Uplink Performance Analysis in Multi-Tier Heterogeneous Cellular Networks with Power Control and Biased User Association

A K-tier uplink heterogeneous cellular network is modelled and analysed by accounting for both truncated channel inversion power control and biased user association. Each user has a maximum transmit power constraint and transmits data when it has sufficient transmit power to perform channel inversion. With biased user association, each user is associated with a base station(BS) that provides the maximum received power weighted by a bias factor, but not their nearest BS. Stochastic geometry is used to evaluate the performances of the proposed system model in terms of the outage probability and ergodic rate for each tier as functions of the biased and power control parameters. Simulations validate our analytical derivations. Numerical results show that there exists a trade-off introduced by the power cut-off threshold and the maximum user transmit power constraint. When the maximum user transmit power becomes a binding constraint, the overall performance is independent of BS densities. In addition, we have shown that it is beneficial for the outage and rate performances by optimizing different network parameters such as the power cut-off threshold as well as the biased factors.

Container Networking Performance Analysis for Large-Scale User Behavior Simulation

Accurately simulating large-scale user behavior is important to improve the similarity between the cyber range and the real network environment. The Linux Container provides a method to simulate the behavior of large-scale users under the constraints of limited physical resources. In a container-based virtualization environment, container networking is an important component. To evaluate the impact of different networking methods between the containers on the simulation performance, the typical container networking methods such as none, bridge, macvlan were analyzed, and the performance of different networking methods was evaluated according to the throughput and latency metrics. The experiments show that under the same physical resource constraints, the macvlan networking method has the best network performance, while the bridge method has the worst performance. This result provides a reference for selecting the appropriate networking method in the user behavior simulation process.

Framework to Model User Request Access Patterns in the World Wide Web

In this paper, we present a novel approach to model user request patterns in the World Wide Web. Instead of focusing on the user traffic for web pages, we capture the user interaction at the object level of the web pages. Our framework model consists of three sub-models: one for user file access, one for web pages, and one for storage servers. Web pages are assumed to consist of different types and sizes of objects, which are characterized using several categories: articles, media, and mosaics. The model is implemented with a discrete event simulation and then used to investigate the performance of our system over a variety of parameters in our model. Our performance measure of choice is mean response time and by varying the composition of web pages through our categories, we find that our framework model is able to capture a wide range of conditions that serve as a basis for generating a variety of user request patterns. In addition, we are able to establish a set of parameters that can be used as base cases. One of the goals of this research is for the framework model to be general enough that the parameters can be varied such that it can serve as input for investigating other distributed applications that require the generation of user request access patterns.

Multi-user Motion JPEG2000 over wireless LAN: run-time performance-energy optimization with application-aware cross-layer scheduling

This paper introduces a video application-aware cross-layer framework for joint performance-energy optimization,considering the scenario of multiple users upstreaming real-time Motion JPEG2000 video streams to the access point of a WiFi wireless local area network and extends the PHY-MAC run-time cross-layer scheduling strategy that we introduced in (Mangharam et al., 2005; Pollin et al., 2005) to also consider congested network situations where video packets have to be dropped. We show that an optimal solution at PHY-MAC level can be highly suboptimal at application level, and then show that making the cross-layer framework application-aware through a prioritized dropping policy capitalizing on the inherent scalability of Motion JPEG2000 video streams leads to drastic average video quality improvements and inter-user quality variation reductions of as much as 10 dB PSNR, without affecting the overall energy consumption requirements.

企业—用户互动、敏捷开发与数字产品创新绩效

数字技术的可重新编程性、开放性等特征增强了市场需求的不确定性,企业通过与用户互动进行敏捷开发以提升数字产品创新绩效,成为获取竞争优势的关键。基于精益创业理论和利益相关者理论,深入分析企业—用户互动、敏捷开发与数字产品创新绩效间的作用机理。结果表明:企业—用户互动通过敏捷开发积极影响数字产品创新绩效,且组织创新氛围将增强三者间的作用关系。研究有助于丰富对于数字情境下企业—用户互动创新的理解,推动敏捷开发研究的发展,为解释数字产品创新绩效差异化提供有价值的研究思路,也为数字产品创新绩效的提升提供重要的管理启示。

用户资源创新能力、创业模式与创业绩效关系研究——基于众创空间的双重网络嵌入的调节作用

资源对用户开展创业活动至关重要,但对用户创业者资源创新能力影响创业模式选择以及关于创业绩效理论机制的探讨较少。通过构建不同资源创新能力、创业模式与创新绩效之间的匹配关系模型,对221家嵌入众创空间的用户创业企业进行实证研究。结果发现:①资源获取创新能力有助于用户创业者选择协同型创业模式并促进生存绩效提升;②资源利用创新能力有助于用户创业者选择自主型创业模式并促进成长绩效提升;③创业模式在资源创新能力对创业绩效影响中发挥部分中介作用;④众创空间双重网络嵌入对资源创新能力与创业模式关系以及创业模式与创业绩效关系发挥正向调节作用。

面向高性能计算环境的多维自适应授权访问策略

高性能计算能力是国家综合实力和创新能力的重要体现,是支撑我国科技持续发展的关键技术之一。随着高性能计算的发展,越来越多领域的科研人员开始关注并使用高性能计算环境。高性能计算环境目前面临资源有限、用户数目增多等挑战。为保证环境的安全性、提高环境资源的利用率,需设置一定的授权访问策略来约束用户的访问行为。本文针对高性能计算环境服务对象用户和应用社区或业务平台,基于机器学习算法对用户行为进行分析获取相关属性,设计并实现了一种多维自适应授权访问策略(MAAC)。实验表明,MAAC可实现对环境资源有效和灵活访问控制,同时该策略的决策时间可控制在1 ms内,与策略响应时间相比可忽略不计。

组织因素对用户创业企业绩效的影响机制研究——基于模糊集定性比较分析

用户成为创业者,为“大众创业、万众创新”带来新的活力,用户创业及其绩效问题已成为创业领域研究的重点之一。以65个用户创业企业为样本,基于用户创业企业组织因素的创业能力、创业氛围、创业拼凑、创业导向和创业战略5个前因条件,构建用户创业企业绩效影响机制模型。运用模糊集定性比较分析(fsQCA)方法,探究5个条件变量组合形成的不同组态对用户创业企业绩效的影响。研究结果表明:创业拼凑是产生高用户创业企业绩效的必要条件;高用户创业企业绩效的路径可被归纳为团队资源内外驱动型和策略资源双向驱动型,其与构成非高用户创业企业绩效的组态呈现非对称性关系。建议用户创业企业有意识地培养创业拼凑能力,发挥多种因素的协同效应,进而促进企业绩效提升。

考虑碳排放约束的用户侧综合能源系统规划

为明晰碳排放约束对用户侧综合能源系统规划的影响及其供能优越性,提出了一种考虑碳排放约束的用户侧综合能源系统规划模型。在构建用户侧综合能源系统和常规分供式系统的结构框架基础上,考虑投资容量、设备运行、能量平衡与碳排放强度等约束,建立以全寿命周期经济成本最小为优化目标的用户侧综合能源系统规划模型并分别对3种建筑负荷情景进行算例分析。结果表明,碳排放约束强度对用户侧综合能源系统的设备容量、经济成本和能源性能影响均较大;与常规分供式系统相比,用户侧综合能源系统更具经济节约、环境友好和节能高效的优势。

环境不确定条件下用户参与与企业新产品开发绩效的关系研究

开放式创新的时代,企业吸纳用户参与自身创新过程是提高创新绩效的重要策略,但用户参与会给企业带来管理复杂性而可能导致创新失败,也会由于用户参与创新的方式与外部环境是否匹配的问题而使用户参与创新成效难以预测。据此,基于知识基础观和权变理论,立足企业,实证研究用户参与对新产品开发绩效的影响及不确定性环境的权变作用。利用444份国内企业样本,采用层次回归分析方法,探索不同用户参与模式如何与不确定环境不同构面特征相匹配,进而有效提升企业新产品开发绩效。结果发现:用户作为信息提供者和合作开发者的方式参与企业创新,有利于提高企业新产品开发绩效,但用户的独立创新与企业新产品开发绩效无显著关系;环境不确定性的不同维度对用户参与与企业新产品开发绩效间的关系产生不同影响。具体而言:市场动荡负向调节独立创新者与新产品开发绩效间的关系,技术动荡正向调节合作开发者与新产品开发绩效间的关系,竞争强度正向调节信息提供者与新产品开发绩效间的关系。由此可见,企业需要基于所处环境的特征,相机决策采纳相应的用户参与方式,从而提高新产品开发绩效。

基于用户需求的乘员舱采暖性能研究

调研发现,国家标准规定的先浸车、确认发动机冷却液处于稳定状态再开始采暖性能测试的试验方案与用户使用工况存在显著差异。针对此问题,建立更贴近用户需求的采暖工况,以此为基础开展乘员舱采暖性能分析、测试。试验结果表明,产品车各监测点温度均满足开发要求和国标要求,具有一定的参考价值。

天然气掺氢对终端用户的影响

为明确现有终端用户设备的掺氢适应性情况,通过案例调研和模型试验分析的方法,评估天然气输送系统中氢气掺混对终端用户设备——居民设备(如燃气灶、热水器、壁挂炉)和工业设备(燃气锅炉、燃气轮机、压缩机、发动机)在燃烧稳定性、热效率和污染物排放等方面的影响。结果表明:适量掺氢能够改善燃烧性能,降低污染物排放,然而掺氢比的提高也引入了如火焰稳定性下降、材料兼容性问题等安全风险。掺氢比10%以内时,对居民燃气设备燃烧特征及稳定性影响较弱,并一定程度降低了污染排放物。因工业设备的运行原理差异,其对掺氢比也表现不同的适应性。燃气锅炉的示范应用表明23%左右是最佳掺氢比,而燃气轮机在掺氢比介于10%~20%的情况下,能够保持设备的安全可靠性,防止回火并且满足排放标准;掺氢可以解决发动机初期点火所需能量大、稀燃能力不足的问题,但排放尾气成分则受多种因素影响;压缩机的转动速率和构造的稳固性在混入氢气后会受到显著影响,目前建议掺氢比在10%以下。

便携式干衣拉杆箱的设计与分析

通过对目标用户群体的需求分析、功能需求的探讨以及用户体验的重视,研究提出了一种结构稳固、便于携带、操作简便且安全环保的干衣拉杆箱设计方案。

面向未来千兆宽带应用的用户行为分析与网络优化

针对千兆宽带应用,分析其中的用户行为和网络优化方法。采集数据并分析用户行为特征,以准确掌握用户需求变动,评估千兆宽带网络性能指标并分析其局限性,识别网络性能的关键指标,运用以用户行为为依据的网络优化策略,如智能路由、负载均衡、差分服务流量调度及软件定义网络(Software Defined Network,SDN)切片技术,提升网络服务质量,保障安全与隐私,为实现未来千兆宽带应用的智能、高效、安全网络环境贡献力量。

Teaching the User By Learning From the User:Personalizing Movement Control in Physical Human-robot Interaction

This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior of each user in coping with different tasks, where lower performance results in higher intervention from the robot. This personalized physical human-robot interaction(p2HRI) method incorporates adaptive modeling of the interaction between the human and the robot as well as learning from demonstration(LfD) techniques to adapt to the users' performance. This approach is based on model predictive control where the system optimizes the rendered forces by predicting the performance of the user. Moreover, continuous learning of the user behavior is added so that the models and personalized considerations are updated based on the change of user performance over time. Applying this framework to a field such as haptic guidance for skill improvement, allows a more personalized learning experience where the interaction between the robot as the intelligent tutor and the student as the user,is better adjusted based on the skill level of the individual and their gradual improvement. The results suggest that the precision of the model of the interaction is improved using this proposed method,and the addition of the considered personalized factors to a more adaptive strategy for rendering of guidance forces.

Real-time hybrid simulation of structures equipped with viscoelastic-plastic dampers using a user-programmable computational platform

A user-programmable computational/control platform was developed at the University of Toronto that offers real-time hybrid simulation （RTHS） capabilities. The platform was verified previously using several linear physical substructures. The study presented in this paper is focused on further validating the RTHS platform using a nonlinear viscoelastic-plastic damper that has displacement, frequency and temperature-dependent properties. The validation study includes damper component characterization tests, as well as RTHS of a series of single-degree-of-freedom （SDOF） systems equipped with viscoelastic-plastic dampers that represent different structural designs. From the component characterization tests, it was found that for a wide range of excitation frequencies and friction slip loads, the tracking errors are comparable to the errors in RTHS of linear spring systems. The hybrid SDOF results are compared to an independently validated thermal- mechanical viscoelastic model to further validate the ability for the platform to test nonlinear systems. After the validation, as an application study, nonlinear SDOF hybrid tests were used to develop performance spectra to predict the response of structures equipped with damping systems that are more challenging to model analytically. The use of the experimental performance spectra is illustrated by comparing the predicted response to the hybrid test response of 2DOF systems equipped with viscoelastic-plastic dampers.

跨语言用户态文件系统框架读写性能优化

以深度学习为代表的数据分析应用越来越多依赖分布式文件系统存储管理大规模数据集.为了增强数据访问的兼容性,现有分布式文件存储系统通常需提供标准POSIX接口,以支持深度学习等应用的无缝对接.然而,以内核模块形态开发提供POSIX接口的文件系统非常复杂耗时.近年来,用户态文件系统(Filesystem in Userspace,FUSE)框架大幅简化了文件系统的开发工作,已被Alluxio和Ceph等诸多知名分布式文件系统使用.目前常用的用户态FUSE库libfuse仅提供C语言编程接口,但现有大数据分布式文件系统基本都是基于Java语言开发的(例如HDFS和Alluxio等),为了使基于Java语言开发的分布式文件系统可以对接C语言开发的FUSE库,需采用跨语言FUSE框架作为中介.跨语言FUSE框架利用跨编程语言的函数回调机制,使操作系统FUSE库的C语言函数可以跨语言的调用分布式文件系统提供的Java语言编程接口,从而为大数据分布式文件系统提供标准POSIX接口的访问能力.但在数据密集型应用中,现有跨语言FUSE框架的执行效率低,导致数据密集型作业(深度学习、大数据分析等)中数据I/O耗时占据了显著的性能开销,成为新的潜在性能瓶颈.针对此问题,本文首先评估分析了重要且广为使用的跨语言FUSE框架JNR-FUSE的性能,发现并定位其在高并发和小文件场景下存在的性能瓶颈;接着从多方面剖析性能瓶颈根因,进而总结出高效跨语言FUSE框架的性能优化方向,并面向Java语言设计实现了跨语言FUSE框架JNI-FUSE.JNI-FUSE利用延迟分离和元信息缓存等优化技术降低跨语言函数回调开销,从而提升跨语言FUSE框架的性能.实验结果表明,对比当前性能最好的Java FUSE框架JNR-FUSE,本文提出的JNI-FUSE带来了1.15~6.04倍的FUSE框架性能提升和1.90~2.71倍的文件系统端到端性能提升,并为上层深度学习训练任务带来了1.06~1.73倍的训练加速.本文设计提出的JNI-FUSE(Java Native Interface-Filesystem in User SpacE)因性能优势,已被知名开源分布式文件系统Alluxio官方接受集成.

“公开表达的顾客契合”如何驱动跨境电商企业绩效提升——基于顾客群体传染效应的视角

跨境电商在数字化与全球化引擎的共同驱动下产生并迅速发展,已成为国际贸易中与传统贸易独立并行的又一重要渠道,在服务主导的商业逻辑中,跨境电商企业与海外顾客的契合关系创造企业价值。本文首次基于顾客群体传染效应的视角,从理论与实证两个维度探索“公开表达的顾客契合”驱动跨境电商企业绩效提升的作用机制,应用社会网络影响理论、IV-Heckit及被调节的中介模型,创新构建组合测度模型以挖掘用户生成内容。研究结果表明:(1)公开表达的顾客契合异质性驱动跨境电商企业绩效,即顾客—企业契合相较于顾客—产品契合的驱动效应更显著,与国内电商情境下的结论存在差异;(2)契合在目标顾客群体间发挥传染效应,具体以“情感偏好”与“特征关注”传染效应的双中介渠道驱动绩效提升;(3)与品牌效应高度相关的企业定价水平U型调节了群体传染效应的作用边界,为跨境电商企业“中等价格陷阱”提供了顾客感知价值视角的解释。本研究为跨境电商企业与顾客价值共创提供了可靠的理论依据与实证支撑,为实现以海外目标顾客为主导的品牌建设实践提供了科学、准确的管理启示。

Zero-forcing beamforming with receiver antenna selection in downlink multi-antenna multi-user system

A study on the zero-forcing beamforming （ZFBF） scheme with antenna selection at user terminals in downlink multi-antenna multi-user systems is presented. Simulation results show that the proposed ZFBF scheme with receiver antenna selection （ZFBF-AS） achieves considerable throughput improvement over the ZFBF scheme with single receiver antenna. The results also show that, with multi-user diversity, the ZFBF-AS scheme approaches the throughput performance of the ZFBF scheme using all receiver antennas （ZFBF-WO-AS） when the base station adopts semi-orthogonal user selection （SUS） algorithm, and achieves larger throughput when the base station adopts the Round-robin scheduling algorithm. Compared with ZFBF-WO-AS, the proposed ZFBF-AS scheme can reduce the cost of user equipments and the channel state information requirement at the transmitter （CSIT） as well as the multiuser scheduling complexity at the transmitter.