网格环境下数字图书馆异构资源整合分析

文章主要对网络环境下的数字图书馆异构资源的整合进行分析,介绍了网络环境下数字图书馆的元数据、异构资源检索类型、异构资源同构化的问题、数字图书馆建设的整体协调及未来发展趋势问题。     

异构网格环境下任务分配的自主计算方法

首先对网格环境的异构性进行描述，定义了关键计算域并给出其划分算法。刻画了基于多agent系统进行任务分配的机制，分析了在自主agent不同移动策略下网格各区域任务分布的不同。采用控制理论的方法加速agent的合理分布，从而可以充分利用关键计算域的异构特征。实例研究表明，提出的任务分配机制具有自配置和自优化特征，能够动态适应异构网格环境的要求。     

DRAGON: a framework for service provisioning in heterogeneous grid networks

Dynamic resource allocation in GMPLS optical networks (DRAGON) defines a research and experimental framework for high-performance networks required by grid computing and e-science applications. The DRAGON project is developing technology and deploying network infrastructure which allows dynamic provisioning of network resources in order to establish deterministic paths in direct response to end-user requests. This includes multidomain provisioning of traffic-engineering paths using a distributed control plane across heterogeneous network technologies while including mechanisms for authentication, authorization, accounting (AAA), and scheduling. A reference implementation of this framework has been instantiated in the Washington, DC area and is being utilized to conduct research and development into the deployment of optical networks technologies toward the satisfaction of very-high-performance science application requirements.     

Efficient allotment of resources in heterogeneous communication

Wireless Networks - Heterogeneous networks assist in enhancing the data rates. In this context, heterogeneous networks comprising eNodeB, Femtocell and Wi-Fi Access Point (AP) operate conjointly to...     

Pricing network resources for adaptive applications

The Differentiated Services framework (DiffServ) has been proposed to provide multiple Quality of Service (QoS) classes over IP networks. A network supporting multiple classes of service also requires a differentiated pricing structure. In this work, we propose a pricing algorithm in a DiffServ environment based on the cost of providing different levels of services, and on long-term average user resource demand of a service class. We integrate the proposed service-dependent pricing scheme with a dynamic pricing and service negotiation environment by considering a dynamic and congestion-sensitive pricing component. Pricing network services dynamically based on the level of service, usage, and congestion allows a more competitive price to be offered, allows the network to be used more efficiently, and provides a natural and equitable incentive for applications to adapt their service requests according to network conditions. We also develop the demand behavior of adaptive users based on a physically reasonable user utility function. Simulation results show that a congestion-sensitive pricing policy coupled with user rate adaptation is able to control congestion and allows a service class to meet its performance assurances under large or bursty offered loads, even without explicit admission control. Users are able to maintain a stable expenditure, and allowing users to migrate between service classes in response to price increases further stabilizes the individual service prices. When admission control is enforced, congestion-sensitive pricing still provides an advantage in terms of a much lower connection blocking rate at high loads.     

Bandwidth aggregation for real-time applications in heterogeneous wireless networks

A variety of wireless interfaces are available for today's mobile user to access Internet content. When coverage areas of these different technologies overlap, a terminal equipped with multiple interfaces can use them simultaneously to improve the performance of its applications. In this paper, we motivate the advantages that can be had through simultaneous use of multiple interfaces and present a network layer architecture that enables diverse multiaccess services. In particular, we explore in depth one such service provided by the architecture: Bandwidth Aggregation (BAG) for real-time applications. An important aspect of the architecture when providing BAG services for real-time applications is the scheduling algorithm that partitions the traffic onto different interfaces such that the QoS requirements of the application are met. We propose one such algorithm Earliest Delivery Path First (EDPF), that ensures packets meet their playback deadlines by scheduling packets based on the estimated delivery time of the packets. We show through analysis that EDPF performs close to an idealized Aggregated Single Link (ASL) discipline, where the multiple interfaces are replaced by a single interface with same aggregated bandwidth. A prototype implementation and extensive simulations carried using video and delay traces show the performance improvement BAG with EDPF scheduling offers over using just the Highest Bandwidth Interface (HBI) and other scheduling approaches based on weighted round robin.     

Ball grid array reliability assessment for aerospace applications

Reliability of ball grid arrays (BGAs) was evaluated with special emphasis on space applications. This work was performed as part of a consortium led by the Jet Propulsion Laboratory (JPL) to help build the infrastructure necessary for implementing this technology. Nearly 200 test vehicles, each with four package types, were assembled and tested using an experiment design. The most critical variables incorporated in this experiment were package type, board material, surface finish, solder volume, and environmental condition. The packages used for this experiment were commercially available packages with over 250 I/Os including both plastic and ceramic BGA packages.The test vehicles were subjected to thermal and dynamic environments representative of aerospace applications. Two different thermal cycling conditions were used, the JPL cycle ranged from −30°C to 100°C and the Boeing cycle ranged from −55°C to 125°C. The test vehicles were monitored continuously to detect electrical failure and their failure mechanisms were characterized. They were removed periodically for optical inspection, scanning electron microscopy (SEM) evaluation, and cross-sectioning for crack propagation mapping. Data collected from both facilities were analyzed and fitted to distributions using the Weibull distribution and Coffin–Manson relationships for failure projection. This paper will describe experiment results as well as those analyses.     

Combinatorial auctions for exchanging resources over a grid network

In grid systems, users compete for different types of resources such that they may execute their applications. Traditional grid systems are formed of organisations that join together for the purpose of collaborative projects. Resources of each of the participating organisation are pooled such that members of individual organisations may access the shared infrastructure. In general, each participant is both a provider and a consumer of resources. Whilst such systems address large organisations, in this paper we address democratic grid systems to satisfy needs of small organisations and even individuals, where on-demand grids may be formed by drawing idling resources available on the Internet. Whilst traditional grid systems resort to allocations that satisfy system specific objectives such as maximization of the resource utilisation, market mechanisms try to obtain allocations that are efficient economically. Economic mechanisms permit to achieve equilibrium between supply and demand and furthermore provide incentives for providers. Combinatorial auction has been argued as an effective mechanism to address the problem of resource allocation within grid systems. Auctions within which multiple types of resources in varying quantities may be traded eliminate the exposure problem by addressing co-allocation. In this paper, we describe a combinatorial exchange where multiple providers and multiple consumers may participate. We describe the winner determination problem that incorporates the time dimension, i.e. resource bundles may be requested for different time ranges, and describe a set of heuristics that have been designed to be fast. We show that these achieve a high level of efficiency as compared to exact solutions. The second part focusses on the pricing problem. The objective is to compute prices that represent the state of the market and bring trustworthy feedback to participants. Drawing on the approach taken by Kwasnica et al. (Manage Sci 51(3):419–434, 2005), we propose a pricing model that computes per-item pricing. Per-item pricing allows users to deduce the price of bundles that they require by linear summation. Furthermore, we propose a model that computes prices as a function of time, thus permitting users, in particular consumers to adjust their demand trading off price and time of execution.     

Accurate interfacing of heterogeneous structured FDTD grid components

We study strategies to interface finite-difference time-domain (FDTD) update equations in heterogeneous structured grid components for overset composite FDTD grids. An overset composite grid (or "chimera" grid) is a heterogeneous grid formed by the combination of structured FDTD subgrid components chosen to better conform to local geometrical features. We study the performance of various analytical filters and phase matching techniques to reduce problems associated with such heterogeneous grid interfacing, including spatial frequency aliasing and (numerical) phase velocity mismatch. We demonstrate the performance of interfacing algorithms in some canonical examples.     

基于先进小区干扰协调技术的异构网络联合资源分配

高发射功率的宏基站与低发射功率的小基站之间的资源分配策略直接影响着异构蜂窝网络的性能。这是一个联合资源优化问题,即用户的基站接入选择、宏基站预留给小基站的资源数量和基站的调度策略。针对这一问题,利用块并列下降方法,提出了一组新颖的资源优化算法。所提出的解决方案能分布式实现,并兼容先进长期演进技术( LTE-A )协议中的先进小区间干扰协调技术( eICIC)。大量的动态系统级仿真结果表明系统性能和用户间公平性都得到了显著提升。     

Resource management for symmetrical applications over heterogeneous services in IEEE 802.16

Wireless Networks - Symmetrical applications are multimedia applications that require both uplink and downlink connectivity. The demands of symmetrical applications are expected to grow rapidly in...     

A design flow for speeding-up dsp applications in heterogeneous reconfigurable systems

In this paper, we propose a method for speeding-up Digital Signal Processing applications by partitioning them between the reconfigurable hardware blocks of different granularity and mapping critical parts of applications on coarse-grain reconfigurable hardware. The reconfigurable hardware blocks are embedded in a heterogeneous reconfigurable system architecture. The fine-grain part is implemented by an embedded FPGA unit, while for the coarse-grain reconfigurable hardware our developed high-performance coarse-grain data-path is used. The design flow mainly consists of three steps; the analysis procedure, the mapping onto coarse-grain blocks, and the mapping onto the fine-grain hardware. In this work, the methodology is validated using five real-life applications; an OFDM transmitter, a medical imaging technique, a wavelet-based image compressor, a video compression scheme and a JPEG encoder. The experimental results show that the speedup, relative to an all-FPGA solution, ranges from 1.55 to 4.17 for the considered applications.     

Estimating architectural resources and performance for high-levelsynthesis applications

The authors present a solution to the following problems related to architectural synthesis. (1) Given an input specification and a performance constraint, determine a lower bound number of resources (active and interconnect) required to execute the data flow graph while satisfying the performance constraint. (2) Determine a lower bound performance for executing an input specification for a given number of resources (active and interconnect). These bounds are close to the actual designs synthesized by several existing systems     

Deployment of the GMPLS control plane for grid applications in experimental high-performance networks

In this article we present a review of the latest activities in recent experimental high-performance optical networks such as ultrascience network (USN), dynamic resource allocation via GMPLS optical network (DRAGON), and circuit-switched high-speed end-to-end transport architecture (CHEETAH). We compare the control and management approaches adopted in each of these networks and analyze their capabilities vis-a-vis the functional requirements of grid computing applications. Grid computing is increasingly on the rise to meet the massive processing and storage demands of a new class of e-science physics applications that may generate and require the processing of data sets reaching terabytes per day. The requirements of these applications challenge the limitations of the networking technologies that are in place today. In particular, the area of network management and control is undergoing significant developments in order to meet the demands of these applications. It is the purpose of this article to share our experiences in the deployment of the GMPLS control plane in these experimental optical networks. It is our belief that these and similar efforts will result in significant progress toward enabling connection-oriented high-performance networking. This new paradigm will encompass grid computing applications as well as commercial, health, and entertainment services, thus making it useful to the public at large.     

Narrow and wide band monopole antenna design using heterogeneous bidirectional recurrent neural network for LTE and UWB applications

The proposed antenna is a small wideband monopole with wideband circular polarization using heterogeneous bidirectional recurrent neural network for both narrow and wide band applications (NWB-MAD-HBRNN). The electromagnetic structure is designed, fabricated, and simulated with 1 mm thickness on FR4 substrate material along dielectric constant 4.3. The proposed antenna includes 4.3–8.85 GHz for ultrawideband applications; it contains reconfigurable narrow band for L-band 1.27 GHz, LTE, and ultrawideband applications. To enhance the antenna impedance bandwidth (BW) along axial ratio bandwidth (ARBW), a slit is etched at the antenna patch, a rectangular stub is inserted into the ground plane, and semicircular stub is added to the top of antenna feed line. The better agreement is observed in the measured and simulated gain performance of 4.8 dB for LTE band applications. The proposed NWB-MAD-HBRNN design provides 13.50%, 18.91%, and 22.58% higher bandwidth and 18.36%, 20.38%, and 27.58% lower return loss than the existing designs, such as bio-inspired wideband antenna for wireless applications based on perturbation technique (BWA-WA-PA), a compact circularly polarized modified printed monopole antenna for wireless applications (CCP-MPMA-WA), and new multiband monopole antenna for certain broadband wireless applications along wireless personal communications (PA-MMA-BWA), respectively.     

Energy-efficient routing protocol and optimized passive clustering in WSN for SMART grid applications

Due to low cost, ease of implementation and flexibility of wireless sensor networks (WSNs), WSNs are considered to be an essential technology to support the smart grid (SG) application. The prime concern is to increase the lifetime in order to find the active sensor node and thereby to find once the sensor node (SN) dies in any region. For this reason, an energy-efficient Dynamic Source Routing (DSR) protocol needs to provide the right stability region with a prolonged network lifetime. This work is an effort to extend the network's existence by finding and correcting the considerable energy leveraging behaviors of WSN. We build a comprehensive model based on real measures of SG path loss for different conditions by using the characteristics of WSN nodes and channel characteristics. This method also establishes a hierarchical network structure of balanced clusters and an energy-harvesting SN. The cluster heads (CHs) are chosen by these SN using a low overhead passive clustering strategy. The cluster formation method is focused on the use of passive clustering of the particle swarm optimization (PSO). For the sake of eliminating delayed output in the WSN, energy competent dynamic source routing protocol (EC-DSR) is used. Chicken swarm optimization (CSO) in which optimum cluster path calculation shall be done where distance and residual energy should be regarded as limitation. Finally, the results are carried out with regard to the packet distribution ratio, throughput, overhead management, and average end-to-end delay to demonstrate the efficiency of the proposed system.     

Signaling architectures and recovery time scaling for grid applications in IST Project MUPBED

It is now evident to the research community that local computational resources cannot keep up in an economical way with the demands generated by some users/applications. Therefore, distributed computing and the concept of a computational grid are now emerging. Novel transport network concepts are needed to support such visions, and high-speed intelligent optical networking may be the required infrastructure that will enable global grids. Emerging utility grid applications like business continuity and disaster recovery have strong requirements on the dynamic optical networks connecting the distributed grid resources. Supporting grid networking with an intelligent optical network (ION) infrastructure will allow utility grid applications the necessary flexibility with the required QoS (e.g., high bandwidth, reliability, limited delay). Emerging QoS requirements, such as scalable recovery time, highly depend on the ION's signaling architecture. This article gives simple analytical models for the implementation options of optical control plane signaling, shows simulation models for different resilience strategies, and offers some illustrative numerical comparisons to support the aforementioned efforts. This research area is also discussed, among others, in the European research project Multi-Partner European Testbeds for Research Networking (MUPBED).     

A model‐based abstraction layer for heterogeneous SDN applications

Modern controllers for software‐defined networks (SDN) enable the execution of arbitrary SDN applications (eg, Network Address Translation (NAT), traffic monitors) that may be exploited by an overarching set of services (eg, application‐layer orchestrators) to build even richer services. To this purpose, the above overarching services require a mechanism that allows reading the run‐time state and writing the configuration of arbitrary SDN applications, possibly through a uniform API. Unfortunately, most SDN applications are not designed/implemented by taking into account the possibility to be used as part of higher level service workflows (eg, a complex intrusion prevention system that leverages multiple elementary services as individual components), hence they may not provide an adequate interface that would allow overarching services to exploit their features. This paper addresses this problem by proposing an approach to represent the run‐time state of arbitrary applications, where data are exported according to high‐level model‐based structures. Furthermore, the mapping from the high‐level data model to the actual data representation within the SDN application is enabled by a suite of algorithms that are generic enough to operate independently of the actual source code of the application, thus avoiding undesired and invasive modifications to existing applications. The paper also presents a software framework and a prototype implementing the proposed approach, characterizes the resulting performance, and discusses pros and cons of the proposed approach.     

基于网格的数字图书馆资源组织模式构建

在网格环境下,对数字图书馆资源进行有效的组织为网格系统服务提供了工作准备,是用户获取信息的基础。针对网格资源异构性、分布性、动态性的特点,构建出一种全局/局域分层式数字图书馆资源组织模式,该模式避免了资源发现的盲目性,缩短了资源的查找时间,同时通过对局域资源服务器的实时监控,使检索结果按特定规则排列,大大提高了资源的利用率,有效地提高了网格系统的性能。