JAVA: network-centric enterprise computing

In recent years, the popularity of the Internet has increased and Java has emerged as a powerful animation tool for creating web pages. However, users have still not exploited the full power of Java. Java is an object-oriented programming language with a rich set of application programming interfaces (API). It has the infrastructure for building applications in diverse domains with ease. Java's sophisticated networking APIs facilitate building network centric enterprise applications. Java's virtual machine enables development of architecture neutral applications which can be ported without any modifications. This has revolutionized the way software is written and distributed. This paper highlights the key features of Java language, illustrates the use of networking libraries and enlists features that facilitate enterprise software development.     

Web-based enterprise computing

The paper considers how Web technologies have emerged as a credible alternative to client-server computing in the corporate enterprise. Web-based enterprise computing allows corporate IT to integrate disparate systems into a single, coherent environment. This shift from a traditional Web server with database connectivity to integrated systems that support the use of Web technologies facilitates business processes and allows corporations to service both internal and external customers effectively     

Heterogeneous computing: challenges and opportunities

The issues and problems posed by heterogeneous computing are discussed. They include design of algorithms for applications, partitioning and mapping of application tasks, interconnection requirements, and the design of programming environments. The use of heterogeneous computing in image understanding is reviewed. An example vision task is presented, and the different types of parallelism used in the example are identified     

Next-Generation Enterprise Computing: Beyond EDOC 2006

With the increasing demand for networked and XML services, IT professionals need conferences like EDOC to discuss emerging technologies and next-generation enterprise computing.     

The challenges of mobile computing

The technical challenges that mobile computing must surmount to achieve its potential are hardly trivial. Some of the challenges in designing software for mobile computing systems are quite different from those involved in the design of software for today's stationary networked systems. The authors focus on the issues pertinent to software designers without delving into the lower level details of the hardware realization of mobile computers. They look at some promising approaches under investigation and also consider their limitations. The many issues to be dealt with stem from three essential properties of mobile computing: communication, mobility, and portability. Of course, special-purpose systems may avoid some design pressures by doing without certain desirable properties. For instance portability would be less of a concern for mobile computers installed in the dashboards of cars than with hand-held mobile computers. However, the authors concentrate on the goal of large-scale, hand-held mobile computing as a way to reveal a wide assortment of issues     

The challenges of wearable computing: Part 1

Wearable computing pursues an interface ideal of a continuously worn, intelligent assistant that augments memory, intellect, creativity, communication, and physical senses and abilities. Many challenges await wearable designers as they balance innovative interfaces, power requirements, network resources, and privacy concerns. This survey describes the possibilities offered by wearable systems and, in doing so, demonstrates attributes unique to this class of computing     

The challenges of wearable computing: Part 2

For pt. 1 see ibid. Wearable computing pursues an interface ideal of a continuously worn, intelligent assistant that augments memory, intellect, creativity, communication, and physical senses and abilities. Many challenges await wearable designers. Part 2 begins with the challenges of network resources and privacy concerns. This survey describes the possibilities offered by wearable systems and, in doing so, demonstrates attributes unique to this class of computing     

边缘计算: 现状与展望

近年来,信息技术的不断变革伴随数据量的急剧爆发,使主流的云计算解决方案面临实时性差、带宽受限、高能耗、维护费用高、隐私安全等问题. 边缘智能的出现与快速发展有效缓解了此类问题,它将用户需求处理下沉到边缘,避免了海量数据在网络中的流动,得到越来越多的关注. 由于边缘计算中资源性能普遍较低,通过资源实现协同推理正成为热点.通过对边缘智能发展的趋势分析,得出边缘协同推理目前仍处于增长期,还未进入稳定发展期. 因此,在对边缘协同推理进行充分调研的基础上,将边缘协同推理划分为智能化方法与协同推理架构2个部分,分别对其中涉及到的关键技术进行纵向归纳整理,并从动态场景角度出发,对每种关键技术进行深入分析,对不同关键技术进行横向比较以及适用场景分析.最后对动态场景下的边缘协同推理给出值得研究的若干发展方向.

     

Pervasive computing goes to work: interfacing to the enterprise

The paperless office is an idea whose time has come, and come, and come again. To see how pervasive computing applications might bring some substance to this dream, the author spoke recently with key managers and technologists at McKesson Corporation (San Francisco), a healthcare supplier, service, and technology company with US$50 billion in sales last year, and also at AvantGo (Hayward, Calif.), a provider of mobile infrastructure software and services. For the past several years, McKesson has used mobility middleware developed by AvantGo to deploy major supply chain applications with thousands of pervasive clients and multiple servers that replace existing paper-based tracking systems. According to McKesson's managers, their system greatly reduced errors and associated costs caused by redelivery or loss of valuable products, giving McKesson a solid return on its investment.     

The challenges to invisible computing

The paper discusses some of the challenges to invisible computing. It clarifies the distinction between ubiquitous and invisible computing using an example from digital photography. It considers computer networking challenges and data management     

Business intelligence in enterprise computing environment

Business intelligence (BI) is the process of gathering correct information in the correct format at the correct time; and delivering the results for decision-making purposes, or have a positive impact on business operations, tactics, and strategy in the enterprises. This paper is intended as a brief review of BI in an enterprise computing environment, with an emphasis on the algorithms and methods. The review points out the challenges to the broad and deep deployment of business intelligence systems, and provide proposals to make business intelligence more effective.     

A NASA perspective on quantum computing: Opportunities and challenges

In the last couple of decades, the world has seen several stunning instances of quantum algorithms that provably outperform the best classical algorithms. For most problems, however, it is currently unknown whether quantum algorithms can provide an advantage, and if so by how much, or how to design quantum algorithms that realize such advantages. Many of the most challenging computational problems arising in the practical world are tackled today by heuristic algorithms that have not been mathematically proven to outperform other approaches but have been shown to be effective empirically. While quantum heuristic algorithms have been proposed, empirical testing becomes possible only as quantum computation hardware is built. The next few years will be exciting as empirical testing of quantum heuristic algorithms becomes more and more feasible. While large-scale universal quantum computers are likely decades away, special-purpose quantum computational hardware has begun to emerge, which will become more powerful over time, as well as small-scale universal quantum computers.     

Moving from exascale to zettascale computing: challenges and techniques

High-performance computing (HPC) is essential for both traditional and emerging scientific fields, enabling scientific activities to make progress. With the development of high-performance computing, it is foreseeable that exascale computing will be put into practice around 2020. As Moore’s law approaches its limit, high-performance computing will face severe challenges when moving from exascale to zettascale, making the next 10 years after 2020 a vital period to develop key HPC techniques. In this study, we discuss the challenges of enabling zettascale computing with respect to both hardware and software. We then present a perspective of future HPC technology evolution and revolution, leading to our main recommendations in support of zettascale computing in the coming future.     

石化企业云计算数据中心设计

随着中国石化建设世界一流能源化工公司的重大决策的制定,建设"世界一流信息化能力"的信息化战略目标提出,企业IT管理的标准化、内部控制的流程化,现有的烟囱式IT基础设施架构已不能满足按需分配资源需求。云计算的广泛实践为企业数据中心建设提供了技术基础。本文应用基础设施即服务(IaaS)架构对企业数据中心进行设计,对计算、存储、网络、安全等资源池进行了详细设计,并在企业进行了实施。本文提出的云计算数据中心可以为今后一个时期的石化企业信息化应用奠定基础。     

Restructuring computing programs to meet employment challenges

For many years, computing professionals have enjoyed steady employment and good salaries. Throughout most of the career in computer science education, nearly all the graduates who wanted a job in computing, even those who were clearly weaker, could find suitable employment without really trying. However, the job prospects of college graduates with degrees in computing and information technology have recently dimmed significantly. By restructuring the curriculum to create an interdisciplinary program, smaller schools can maximize their graduates' prospects for employment as computing professionals and improve the faculty's prospects of competing for national funding in focused research areas.     

面向海洋的多模态智能计算：挑战、进展和展望

海洋是高质量发展的要地,海洋科学大数据的发展为认知和经略海洋带来机遇的同时也引入了新的挑战。海洋科学大数据具有超多模态的显著特征,目前尚未形成面向海洋领域特色的多模态智能计算理论体系和技术框架。因此,本文首次从多模态数据技术的视角,系统性介绍面向海洋现象/过程的智能感知、认知和预知的交叉研究进展。首先,通过梳理海洋科学大数据全生命周期的阶段演进过程,明确海洋多模态智能计算的研究对象、科学问题和典型应用场景。其次,在海洋多模态大数据内容分析、推理预测和高性能计算3个典型应用场景中展开现有工作的系统性梳理和介绍。最后,针对海洋数据分布和计算模式的差异性,提出海洋多模态大数据表征建模、跨模态关联、推理预测以及高性能计算4个关键科学问题中的挑战,并提出未来展望。     

企业私有云计算基础架构研究与设计

随着信息化在企业中的深入运用,传统IT架构慢慢显现出弊端：基础资源利用率偏低、管理上太分散;面对管理或业务出现变化时,旧的业务系统难以快速响应.怎样实现业务同IT建设的协同,怎样对IT系统现有数据进行利用,这些都成为当下企业立刻要解决的.“云计算”作为眼下信息领域炙手可热的技术,一方面它能对现有IT资源进行很好地整合,另一方面面对业务变化时它能实现IT建设的迅速响应,因此它的研发为解决企业的上述难题提供了希望.