BAAQ: an infrastructure for application integration and knowledge discovery in bioinformatics.

The emerging grid computing technologies enable bioinformatics scientists to conduct their researches in a virtual laboratory, in which they share public databases, computational tools as well as their analysis workflows. However, the development of grid applications is still a nightmare for general bioinformatics scientists, due to the lack of grid programming environments, standards and high-level services. Here, we present a system, which we named Bioinformatics: Ask Any Questions (BAAQ), to automate this development procedure as much as possible. BAAQ allows scientists to store and manage remote biological data and programs, to build analysis workflows that integrate these resources seamlessly, and to discover knowledge from available resources. This paper addresses two issues in building grid applications in bioinformatics: how to smoothly compose an analysis workflow using heterogeneous resources and how to efficiently discover and re-use available resources in the grid community. Correspondingly an intelligent grid programming environment and an active solution recommendation service are proposed. Finally, we present a case study applying BAAQ to a bioinformatics problem.     

Exploring microbial genome sequences to identify protein families on the grid.

The analysis of microbial genome sequences can identify protein families that provide potential drug targets for new antibiotics. With the rapid accumulation of newly sequenced genomes, this analysis has become a computationally intensive and data-intensive problem. This paper describes the development of a Web-service-enabled, component-based, architecture to support the large-scale comparative analysis of complete microbial genome sequences and the subsequent identification of orthologues and protein families (Microbase). The system is coordinated through the use of Web-service-based notifications and integrates distributed computing resources together with genomic databases to realize all-against-all comparisons for a large volume of genome sequences and to present the data in a computationally amenable format through a Web service interface. We demonstrate the use of the system in searching for orthologues and candidate protein families, which ultimately could lead to the identification of potential therapeutic targets.     

网格技术在视频会议系统中的应用初探

网格(Grid)是近年来兴起的一个研究热点。他旨在使互联网上所有资源(计算资源、存储资源、通信资源、软件资源、信息资源、知识资源等)实现全面共享与协同工作，使整个因特网整合成一台巨大的超级计算机，为用户提供一个有效的平台，支持全球范围内分布异构应用程序的运行。本文不仅介绍了网格技术的涵义、特．最、功能，并且从网格技术能支持异构结点在网络环境下的分布动态协同工作的角度出发，给出了基于网格平台的通用视频会议系统的设计构想。     

An Efficient Dynamic Integration Middleware for Cyber-Physical Systems in Mobile Environments

Advances in information technologies have brought a wide variety of computing environments. In recent years, integrations of computational, networking, and physical elements in different environments tend to increase, so interoperability between heterogeneous computing elements has become a key area of research. A cyber-physical system (CPS) that has gained a lot of attention lately is a tight integration of the system’s computational and physical elements. The CPS technology builds on the older discipline of embedded systems, and CPS applications can be found in diverse industry sectors, such as smart home, health care, and transportation. There is a high possibility that a global CPS network that integrates different CPS networks appears in the near future. This paper proposes a CPS middleware framework that ensures interoperability and communication between heterogeneous components in a global CPS network. Through local and global communications, the proposed middleware makes mobile devices in different networks interoperable. It employs Internet Protocol version 6 (IPv6) and performs protocol conversion to communicate with devices using different protocols.     

Building Grid Portal Applications From a Web Service Component Architecture

This work describes an approach to building Grid applications based on the premise that users who wish to access and run these applications prefer to do so without becoming experts on Grid technology. We describe an application architecture based on wrapping user applications and application workflows as Web services and Web service resources. These services are visible to the users and to resource providers through a family of Grid portal components that can be used to configure, launch, and monitor complex applications in the scientific language of the end user. The applications in this model are instantiated by an application factory service. The layered design of the architecture makes it possible for an expert to configure an application factory service with a custom user interface client that may be dynamically loaded into the portal.     

How will bioinformatics impact signal processing research?

Biomedical research once involved building complex theories upon relatively small amounts of experimental data. The field of bioinformatics has posed many computational problems (bioinformatics can be broadly defined as the interface between biology and computational sciences). The field has stimulated synergetic research and development of state-of-the-art techniques in the areas of data mining, statistics, imaging/pattern analysis, and visualization. By applying these techniques to gene and protein sequence information embedded in biological systems. Signal processing (SP) techniques have been applied most everywhere in bioinformatics and will continue to play an important role in the study of biomedical problems. The goal of this article is to demonstrate to the SP community the potential of SP tools in uncovering complex biological phenomena.     

Intelligent Monitoring for Adaptation in Grid Applications

Grid applications access distributed, and often shared, resources. One consequence of this resource sharing is that measured application performance can vary widely and in unexpected ways. Determining the causes of poor performance, due to either anomalous application behavior or contention for shared resource use, and adapting to changing circumstances are critical to creation of robust Grid applications. Performance contracts and real-time adaptive control are two mechanisms to realize soft performance guarantees in Grid environments. Performance contracts formalize the relationship between application performance needs and resource capabilities. During execution, contract monitors use performance data to verify that expectations are met. When the contracted specifications are not satisfied, the system can choose to either adapt the application to available resources or reschedule the application on a new set of resources that can satisfy the original contract specifications. We describe an infrastructure for Grid application contract development and monitoring. This infrastructure, based on the Autopilot toolkit, provides flexible and scalable tools to assess both application and system behavior.     

Virtual Computing Infrastructures for Nanoelectronics Simulation

The operational principles, components, and organization of a Grid-computing infrastructure called In-VIGO (standing for In Virtual Information Grid Organizations)are described. In-VIGO enables computational engineering and science in virtual information Grid organizations. Its distinctive feature is the extensive use of virtualization technologies to provide secure execution environments as needed by tools and users. This paper reviews and motivates the requirements of a cyber infrastructure for computational nanoelectronics. It then explains how such requirements are addressed by the In-VIGO middleware approach, which uses virtualized resources to build computational Grids. The architecture and key design aspects of its first deployed version-In-VIGO 1.0-are presented. It is operational and currently being used to enable the use of computational electronics tools over the Web. Aspects of the design and architecture of the next version of In-VIGO are also presented. It uses Web services standards and components, and lessons learned from In-VIGO 1.0.     

Component-based waveform development: the Nucleus tool flow for efficient and portable software defined radio

With the advent of multi-processor systems on chip (MPSoCs) and due to the complexity and variety of modern wireless standards, academia and industry are moving towards software defined radio (SDR) solutions. It is the goal of the SDR approach to allow designers to describe a radio standard or waveform by means of a high level language. This allows faster waveform development cycles and makes it easier to migrate waveforms across different platforms. Out of many software paradigms, component-based software engineering (CBSE) is an attractive match for SDR, especially for baseband applications. It abstracts waveforms in the traditional way algorithm designers think of their applications and guarantees a high degree of portability. However, existing CBSE approaches for SDR have not been able to close the gap between specification and implementation so as to achieve the computational performance and the energy efficiency of handcrafted solutions. The main reason for this gap is that these flows rely on traditional compilers to lower the high level specification to the platform. The work presented in this paper builds on the Nucleus Concept (Ramakrishnan et al., IEEE Military Communications Conference (MILCOM 2009) [28]) in which computationally intensive kernels and their implementation characteristics on the target platform are known. This information allows a tool to close the performance gap, and thus enables efficient component-based SDR development. In this paper we present such a flow and its supporting environment, which includes state-of-the-art tools for system level design. The flow is demonstrated on a MIMO OFDM transceiver.     

集成网格服务的中国虚拟天文台工作流系统研究与设计

根据天文数据的广域分布、异构性以及共享性的特点,将网格技术应用于虚拟天文台项目中,并与工作流技术相结合,提出了集成网格技术的虚拟天文台的工作流体系结构。该结构利用网格技术有效解决了虚拟天文台建设中天文数据资源、计算资源、存储资源等各种资源的全面共享,工作流技术集成网格技术则使得服务调用应用的流程更加规范,实现了协同合作,达到更高的效率,以期望达到真正的无缝连接。     

An open medical imaging workstation architecture forplatform-independent 3-D medical image processing and visualization

A need for an entirely new medical workstation design was identified to increase the deployment of 3D medical imaging and multimedia communication. Recent wide acceptance of the World Wide Web (WWW) as a general communication service within the global network has shown how big the impact of standards and open systems can be. Information is shared among heterogeneous systems and diverse applications on various hardware platforms only by agreeing on a common format for information distribution. For medical image communications, the Digital Imaging and Communication in Medicine (DICOM) standard is possibly anticipating such a role. Logically, the next step is open software: platform-independent tools, which can as easily be transferred and used on multiple platforms. Application of the platform-independent programming language Java enables the creation of plug-in tools, which can easily extend the basic system. Performance problems inherent to all interpreter systems can be circumvented by using a hybrid approach. Computationally intensive functions like image processing functions can be integrated into a natively implemented optimized image processing kernel. Plug-in tools implemented in Java can utilize the kernel functions via a Java-wrapper library. This approach is comparable to the implementation of computationally intensive operations in hardware     

Fast simulation of DS/CDMA with and without coding in multipathfading channels

Code-division multiple access (CDMA) has found widespread applications in various applications such as advanced wireless technologies and digital cellular communications. We consider the error-rate performance of asynchronous direct-sequence CDMA in a wireless radio communications environment that is characterized by Rayleigh multipath fading channels. Because of the system complexity, the performance of CDMA systems in such an environment is difficult to assess analytically. Monte Carlo simulations can offer an alternative performance evaluation tool. Unfortunately, in practice, such an alternative is often limited by an excessive computational burden. Importance sampling is a variance reduction technique which can significantly reduce the computational cost required by Monte Carlo simulations. This paper describes the basic principles behind this powerful technique. In particular, it illustrates its use as a computationally efficient and accurate tool for computer-aided design and analysis of uncoded as well as coded CDMA in wireless communications     

Grid Computing and Beyond: The Context of Dynamic Data Driven Applications Systems

The advent of Grid computing has enhanced our capabilities to model and simulate complex systems arising in scientific, engineering, and commercial applications. The premise of Grid computing has been "on-demand" availability of computational resources to an application as needed, in the same manner as electricity is provided readily through electrical power grids. The computational grid (or simply the "Grid") entails ubiquitous access to resources (local or remote), such as computation and communication resources, as well as access to storage systems and visualization systems. As Grid computing technologies mature, it behooves to look beyond the current capabilities, into more advanced future environments. The environments of interest here are the enhanced capabilities that can be created by the paradigm of dynamic data driven applications systems (DDDAS). DDDAS entails the ability to incorporate additional data into an executing application and, in reverse, the ability of applications to dynamically steer the measurement process. The DDDAS concept offers the promise of improving application models and methods, and augmenting the analysis and prediction capabilities of application simulations and the effectiveness of measurement systems. Enabling this synergistic feedback and control loop between application simulations and measurements requires novel application modeling approaches and frameworks, algorithms stable under dynamic data injection and steering conditions, and new systems software and computational infrastructure capabilities. Recent advances in complex applications and the advent of Grid computing and sensor systems are some of the technologies that make it timely to embark in developing DDDAS capabilities. DDDAS environments extend the current notion of Grid infrastructure to also include the measurement systems in an integrated and synergistic way. DDDAS environments require support and services that go beyond the current Grid services in terms of t     

The Hi- neural simulator and its applications

This paper describes the Hi- (hierarchical network of object-oriented neurons) neural simulator, originally conceived as a general-purpose, computationally efficient, object-oriented software system for the simulation of small systems of biological neurons, as an aid to the study of links between neurophysiology and behaviour in lower animals. As such, the artificial neurons employed were spiking in nature; to effect an appropriate compromise between computational complexity and biological realism, modelling was at the transmembrane potential level of abstraction. Further, since real neural systems incorporate different types of neurons specialised to somewhat different functions, the software was written to accommodate a non-homogeneous population of neurons. The computational efficiency of Hi- makes it eminently suitable for situated system studies (biological robotics, animats) where real-time operation is a pre-requisite. The flexibility which was a central design goal of Hi- means that the system is also capable of modelling interconnections of non-spiking artificial neurons with continuous or piecewise linear activation functions. The efficacy of the simulator is illustrated with respect to some recent applications to situated systems studies. We also consider prospects for integrating Hi- with a conventional circuit simulator in the future.     

A Distributed Framework for Parallel Data Mining Using HPJava

Java has become a language of choice for applications executing in heterogeneous environments utilising distributed objects and multithreading. To handle large data sets, scalable and efficient implementations of data mining approaches are required, generally employing computationally intensive algorithms. Conventional Java implementations do not directly provide support for the data structures often encountered in such algorithms, and they also lack repeatability in numerical precision across platforms. This paper describes a distributed framework employing task and data parallelism, and implemented in high performance Java (HPJava). Issues of interest for data mining algorithms are identified, and possible solutions discussed for overcoming limitations in the Java Virtual Machine. The framework supports parallelism across workstation clusters, using the message-passing interface as middleware, and can support different analysis algorithms, wrapped as Java objects, and linked to various databases using the Java database connectivity interface. Guidelines are provided for implementing parallel and distributed data mining on large data sets, and a proof-of-concept data mining application is analysed using a neural network.     

Design of a hardware accelerator for real-time moment computation:a wavefront away approach

In image processing, pattern recognition, and computer vision, one of the most powerful techniques for feature extraction is to use moments. Real-time applications of this method, however, have been prohibited due to the intensive computation encountered in calculating the moments. One solution to this problem is to adopt specially designed hardware accelerators. This paper describes, from a practical standpoint, the design of a custom hardware accelerator for speeding up the moment computation. The design of the core functional units and the design of the overall system based on a wavefront array architecture are discussed. The moment accelerator can be easily configured into different sizes to meet diverse application requirements cost effectively. Testing results based on implementation using field-programmable gate array devices show that, at an affordable cost, the proposed hardware accelerator can deliver real-time speeds for moment computation. Elimination of this computational bottleneck makes it possible to use moments-based features in real-time industrial applications     

电子政务系统整合研究

信息技术的应用多样性、复杂性与计算分布性,导致许多应用系统基于分布式网络由多种异构资源组成。对电子政务的各组成部门而言,各自的信息系统存在着不同时期、由不同开发商、利用不同的开发工具、在不同的开发平台上搭建起来。这就给以后的整合关联应用带来不便。为了保障数据的一致性、提高数据的共享性,就需要建立一个横跨多种异构系统的数据交换平台。文中从多个信息系统的整合需求出发,经研究分析,提出了针对性的技术解决方案。     

A Distributed and Elastic Application Processing Model for Mobile Cloud Computing

The latest developments in mobile computing technology have increased the computing capabilities of smart mobile devices (SMDs). However, SMDs are still constrained by low bandwidth, processing potential, storage capacity, and battery lifetime. To overcome these problems, the rich resources and powerful computational cloud is tapped for enabling intensive applications on SMDs. In Mobile Cloud Computing (MCC), application processing services of computational clouds are leveraged for alleviating resource limitations in SMDs. The particular deficiency of distributed architecture and runtime partitioning of the elastic mobile application are the challenging aspects of current offloading models. To address these issues of traditional models for computational offloading in MCC, this paper proposes a novel distributed and elastic applications processing (DEAP) model for intensive applications in MCC. We present an analytical model to evaluate the proposed DEAP model, and test a prototype application in the real MCC environment to demonstrate the usefulness of DEAP model. Computational offloading using the DEAP model minimizes resources utilization on SMD in the distributed processing of intensive mobile applications. Evaluation indicates a reduction of 74.6% in the overhead of runtime application partitioning and a 66.6% reduction in the CPU utilization for the execution of the application on SMD.

     

Exploiting structure in fast aerial image computation forintegrated circuit patterns

Modeling aerial images has recently become a crucial component of semiconductor manufacturing. As all steppers employ partially coherent illumination, such modeling has been computationally intensive for all but elementary patterns. In this paper we describe a fast computational method for calculating aerial images of integrated circuit masks produced by a partially coherent optical projection system. The method described relies on two tools to realize fast computation: (1) coherent decompositions of partially coherent imaging system models as proposed by Pati and Kailath (1994), and (2) the use of “basis” (or building block) images that are well-suited to describe integrated circuit patterns. Examples are presented in which aerial images are computed for large mask areas. The proposed method represents a speed improvement of several orders of magnitude over a more traditional, and more general, approach (SPLAT from the University of California, Berkeley)