this paper, a Distributed In-Memory Database (DIMDB) system is proposed to improve processing efficiency in mass data applications. The system uses an enhanced language similar to Structured Query Language (SQL) with a key-value storage schema. The design goals of the DIMDB system is described and its system architecture is discussed. Operation flow and the enhanced SQL-like language are also discussed, and experimental results are used to test the validity of the system.     

数据仓库在PHS网络质量分析中的应用

将数据仓库技术运用在小灵通网络质量分析中,能深层次地挖掘、分析当前和小灵通历史的业务数据以及相关环境数据,自动快速获取其中有用的网络质量信息,提供快速、准确和便捷的决策支持数据,有目的的采取优化手段、优化网络质量,提高小灵通网络的运行质量、用户满意度和小灵通网络的经济效益。