A new DOA estimate algorithm for coherent sources

This paper proposed a new subspace based method to estimate the direction of arrival （DOA）. the existence of coherent sources results in the rank deficit of sample covariance matrix. Classic MUSIC（Multiple Signal Classification） can not classify coherent sources, and instead, generate an equivalent sources somewhere between them. In our method, at first, the contribution of the equiva- lent sources is subtracted by the collected data. And then, the method is recursively applied. Simulation experiment show that com- pared to the other method, this method has higher spatial resolution and less estimation error.     

Message scheduling for array re-decomposition on distributed memory systems

For many parallel applications on distributed memory systems, array re-decomposition is usually required to enhance data locality and reduce the communication overheads. How to effectively schedule messages to improve the performance of array re-decomposition has received much attention in recent years. This paper is devoted to develop efficient scheduling algorithms using the compiling information provided by array distribution patterns, array alignment patterns and the periodic property of array accesses. Our algorithms not only avoid inter-processor contention, but also reduces real communication cost and communication generation time. The experimental results show that the performance of array redecomposition can be significantly improved using our algorithms     

MIMO阵列中基于PM和降维变换的高效DOA估计算法

在这篇论文中,我们讨论MIMO阵列中的高效DOA估计方法。由于PM算法不需要对互相关矩阵进行特征值分解,也不需要对接收的数据进行奇异值分解,因此它的计算量可以显著的变小。因此MIMO阵列中基于PM算法和降维变换的DOA估计方法被提出了,而且这种提出的算法比PM算法有更低的计算复杂度。这种算法在没有频谱搜索的情况下效果很好。此外,它比PM算法的角度估计性能稍好。DOA估计中的估计误差的方差和克拉美罗界也可以导出。仿真结果验证了提出的算法的有效性。     

改善磁盘阵列性能的方法

磁盘阵列是解决计算机Ｉ／Ｏ瓶颈问题的有效方法之一，通过对现有磁盘阵列结构的研究，提出了４种改善磁盘阵列性能的方法，即良分利用磁盘带宽，平衡多盘的负载，减少奇偶检验数据存取时间和磁盘阵列Ｃａｃｈｅ技术等，分析结果表明：在事务处理应用领域，利用Ｃａｃｈｅ来把小写转化为大写可大大改善目前一般情况下，以一道数据大小来作为磁盘的基本存取大小是合适的选择，磁盘阵列负载平衡设计不足是指正常模式下系统请求在多盘间     

Collaborative signal processing for target tracking in distributed wireless sensor networks

Target tracking, especially visual target tracking, in complex situations is challenging, which is always performed in single-view system. Because of the conflict between resolution and tracking range, however, single-view tracking is not robust and accurate. This paper presents a distributed multi-view tracking system using collaborative signal processing (CSP) in distributed wireless sensor networks (DWSNs). In the proposed tracking system, target detection and classification algorithms are based on single-node processing and target tracking is performed in sink node, whereas target localization algorithm is carried out by CSP between multisensor. For conquering the disadvantages of client/server based centralized data fusion, a progressive distributed data fusion are proposed. Finally, an indoor target tracking experiment is illustrated, and then tracking performance, execution time and energy consumption of progressive distributed data fusion are compared with client/server based centralized data fusion. Experimental results demonstrate that the CSP based distributed multi-view tracking system in DWSNs can accomplish multi-target extraction, classification, localization, tracking and association quickly and accurately with little congestion, energy consumption and execution time.     

Study of OpenMP applications on the InfiniBand-based software distributed shared-memory system

For the past decades computer engineers have focused on building high-performance and large-scale computer systems with low-cost. One of the examples is a distributed-memory computer system like a cluster, where fast processing nodes to use commodity processors are connected through a high speed network. But it is not easy to develop applications on this system, because a programmer must consider all data and control dependences between processes and program them explicitly. For alleviating this problem the distributed virtual shared-memory (DVSM) system has been proposed. It is well known that the performance of the DVSM system highly depends on the network’s performance and programming semantics, and currently its performance is very limited on a conventional network. Recently many advanced hardware-based interconnection technologies have been introduced, and one of them is the InfiniBand Architecture (IBA) which supports shared-memory programming semantics by means of remote direct-memory access (RDMA) and atomic operations. In this paper, we present the implementation of our InfiniBand-based DVSM system and analyze the performance of SPEC OMP benchmarks in detail by comparing with the DVSM based on the traditional network architecture and the hardware shared-memory multiprocessor (SMP) system. As experiment result, we show that our DVSM system to use full features of the IBA can improve the performance significantly over the IPoIB-based traditional system on the IBA, and furthermore the performance of one application on the IBA-based DVSM system is better than on the hardware SMP.     

不计信源数目的修正MUSIC算法分析

在介绍MUSIC算法的基础上，分析了信源数目估计误差对MUSIC算法测向性能的影响，针对信源数日过估计下出现虚假信号和欠估计下存在谱峰消失的问题，根据阵列协方差矩阵特征分解后噪声特征值非常接近的特点，提出了一种在未知信源数日情况下进行正确DOA估计的修正MUSIC算法，计算机仿真结果证明了该算法的可行性和有效性。     

基于均匀圆阵的闭环式单基站测向算法研究

为了估算基于均匀圆阵列(UCA)的三维(3D)单基站测向(方位角、仰角和区间),提出了一种改进的适用于三维场景的闭环式算法。该算法是一种计算过程较简单的通用算法,无需使用均匀圆阵列的中心对称性,没有任何传感器数量的限制,只需要一个单独的最小平方程序用于估算基站的位置,并可以估算所有的三维测向参数。实验结果表明,相比多种类似算法,所提算法的性能可与三维MUSIC算法的性能相媲美,且计算复杂度更低,实现速度更快。     

A DSS for distributed computer system design in the presence of multiple conflicting objectives

The design of distributed computer systems (DCS) requires compromise among several desirable and conflicting objectives. Design tools for this purpose should, therefore, facilitate the process of making such tradeoffs. To this end, this paper presents a prototype Decision Support System (DSS) which uses multicriteria decisions making techniques as the underlying methodology to aid the designer in making compromises in a systematic and efficient manner.While there are several isolated subproblems of DCS design that can be modelled and solved quantitatively, there are also, many design aspects that are difficult to quantify and/or formalize. Thus the design process requires a synthesis of analytic model execution and informed judgement on the part of the designer. The DSS aids in this iterative process by executing appropriate models and generating a sequence of ‘Pareto-optimal’ or non-dominated set of solution vectors. The relatively unstructured task of making tradeoffs among the components of each vector is left in the hands of the designer. Efficiency is achieved by avoiding needles search through clearly inferior solutions and focusing on non-dominated ones only. Various details of the prototype, implemented on a UNIVAC 1100 and an IBM PC AT, are highlighted in an example session. The potential advantages of using multicriteria techniques as opposed to the widespread practice of using single criteria optimization methods are also noted in this paper.     

阵列信号处理中基于MUSIC算法的空间谱估计

阐述了阵列信号处理中广泛采用的用于来波方向(DOA)估计的多信号分类(MUSIC)算法原理,理论分析了算法的实现过程,并结合Matlab实验,从理论和系统仿真两方面证明将此法用于确定目标方位角的实用价值,是一种有效的测量目标方位角的方法。     

Improving the predictability of distributed stream processors

Next generation real-time applications demand big-data infrastructures to process huge and continuous data volumes under complex computational constraints. This type of application raises new issues on current big-data processing infrastructures. The first issue to be considered is that most of current infrastructures for big-data processing were defined for general purpose applications. Thus, they set aside real-time performance, which is in some cases an implicit requirement. A second important limitation is the lack of clear computational models that could be supported by current big-data frameworks. In an effort to reduce this gap, this article contributes along several lines. First, it provides a set of improvements to a computational model called distributed stream processing in order to formalize it as a real-time infrastructure. Second, it proposes some extensions to Storm, one of the most popular stream processors. These extensions are designed to gain an extra control over the resources used by the application in order to improve its predictability. Lastly, the article presents some empirical evidences on the performance that can be expected from this type of infrastructure.     

Minimisation of the update response time in a distributed database system

This paper is concerned with the minimisation of the update response time in distributed database systems (DDBS) where resequencing algorithms are used to preserve the consistency of the databases. The authors proposed a novel resequencing technique, in reference [7], namely hop-by-hop resequencing with batch processing for connecting the first stage to the second stage of a two-stage DDBS. In this paper, a stochastic upper bound is calculated for the system response time and it is shown that the system response is smaller than that for a one-stage system of the same size and parameters.     

The performance of the Amoeba distributed operating system

Amoeba is a capability-based distributed operating system designed for high-performance interactions between clients and servers using the well-known RPC model. The paper starts out by describing the architecture of the Amoeba system, which is typified by specialized components such as workstations, several services, a processor pool, and gateways that connect other Amoeba systems transparently over wide-area networks. Next the RPC interface is described. The paper presents performance measurements of the Amoeba RPC on unloaded and loaded systems. The time to perform the simplest RPC between two user processes has been measured to be 1-4 ms. Compared to SUN 3/50's RPC, Amoeba has one ninth of the delay, and over three times the throughput. Finally we describe the Amoeba file server. The Amoeba file server is so fast that it is limited by the communication bandwidth. To the best of our knowledge this is the fastest file server yet reported in the literature for this class of hardware.     

Retrieving multiple light sources in the presence of specular reflections and texture

Recovering multiple point light sources from a sparse set of photographs in which objects of unknown texture can move is challenging. This is because both diffuse and specular reflections appear to slide across surfaces, which is a well known physical fact. What is seldom demonstrated, however, is that it can be taken advantage of to address the light source recovery problem. In this paper, we therefore show that, if approximate 3D models of the moving objects are available or can be computed from the images, we can solve the problem without any a priori constraints on the number of sources, on their color, or on the surface albedos.Our approach involves finding local maxima in individual images, checking them for consistency across images, retaining the apparently specular ones, and having them vote in a Hough-like scheme for potential light source directions. The precise directions of the sources and their relative power are then obtained by optimizing a standard lighting model. As a byproduct we also obtain an estimate of various material parameters such as the unlighted texture and specular properties.We show that the resulting algorithm can operate in presence of arbitrary textures and an unknown number of light sources of possibly different unknown colors. We also estimate its accuracy using ground-truth data.     

Mirage+: A kernel implementation of distributed shared memory on a network of personal computers

We describe the evolution of a distributed shared memory (DSM) system, Mirage, and the difficulties encountered when moving the system from a Unix-based* kernel on the VAX to a Unix-based kernel on personal computers. Mirage provides a network transparent form of shared memory for a loosely coupled environment. The system hides network boundaries for processes that are accessing shared memory and is upward compatible with the Unix System V Interface Definition. This paper addresses the architectural dependencies in the design of the system and evaluates performance of the implementation. The new version, MIRAGE +, performs well compared to Mirage even though eight times the amount of data is sent on each page fault because of the larger page size used in the implementation. We show that performance of systems with a large page size to network packet size can be dramatically improved on conventional hardware by applying three well-known techniques: packet blasting, compression, and running at interrupt level. The measured time for a page fault in MIRAGE + has been reduced 37 per cent by sending a page using packet blasting instead of using a handshake for each portion of the page. When compression was added to MIRAGE +, the time to fault a page across the network was further improved by 47 per cent when the page was compressed into one network packet. Our measured performance compares favorably with the amount of time it takes to fault a page from disk. Lastly, running at interrupt level may improve performance 16 per cent when faulting pages without compression.     

基于阵列的盲信号处理研究和应用

本文对比了阵列信号处理与盲信号处理的数学模型,分析了二者的特点并进行了综合统一,提出了基于信号的非二阶特性空间扫描的概念,并验证了信号峰度随信噪比条件的变化和基于峰度的空间扫描。针对采用民用广播电台信号的外辐射源雷达所面临的严重同频干扰问题,采用独立成分分析的方法进行干扰抑制,并进行了实测数据的验证。     

Block rank sparsity-aware DOA estimation with large-scale arrays in the presence of unknown mutual coupling

With the development of massive multiple-input mutiple-output (MIMO) technique, high-resolution direction-of-arrival (DOA) estimation has attracted great attention. A novel sparse signal reconstruction method based on the inherent block rank sparsity of the sub-matrix is proposed for high resolution DOA estimation with large-scale arrays under the condition of unknown mutual coupling. In the proposed method, by taking advantage of the banded symmetric Toeplitz structure of the mutual coupling matrix (MCM), a novel block representation model is firstly formulated by parameterizing the steering vector. Then, exploiting the inherent block sparsity characteristics of the sub-matrix, a reweighted nuclear norm minimization algorithm is proposed to reconstruct the sparse matrix, in which the weighted matrix is designed by using the spectrum of MUSIC-Like algorithm. Finally, the DOAs are achieved by searching the non-zeros blocks of the recovered matrix. The proposed method not only makes full use of the block rank sparsity characteristics of the sub-matrix and weighted matrix for enhancing the sparse solution, but also avoids the array aperture loss. Thus, the proposed method has superior estimation performance than the state-of-the-art algorithms under the condition of unknown mutual coupling. Especially, in the case of large-scale antennas, the advantage of the proposed method is more obvious. Some computer simulation results are performed to verify the advantage of our proposed method.     

Performance evaluation of bag of gangs scheduling in a heterogeneous distributed system

Distributed systems deliver a cost-effective and scalable solution to the increasing performance intensive applications by utilizing several shared resources. Gang scheduling is considered to be an efficient time-space sharing scheduling algorithm for parallel and distributed systems. In this paper we examine the performance of scheduling strategies of jobs which are bags of independent gangs in a heterogeneous system. A simulation model is used to evaluate the performance of bag of gangs scheduling in the presence of high priority jobs implementing migrations. The simulation results reveal the significant role of the implemented migration scheme as a load balancing factor in a heterogeneous environment. Another significant aspect of implementing migrations presented in this paper is the reduction of the fragmentation caused in the schedule by gang scheduled jobs and the alleviation of the performance impact of the high priority jobs.     

The impact of distributed programming abstractions on application energy consumption

With battery capacities remaining a key physical constraint for mobile devices, energy efficiency has become an important software design consideration. Distributed programming abstractions (e.g., sockets, RPC, messages, etc.) are an essential component of modern software, but their energy consumption characteristics are poorly understood. The programmer has few practical guidelines to choose the right abstraction for energy-constrained scenarios. In this article, we report on the findings of a systematic study we conducted to compare and contrast major distributed programming abstractions in terms of their energy consumption patterns. By varying the abstractions with the rest of the functionality fixed, we measure and analyze the impact of distributed programming abstractions on application energy consumption. Based on our findings, we present a set of practical guidelines for the programmer to select an abstraction that satisfies the energy consumption constraints in place. Our other guidelines can steer future efforts in creating energy efficient distributed programming abstractions.     

Noncircularity-exploitation in direction estimation of noncircular signals with an acoustic vector-sensor

The main motivation of using an acoustic vector-sensor in direction-of-arrival (DOA) estimation applications has been its unambiguous two-dimensional directivity, insensitivity to the range of sources, and independence of signal frequency. The main objection lies in its lack of geometry-redundancy and limited degree of freedom. Four thus emerged challenging tasks and the corresponding solutions by recurring to the redundancies in the nonvanishing conjugate correlations of noncircular signals are described in the paper: (1) fulfilling source decorrelation in a multipath propagation environment; (2) enhancing processing capacity to accommodate more signals; (3) suppressing colored-noise with unknown covariance structure; and (4) deriving closed-form approaches to avoid iteration and manifold storage. Simulation experiments are carried out to examine the associated DOA estimators termed as: (1) phase-smoothing MUSIC (multiple signal classification); (2) virtual-MUSIC; (3) conjugate-MUSIC; and (4) noncircular-ESPRIT (estimation of signal parameters via rotational invariance techniques), respectively.