Ad Hoc网络区域最小覆盖方法研究

覆盖控制作为无线传感器网络中的一个基本问题,反映了网络所能提供的“感知”服务质量,可以使无线传感器网络的空间资源得到优化分配,进而更好地完成环境感知、信息获取和有效传输的任务.如何计算同时满足“覆盖要求”（工作节点必须能够完全覆盖目标区域）和“连通性要求”（工作节点组成的通信网络必须是连通的）的最小节点集合,是一个NP难问题.本文设计了一种基于目标区域Voronoi划分的改进集中式近似算法,用于计算完全覆盖目标区域所需要的近似最小节点集.     

基于模糊均值聚类的调峰调频信息控制方法研究

随着分布式能源大规模接入电网,接入电力网络的信息呈多元化趋势发展。为解决分布式能源调峰调频控制信息时延保障的问题,提出了一种基于模糊均值聚类的调峰调频信息控制方法。首先,对分布式能源信息进行聚类,并对分布式能源按控制、信息类划分传输优先级。其次,建立多个网段的流量协作控制单元,对区域网络进行统一控制。然后,通过边缘计算判断当前网段节点流量数据是否越限,对超过流量阈值的信息类数据进行流量卸载,降低调峰调频信息的传输时延。最后,在某区域配电网进行实例验证。该方法的数据分析准确率平均为99.7%,高于四阶累积量方法。其运行结果验证了该方法的有效性。     

IT业的“红移”

“未来全世界可能只需要几百台系统,就可以满足全世界的计算需求。这几百台系统可能会分布在不同的区域,通过分布式网络与个人用户连接在一起。”Sun公司首席技术官兼执行副总裁Greg Papadopoulos如此畅想由他所提出的“红移”理论的前景。     

HowU网格自适应调度模型

随着互联网的迅速发展，基于异构分布式网络的高性能计算平台——计算网格，成为了一种新型的计算模式。介绍了基于G10bus的HowU网格的实现技术，通过资源请求代理进行网格作业提交。为了有效利用网格资源，以“参数考察”任务为例，提出了一种自适应网格任务调度模型，该模型充分考虑了任务的实时容错需求。最后比较分析了该模型与Globus协作分配策略和GRADS分配框架的性能差异．     

一个分布式入侵检测系统框架设计

提出了一个网络环境下分布式入侵检测系统的框架。描述了将原始网络报文分组加工组织成相当于单词和文本的结构形式的方法，通过聚类发现相当于文本类特征词的方法，以及通过分类算法实现网络入侵检测的方法。讨论了控制节点的agent如何将完整的入侵检测任务合理组织分配到分布在各计算节点上的agent，并协调各计算任务的并发过程。     

基于分布式遗传算法以太无源光网络设计

针对以太无源光网络中各个光网络单元连接到光分配网络,再将光分配网络连接到光线路终端的全部通信费用为最小的问题,介绍了分布式遗传算法（DGA）,该算法在分群操作的基础上,根据每个子群进化的优劣程度动态地划分子群大小、控制子群间个体的迁移方向,采用分布式遗传算法对以太无源光网络进行设计建模,利用分布式遗传算法使路径搜索更快,更好的收敛于最优的特点,使得光分配网连接到光线路终端的路径和为最小,解决了降低网络通信费用的问题。     

基于代理的分布式网络实时取证模型及关键技术研究

该文在分析分布式网络犯罪入侵特点的基础上,提出基于移动Agent和静态Agent技术相结合的分布式网络实时取证系统模型MADBFS,它采用“分布取证、动态协调、区域监督、全局推理”概念模型,用一个类似树状的结构来构造分布式网络实时取证系统。并对MADRFS中证据完整性保护、证据信息可靠与高速获取、系统的健壮性与容忍性、动态协调移动Agent取证、Agent之间协调得相互关系等关键技术进行了探讨。     

网络环境下虚拟机器人——“SoftMan”系统平台总体设计

基于网络环境虚拟机器人的计算模式融合分布式人工智能、并行分布式系统、移动智体和人工生命的技术,是计算机网络时代的一项崭新而关键技术,不仅会实现更灵活的分布式异步计算,而且将把网络计算带入一个全新的智能化时代。这种计算方式在如何充分利用网络资源,如何给移动用户提供高效的服务等诸多问题上提供了新的思路,目前主要研究领域集中在动态信息获取、智能网络、电子商务、主动网络和移动智能通信网络等。本文系统阐述“SoftMan”系统平台的设计方法、开发策略、总体架构和软件实现,同时对其相关支撑技术进行了剖析;最后就“Soft—Man”系统开发的思路和未来研究趋势进行了展望。     

分布式SDN控制器放置问题研究

软件定义网络(Software-Defined Networking,SDN)通过控制平面与数据平面的分离和逻辑集中的控制构建了新的网络范式.考虑性能、可扩展性和可靠性等方面的需求,大规模网络通常采用分布式SDN控制平面,即通过放置多个控制器共同管理整个网络.这需要确定控制器的放置数量、放置位置以及交换机到控制器的分配...     

无线局域网分布式自适应信道分配

提出一种分布式自适应信道分配算法,利用全面的动态网络信息增加信道选择的正确性,引入退避机制减少信道分配中的冲突开销。在网络仿真平台NS2上对算法进行大量实验。结果表明,与传统分布式信道分配算法相比,该算法具有干扰检测率高、可靠稳定的特点,从而有效提高网络整体吞吐量。     

Making Procedural Water Waves Boundary-aware

The “procedural” approach to animating ocean waves is the dominant algorithm for animating larger bodies of water in interactive applications as well as in off-line productions — it provides high visual quality with a low computational demand. In this paper, we widen the applicability of procedural water wave animation with an extension that guarantees the satisfaction of boundary conditions imposed by terrain while still approximating physical wave behavior. In combination with a particle system that models wave breaking, foam, and spray, this allows us to naturally model waves interacting with beaches and rocks. Our system is able to animate waves at large scales at interactive frame rates on a commodity PC.     

Energy dispatch controllers for a photovoltaic system

In this paper two energy dispatch controllers for use in a grid-independent photovoltaic (PV) system are presented. The first, an optimal energy dispatch controller, is based on a class of Adaptive Critic Designs (ACDs) called Action Dependent Heuristic Dynamic Programming (ADHDP). This class of ACDs uses two neural networks to evolve an optimal control strategy over time. The first neural network or “Action” network dispenses the actual control signals while the second network or “Critic” network uses these control signals along with the system states to provide feedback to the action network, measuring performance using a utility function. This feedback loop allows the action network to improve behavior over time. The optimal energy dispatcher places emphasis on always meeting the critical load, followed by keeping the charge of the battery as high as possible so as to be able to power the critical load in cases of extended low output from the PV array, and lastly to power the non-critical load in so far as to not interfere with the first two objectives. The second energy dispatch controller is a smart energy dispatch controller and is built using knowledge from an expert, codified into a series of static rules. This smart energy dispatch controller is called the “PV-priority 2” controller. These energy dispatchers are compared with a static scheme called the “PV-priority 1”. The PV-priority 1 controller represents the standard control strategy. Results show that the ADHDP-based optimal energy dispatcher (or controller) outperforms the standard PV-priority 1 energy dispatcher in meeting the stated objectives, but trails the PV-priority 2 energy dispatcher. However, the major advantage of the ADHDP controller is that no expert is required for designing the controller, whereas for a rule-based controller such as the PV-priority 2 controller, an expert is always required.     

基于移动节点的无线传感器网络覆盖空洞修复方法

无线传感器网络（ WSNs）一旦产生覆盖空洞,则会严重影响网络性能,针对此问题,提出了一种基于移动节点的覆盖空洞修复算法——联合补丁法,该算法按照预先制定的缝制方案把所需的移动节点“缝制”成一块大的“布”,然后对空洞进行直接修复。首先,在理论上证明了该算法的性能;其次,用Matlab进行仿真实验,并与基于移动节点的三角形逐个贴片修复算法（ PATT）在所需节点数和冗余度两方面进行对比;最后,对算法的稳定性进行了分析。最终表明：该算法具有较高的覆盖率和较低的冗余度。     

Fast Filtered Sampling

Traffic sampled from the network backbone using uniform packet sampling is commonly utilized to detect heavy hitters, estimate flow level statistics, as well as identify anomalies like DDoS attacks and worm scans. Previous work has shown however that this technique introduces flow bias and truncation which yields inaccurate flow statistics and “drowns out” information from small flows, leading to large false positives in anomaly detection.In this paper, we present a new sampling design: Fast Filtered Sampling (FFS), which is comprised of an independent low-complexity filter, concatenated with any sampling scheme at choice. FFS ensures the integrity of small flows for anomaly detection, while still providing acceptable identification of heavy hitters. This is achieved through a filter design which suppresses packets from flows as a function of their size, “boosting” small flows relative to medium and large flows. FFS design requires only one update operation per packet, has two simple control parameters and can work in conjunction with existing sampling mechanisms without any additional changes. Therefore, it accomplishes a lightweight online implementation of the “flow-size dependent” sampling method. Through extensive evaluation on traffic traces, we show the efficacy of FFS for applications such as portscan detection and traffic estimation.     

Visual analysis of machine learning methods in the field of ergonomics — Based on Cite Space V

To analyze the research hotspots on the application of machine learning methods in the field of ergonomics, we collected 1141 articles related to machine learning methods in the field of ergonomics from 2014 to 2021 on the Web of Science (WoS) database. Then we used Cite Space V 6.1. R2 to generate network maps and analyze the authors, institutions, countries, co-cited literature, and keywords. Results show that the correlation between authors in the formed author co-occurrence network is not strong, which indicates low cooperation among authors. In the analysis of research institutions, the University of Southampton is the most frequently cited literature in the United Kingdom. However, the US is leading in the country's co-occurrence network. “System” and “Model” are the top two cited keywords, while “Methodology” and “Decision-making” were active from 2015 to 2018, with a longer development time. Other keywords, including “Musculoskeletal disorders”, “Performance”, “Low back pain”, “Health”, and “Risk Factors”, are the most frequently cited keywords and have a high betweenness centrality. “Validation” and “Prediction” have recently become popular keywords in this field. Therefore, we conclude that the application of machine learning methods in the field of ergonomics will continue to increase year by year and that the development of machine learning methods in the field of ergonomics is gaining importance due to its cross-disciplinary nature. In ergonomics, machine learning methods will be further developed and widely used.     

The development of a new integral control model based on the analysis of three complex systems in Serbia

The aim of this paper is to analyse the results of research carried out in the railway, mining, and electric power systems in Serbia and form a new integral control model. The three methodological procedures are applied. First, analytical-synthetic methodological approach breaks down complex technical system into three parts: bio-cybernetic system, “operator”; technical system, “technology”; and additional system, “working environment.” Second, network planning method is used to analyse time, according to the critical path method. Third, fuzzy analytic hierarchy process determines the key research factors. General results of research are new integral control model, and new research areas and activities. The most prominent factors are: in “bio-cybernetic system”—operator’s arm reach, body postures and movement sequences, operator’s work, occurrence of stress, and occurrence of fatigue; in “technical system”—location and dimension of control desk, display panel, video display terminal, symbols on video display terminal, colours in control centres, and suitability of the keyboards; and in “supporting system”—illumination in control centres and relative humidity. Based on the analysis of factors and synthesis of results, the following recommendation are proposed: new control desk design; new display panel design; new design of the main and local lighting; new illumination and contrast characteristics, and environmental impact assessment. For research on a variety of complex technical systems, new integral control model can be applied, with corresponding extensions.     

基于SDN的蜂窝移动网络优化研究

现有的蜂窝网络不灵活、设备昂贵、控制平面协议复杂,配置界面由供应商定制。因此,本文考虑利用软件定义网络（SDN）的思想,简化蜂窝数据网络的设计和管理,并提供新业务。然而,要支持大量的用户频繁地流动、要对其行为进行细粒度的测量和控制并实10时跟进,这些都是对未来的SDN架构应该解决的新的可扩展性的挑战。所以本文提出了一种软件定义的蜂窝网络架构：一、允许控制器应用基于用户的属性来执行政策,而不是基于网络地址和位置;二、通过每台交换机上的本地代理,实现实时、细粒度的控制;三、将交换机进行扩展来支持像网络资源的深度包检测和头压缩,以满足移动数据服务的需求;四、支持基于用户的属性,而不是分组报头字段,进行网络资源的灵活切片,并通过15设置控制器进行无线资源的管理、准入控制和移动性控制,对基站和无线资源的进行灵活的“切片”。     

A Practical Method for Animating Anisotropic Elastoplastic Materials

This paper introduces a simple method for simulating highly anisotropic elastoplastic material behaviors like the dissolution of fibrous phenomena (splintering wood, shredding bales of hay) and materials composed of large numbers of irregularly-shaped bodies (piles of twigs, pencils, or cards). We introduce a simple transformation of the anisotropic problem into an equivalent isotropic one, and we solve this new “fictitious” isotropic problem using an existing simulator based on the material point method. Our approach results in minimal changes to existing simulators, and it allows us to re-use popular isotropic plasticity models like the Drucker-Prager yield criterion instead of inventing new anisotropic plasticity models for every phenomenon we wish to simulate.     

工业控制系统安全运维模式研究

信息技术在工业控制系统中的广泛运用,逐步打破了工业控制网络环境的封闭性,暴露了系统的脆弱性。国内外层出不穷的工控安全事件,给国家安全敲响了警钟,我国工业基础设施安全面临严峻挑战。基于上述背景,分析了我国大型工业企业,尤其是流程工业企业的工业控制系统运维现状。围绕人、财务、信息、技术四种资源,建立了工业控制系统安全运维模型,提出了安全运维本质对象是业务,阐述了数据、载体、环境和边界四种安全运维实体对象的内涵及其关联关系。基于ISO 27001信息安全管理体系,提出了工业控制系统“安全运维”和“运维安全”两种模式,并从服务对象和服务目标角度分析了两种模式的区别和共性。     

多中心联合取送货车辆路径优化与利润分配

共享模式是电商逆向物流的新发展趋势,在共享车辆与客户订单的条件下,考虑带时间窗约束的客户同时取送货情景,建立了MJVRPSDPTW（multi-centers joint vehicle routing problem with simultaneous delivery and pick-up and time window）模型。接着设计一种基于大邻域搜索的混合遗传算法进行求解,针对“多对多网络”设置虚拟中心并利用整体法优化,同时融合大邻域搜索算法中的“破坏”与“修复”算子,增强算法寻优能力。通过多组算例对比实验,证明该算法优于两阶段规划法与经典遗传算法。基于优化后的网络,利用Shapley值法对不同联盟情况下的各物流企业进行利润分配,结果证明大联盟最稳定且共同利润最大。