面向网格计算的高效可配置数据传输协议

针对目前主流的数据传输协议难以有效应对网格计算的问题,提出了一种面向网格计算的高效可配置数据传输协议(ECUDP)。ECUDP基于标准的用户数据报协议(UDP)协议,在保证高效通信的前提下,解决了UDP可靠性不足的缺陷。同时,通过可配置的功能模块,ECUDP能够满足不同网格应用的传输需求。实验结果表明,ECUDP可以在不同的网格计算情景中非常有效的运行,分析模型能够结合实际情况对其性能做出较为准确的预测。     

Adaptive wireless thin‐client model for mobile computing

The thin‐client computing model has the potential to significantly increase the performance of mobile computing environments. By delivering any application through a single, small‐footprint client (called a thin client) implemented on a mobile device, it is possible to optimize application performance without the need for building wireless application gateways. We thus present two significant contributions in the area of wireless thin‐client computing. Firstly, a mathematical performance model is derived for wireless thin‐client system. This model identifies factors that affect the performance of the system and supports derivation and analysis of adaptation strategies to maintain a user‐specified quality of service (QoS). Secondly, a proxy‐based adaptation framework is developed for wireless thin‐client systems, which dynamically optimizes performance of a wireless thin client via dynamically discovered context. This is implemented with rule‐based fuzzy logic that responds to variations in wireless link bandwidth and client processing power. Our fuzzy inference engine uses contextual data to dynamically optimize tradeoffs among different quality of service parameters offered to the end users. Additionally, our adaptation framework uses highly scalable wavelet‐based image coding to provide scalable QoS that can degrade gracefully. Our thin‐client adaptation framework shields the user from ill effects of highly variable wireless network quality and mobile device resources. This improves performance of active applications, in which the display changes frequently. Further, active application behaviour may produce high transmission latency for screen updates, which can adversely affect user perception of QoS, resulting in poor interactivity. We report measured adaptive performance under realistic mobile device and network conditions for several different clients and servers. Copyright © 2008 John Wiley & Sons, Ltd.     

Gain adaptation of networked DC motor controllers based on QoS variations

Connecting a complex control system with various sensors, actuators, and controllers as a networked control system by a shared data network can effectively reduce complicated wiring connections. This system is also easy to install and maintain. The trend is to use networked control systems for time-sensitive applications, such as remote DC motor actuation control. The performance of a networked control system can be improved if the network can guarantee quality-of-service (QoS). Due to time-varying network traffic demands and disturbances, QoS requirements provided by a network may change. In this case, a network has to reallocate its resources and may not be able to provide QoS requirements to a networked control application as needed. Therefore, the application may have to gracefully degrade its performance and perform the task as best as possible with the provided network QoS. This paper proposes a novel approach for networked DC motor control systems using controller gain adaptation to compensate for the changes in QoS requirements. Numerical and experimental simulations, and prototyping, are presented to demonstrate the feasibility of the proposed adaptation scheme to handle network QoS variation in a control loop. The effective results show the promising future of the use of gain adaptation in networked control applications.     

An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements

Grid computing is increasingly considered as a promising next-generation computational platform that supports wide-area parallel and distributed computing. In grid environments, applications are always regarded as workflows. The problem of scheduling workflows in terms of certain quality of service (QoS) requirements is challenging and it significantly influences the performance of grids. By now, there have been some algorithms for grid workflow scheduling, but most of them can only tackle the problems with a single QoS parameter or with small-scale workflows. In this frame, this paper aims at proposing an ant colony optimization (ACO) algorithm to schedule large-scale workflows with various QoS parameters. This algorithm enables users to specify their QoS preferences as well as define the minimum QoS thresholds for a certain application. The objective of this algorithm is to find a solution that meets all QoS constraints and optimizes the user-preferred QoS parameter. Based on the characteristics of workflow scheduling, we design seven new heuristics for the ACO approach and propose an adaptive scheme that allows artificial ants to select heuristics based on pheromone values. Experiments are done in ten workflow applications with at most 120 tasks, and the results demonstrate the effectiveness of the proposed algorithm.     

Influence of Network Characteristics on Application Performance in a Grid Environment

In grid computing, a key issue is how limited network resources can be shared by communications by various applications more effectively in order to improve application-level performance, e.g., by reducing the completion time for an individual application and/or set of applications. Communication by an application changes the condition of the network resources, which may, in turn, affect communications by other applications, and thus may degrade their performance. In this paper, we examine the characteristics of traffic generated by typical grid applications, and the effect of the round-trip time and bottleneck bandwidth on the application-level performance (i.e., completion time) of these applications. Our experiments showed that the impact of network conditions on the performance of various applications and the impact of application traffic on network conditions differed considerably depending on the application. These results suggest that effective allocation of network resources must take into account the network-related properties of individual applications.     

Architecture and performance of a Grid-enabled lookup-based biomedical optimization application: light scattering spectroscopy.

This paper presents a case study of a Grid-enabled implementation of light scattering spectroscopy (LSS). The LSS technique allows noninvasive detection of precancerous changes in human epithelium, differentiating from traditional biopsies by allowing in vivo diagnosis of tissue samples and quantitative analyses of parameters related to cancerous changes via numerical techniques. This paper describes the architecture of GridLSS and its integration with a Web-based Grid computing portal. GridLSS solves an optimization problem of determining the light scattering spectrum that best fits experimental spectral data among a large set of spectra computed analytically using rigorous Mie theory. The novel approach taken in this paper is based on the precomputation and storage of Mie theory spectra in lookup databases that are queried during the minimization process. The paper makes three important contributions: 1) it presents a novel parallel application for LSS analysis that delivers high performance in wide-area distributed computing environment; 2) it evaluates and analyzes the performance of this application in cluster-based high-performance computing environments that are typical of Grid deployments; and 3) it shows that the performance of GridLSS benefits significantly from the use of on-demand Grid data transfers based on virtualized distributed file systems and from user-level caches for remote file system data.     

一种面向边缘计算的可扩展网络I/O框架

作为当前的研究热点,边缘计算可以在网络边缘部署计算、存储和网络资源,为用户提供云化服务,以满足新兴应用的处理需求。但是,当前网络I/O模型的扩展性问题使得运行在边缘节点上的边缘应用难以有效地利用丰富的边缘物理资源处理海量用户的网络请求。针对边缘计算场景下网络I/O模型的数据竞争和负载不均衡问题,提出了一种新的可扩展网络I/O模型。通过试验可以看出,利用该模型的边缘应用具有良好的性能和可扩展性。     

Quality of Service Aware Reliable Task Scheduling in Vehicular Cloud Computing

Vehicular Cloud Computing (VCC) facilitates real-time execution of many emerging user and intelligent transportation system (ITS) applications by exploiting under-utilized on-board computing resources available in nearby vehicles. These applications have heterogeneous time criticality, i.e., they demand different Quality-of-Service levels. In addition to that, mobility of the vehicles makes the problem of scheduling different application tasks on the vehicular computing resources a challenging one. In this article, we have formulated the task scheduling problem as a mixed integer linear program (MILP) optimization that increases the computation reliability even as reducing the job execution delay. Vehicular on-board units (OBUs), manufactured by different vendors, have different architecture and computing capabilities. We have exploited MapReduce computation model to address the problem of resource heterogeneity and to support computation parallelization. Performance of the proposed solution is evaluated in network simulator version 3 (ns-3) by running MapReduce applications in urban road environment and the results are compared with the state-of-the-art works. The results show that significant performance improvements in terms of reliability and job execution time can be achieved by the proposed task scheduling model.     

ATM WAN performance tools, experiments, and results

Practical experiments in a wide-area ATM network environment are essential to gain a better understanding of the factors affecting ATM performance. This article summarizes the main lessons learned through the authors' practical experiences with ATM and how these can be applied to performance tuning. In order to achieve maximum performance from an ATM WAN, factors ranging from the transport protocol to the equipment used and the network conditions must be carefully taken into consideration. The authors also discuss some of the software-based throughput measurement tools available for the evaluation of high speed network performance, with particular emphasis on NetSpec     

Design of QoS in Intelligent Communication Environments Based on Neural Network

Due to the latest developments in communication and computing, smart services and applications are being deployed for various applications such as entertainment, health care, smart homes, security and surveillance. In intelligent communication environments, the main difficulty arising in designing an efficient congestion control scheme lies in the large propagation delay in data transfer which usually leads to a mismatch between the network resources and the amount of admitted traffic. To attack this problem, this paper describes a novel congestion control scheme in intelligent communication environments, which is based on a Back Propagation (BP) neural network technique. We consider a general computer communication model with multiple sources and one destination node. The dynamic buffer occupancy of the bottleneck node is predicted and controlled by using a BP neural network. The controlled best-effort traffic of the sources uses the bandwidth, which is left over by the guaranteed traffic. This control mechanism is shown to be able to avoid network congestion efficiently and to optimize the transfer performance both by the theoretic analyzing procedures and by the simulation studies.     

Cellular multiadaptive analogic architecture: a computational framework for UAV applications

An efficient adaptive algorithm in real-time applications should make optimal use of the available computing power for reaching some specific design goals. Relying on appropriate strategies, the spatial resolution/temporal rate can be traded against computational complexity; and sensitivity traded against robustness, in an adaptive process. In this paper, we present an algorithmic framework where a spatial multigrid computing is placed within a temporal multirate structure, and at each spatial grid point, the computation is based on an adaptive multiscale approach. The algorithms utilize an analogic (analog and logic) architecture consisting of a high-resolution optical sensor, a low-resolution cellular sensor-processor and a digital signal processor. The proposed framework makes the acquisition of a spatio-temporally consistent image flow possible even in case of extreme variations (relative motion) in the environment. It ideally supports the handling of various difficult problems on a moving platform including terrain identification, navigation parameter estimation, and multitarget tracking. The proposed spatio-temporal adaptation relies on a feature-based optical-flow estimation that can be efficiently calculated on available cellular nonlinear network (CNN) chips. The quality of the adaptation is evaluated compared to nonadaptive spatio-temporal behavior where the input flow is oversampled, thus resulting in redundant data processing with an unnecessary waste of computing power. We also use a visual navigation example recovering the yaw-pitch-roll parameters from motion-field estimates in order to analyze the adaptive hierarchical algorithmic framework proposed and highlight the application potentials in the area of unmanned air vehicles.     

Analysis of TCP performance under joint rate and power adaptation in cellular WCDMA networks

To improve the spectral efficiency while meeting the radio link level quality of service requirements such as the bit-error-rate (BER) requirements for the different wireless services, transmission rate and power corresponding to the different mobile users can be dynamically varied in a cellular wideband code-division multiple-access (WCDMA) network depending on the variations in channel interference and fading conditions. This paper models and analyzes the performance of transmission control protocol (TCP) under joint rate and power adaptation with constrained BER requirements for downlink data transmission in a cellular variable spreading factor (VSF) WCDMA network. The aim of this multilayer modeling of the WCDMA radio interface is to better understand the interlayer protocol interactions and identify suitable transport and radio link layer mechanisms to improve TCP performance in a wide-area cellular WCDMA network.     

可信终端动态运行环境的可信证据收集机制

可信计算的链式度量机制不容易扩展到终端所有应用程序,因而可信终端要始终保证其动态运行环境的可信仍然困难.为了提供可信终端动态运行环境客观、真实、全面的可信证据,提出了可信终端动态运行环境的可信证据收集机制.首先,在可信终端的应用层引入一个可信证据收集代理,并将该代理作为可信平台模块(trusted platform module,简称TPM)链式度量机制的重要一环,利用TPM提供的度量功能保证该代理可信;然后通过该代理收集可信终端的内存、CPU、网络端口、磁盘文件、策略配置数据和进程等的运行时状态信息,并利用TPM提供的可信存储功能,保存这些状态信息作为终端运行环境的可信证据,并保障可信证据本身的可信性.该可信证据收集机制具有良好的可扩展性,为支持面向不同应用的信任评估模型提供基础.在Windows平台中实现了一个可信证据收集代理的原型,并以一个开放的局域网为实验环境来分析可信证据收集代理所获取的终端动态运行环境可信证据以及可信证据收集代理在该应用实例中的性能开销.该应用实例验证了该方案的可行性.     

WComp middleware for ubiquitous computing: Aspects and composite event-based Web services

After a survey of the specific features of ubiquitous computing applications and corresponding middleware requirements, we list the various paradigms used in the main middlewares for ubiquitous computing in the literature. We underline the lack of works introducing the use of the concept of Aspects in middleware dedicated to ubiquitous computing, in spite of them being used for middleware improvement in other domains. Then, we introduce our WComp middleware model, which federates three main paradigms: event-based Web services, a lightweight component-based approach to design dynamic composite services, and an adaptation approach using the original concept called Aspect of Assembly. These paradigms lead to two ways to dynamically design ubiquitous computing applications. The first implements a classical component-based compositional approach to design higher-level composite Web Services and then allow to increment the graph of cooperating services for the applications. This approach is well suited to design the applications in a known, common, and usual context. The second way uses a compositional approach for adaptation using Aspect of Assembly, particularly well-suited to tune a set of composite services in reaction to a particular variation of the context or changing preferences of the users. Having detailed Aspect of Assembly concept, we finally comment on results indicating the expressiveness and the performance of such an approach, showing empirically that principles of aspects and program integration can be used to facilitate the design of adaptive applications.     

A cellular packet radio data network

A new wide-area data network is described. The network employs packet switching techniques within a multi-access, narrowband cellular radio environment and provides a flexible alternative to copper wire telecommunications for short data message applications. Following a discussion of the network requirements, the paper describes the key design areas in terms of a layered model. A new data link layer protocol called dynamic slotted reservation Aloha is introduced. This protocol is optimised for the bidirectional communication of packets containing around 1000 bits of application data. The practical implementation is presented briefly before a number of the major applications are discussed     

基于基站切换的交通信息采集技术应用研究

基于移动通信网络基站切换的交通信息采集技术,突破传统交通信息采集技术许多的局限性,仅需增加少量处理设备情况下,能够实时、广域范围内采集交通数据,表现出了良好的实用性、经济性,是一种新型的交通信息采集技术。分析这种新型技术的实现原理、关键技术、影响要素,并结合实践应用给出了技术评估指标体系,多方面评估该技术推广发展可行性,提出该技术应用、发展、完善重点,为规模性应用提供研究基础。     

Quality of experience (QoE) driven adaptation scheme for?voice/video over IP

Network quality of service (NQoS) of IP networks is unpredictable and impacts the quality of networked multimedia services. Adaptive voice and video schemes are therefore vital for the provision of voice over IP (VoIP) services for optimised quality of experience (QoE). Traditional adaptation schemes based on NQoS do not take perceived quality into consideration even though the user is the best judge of quality. Additionally, uncertainties inherent in NQoS parameter measurements make the design of adaptation schemes difficult and their performance suboptimal. This paper presents a QoE-driven adaptation scheme for voice and video over IP to solve the optimisation problem to provide optimal QoE for networked voice and video applications. The adaptive VoIP architecture was implemented and tested both in NS2 and in an Open IMS Core network to allow extensive simulation and test-bed evaluation. Results show that the scheme was optimally responsive to available network bandwidth and congestion for both voice and video and optimised delivered QoE for different network conditions, and is friendly to TCP traffic.     

Low response time context awareness through extensible parameter adaptation with ORCA

Ubiquitous computing applications or widespread robots interactions execute in unforeseen environments and need to adapt to changeful available services, user needs, and variations of the environment. Context-awareness ability addresses such a need, enabling, through adaptation rules, applications to react to the perceived dynamic variations. Responses to adaptation have to be quick enough to maximize the time during which the application is coherent with its environment. Adaptation rules, associating variations of the environment to application reactions, are usually established at design time. However, in unforeseen and partially anticipated environments, we claim that adaptation rules have to be dynamically extensible to match previously unexpected variations. Our approach enables rule composition and ensures a deterministic result. We propose to use parameter adaptation to quickly respond to environmental variations and dynamic compositional adaptation to provide extensibility to the parameter adaptation. To foster even lower response times, we internalize context-awareness processing and decision into the application.     

Optimizing Web delivery over wireless links: design, implementation, and experiences

World over wide-area wireless Global System for Mobile Communication (GSM) networks have been upgraded to support the general packet radio service (GPRS). GPRS brings "always-on" wireless data connectivity at bandwidths comparable to that of conventional fixed-line telephone modems. Unfortunately many users have found the reality to be rather different, experiencing very disappointing performance when, for example, browsing the Web over GPRS. In This work, we show what causes the web and its underlying transport protocol TCP to underperform in a GPRS wide-area wireless environment. We examine why certain GPRS network characteristics interact badly with TCP to yield problems such as: link underutilization for short-lived flows, excess queueing for long-lived flows, ACK compression, poor loss recovery, and gross unfairness between competing flows. We also show that many Web browsers tend to be overly aggressive, and by opening too many simultaneous TCP connections can aggravate matters. We present the design and implementation of a web optimizing proxy system called GPRSWeb that mitigates many of the GPRS link-related performance problems with a simple software update to a mobile device. The update is a link-aware middleware (a local "client proxy") that sits in the mobile device, and communicates with a "server proxy" located at the other end of the wireless link, close to the wired-wireless border. The dual-proxy architecture collectively implements a number of key enhancements-an aggressive caching scheme that employs content-based hash keying to improve hit rates for dynamic content, a preemptive push of Web page support resources to mobile clients, resource adaptation to suit client capabilities, delta encoded data transfer of modified pages, DNS lookup migration, and a UDP-based reliable transport protocol that is specifically optimized for use over GPRS. We show that these enhancements results in significant improvement in web performance over GPRS links.     

Virtual-topology adaptation for WDM mesh networks under dynamic traffic

We present a new approach to the virtual-topology reconfiguration problem for a wavelength-division-multiplexing- based optical wide-area mesh network under dynamic traffic demand. By utilizing the measured Internet backbone traffic characteristics, we propose an adaptation mechanism to follow the changes in traffic without a priori knowledge of the future traffic pattern. Our work differs from most previous studies on this subject which redesign the virtual topology according to an expected (or known) traffic pattern, and then modify the connectivity to reach the target topology. The key idea of our approach is to adapt the underlying optical connectivity by measuring the actual traffic load on lightpaths continuously (periodically based on a measurement period) and reacting promptly to the load imbalances caused by fluctuations on the traffic, by either adding or deleting one or more lightpath at a time. When a load imbalance is encountered, it is corrected either by tearing down a lightpath that is lightly loaded or by setting up a new lightpath when congestion occurs. We introduce high and low watermark parameters on lightpath loads to detect any over- or underutilized lightpath, and to trigger an adaptation step. We formulate an optimization problem which determines whether or not to add or delete lightpaths at the end of a measurement period, one lightpath at a time, as well as which lightpath to add or delete. This optimization problem turns out to be a mixed-integer linear program. Simulation experiments employing the adaptation algorithm on realistic network scenarios reveal interesting effects of the various system parameters (high and low watermarks, length of the measurement period, etc.). Specifically, we find that this method adapts very well to the changes in the offered traffic.