水下分布式远程感知技术的发展

目前,水下分布式远程感知技术已经具备了快速发展的基本条件,备受各主要海军国家的重视,预期在未来5~10年内将会有重大进展。但水下分布式远程感知技术的发展还面临着从基础、理论到实践的众多课题,包括系统构成和运用的概念,分布式传感器阵对目标的探测、分类和识别,固定、可部署传感器和移动节点构成的传感器场的配置,水下分布式网络的通信和控制,以及系统的部署和保障等。本文讨论水下分布式远程感知系统的基本组成,实现系统功能所面临的主要挑战,需要关注的主要关键技术,并提出相应的看法和建议。     

A New Wireless Packet Scheduling Algorithm Based on EDF and Its Application in Multi-bottleneck Networks

Most of current wireless packet scheduling algorithms aim at resource allocation as fairly as possible or maximizing throughput. This paper proposed a new packet scheduling algorithm that aims at satisfying delay requirement and is the improvement of earliest due first (EDF) algorithm in wired networks. The main idea is to classify the packets based on their delay bound, scheduling the most "urgent" class of user and the users that have the best channel condition with higher priority. This algorithm can easily integrate with common buffer management algorithms, when buffer management algorithm cannot accept new arrival packets, try to modify scheduling policy. Packet scheduling algorithms in multiple bottleneck wireless networks were also discussed. A new variable multi-hop factor was defined to estimate the congestion situation (including channel condition) of future hops. Multi-hop factor can be integrated into packet scheduling algorithms as assistant and supplement to improve its performance in multi-bottleneck wireless networks.     

一种基于单个移动信标的分布式节点定位算法

定位是无线传感器网络中最重要的功能之一。通过利用一个移动信标节点（装备GPS或提前设定了移动路线）来帮助各个未知节点进行自身定位。信标节点周期性的发送自己位置信息给周围的未知节点,未知节点通过非测距技术估计自身位置。信标节点的移动路径在文中也进行了探讨。仿真结果说明了本文方法的有效性。     

Competition and disruption in a dynamic urban supply chain

Rapid changes and complexities in business environments have stressed the importance of interactions between partners and competitors, leading supply chains to become the most important element of contemporary business environments. There is a concomitant need for foresight in describing supply chain performance in all operating environments, including those involving punctuated disruptions. Furthermore, the urban metropolis is now widely recognized to be an environment which is especially vulnerable to supply chain disruptions and for which integrated supply chain decisions can produce very substantial net benefits. Accordingly, this paper presents a dynamic supply chain network model formulated as a differential variational inequality; the model is fashioned to allow consideration of supply chain disruption threats to producers, freight carriers, and retail enterprises. The DVI is solved using a fixed-point algorithm, and a simple numerical example, introduced to illustrate how the impacts of supply chain disruptions may be quantified, is presented.     

介入移动汇聚节点的无线传感器网络高效数据收集方法

引入移动汇聚节点解决无线传感器网络高效数据收集问题.网络中固定汇聚节点与移动汇聚节点共存,全部传感器节点都拥有维护到固定汇聚节点的路由,移动汇聚节点进入网络后定期向其附近小范围内的传感器节点扩散自己的声明信息,传感器节点向距自己跳数最小的汇聚节点发送或转发数据包.移动汇聚节点和距离其一跳的传感器节点之间通过有效的应答机制来保证数据的可靠传输.通过仿真结果显示引入移动汇聚节点的数据收集在节省能耗方面明显优于传统网络.在延长网络生存时间的同时,可以获得较高的数据传输成功率和较短的数据传输延迟.     

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针对目前广泛应用于城市轨道交通信号系统中,基于IEEE802.11系列标准的两种WLAN传输方式——空间自由波和波导管. 简要分析两种传输方式的工程和技术特点. 深入分析WLAN射频覆盖和通信机制. 结合北京轨道交通亦庄、昌平线组合传输方法的应用实例,提出空间自由波和波导管进行组合的组合传输无线覆盖方式,并简要介绍车地无线通信系统的系统结构和工作方式,无线AP的性能特点和分布原则. 计算WLAN自由空间损耗、信号接收强度、链路系统裕量. 提出WLAN技术在信号系统车地通信中应用的前景.     

铁路路网运输能力可靠性研究

铁路路网运输能力可靠性是指在规定的条件(路网结构、固定设备、移动设备及一定人力与运输组织水平)下和规定的时间内,考虑日常随机因素以及不可抗力因素等的影响,铁路路网所能提供的各种服务能满足OD需求波动的能力.本文在分析了国内外路网能力可靠性研究和铁路运输的特点上,提出了铁路路网能力可靠性的概念,并构建了相关路网能力的计算...     

无标度网下传播拥塞量与时间关系的研究

文章以复杂网络知识为基础,通过对无标度网络及度分布平均场的介绍,利用网络中度与集群系数的联系,研究因特网信息包传播过程中的一般拥塞模型,并解析无标度网络中的拥塞量与时间的关系。这样就能够预测拥塞量,以便及时有效执行相关措施     

Asynchronous n-step Q-learning adaptive traffic signal control

Ensuring transportation systems are efficient is a priority for modern society. Intersection traffic signal control can be modeled as a sequential decision-making problem. To learn how to make the best decisions, we apply reinforcement learning techniques with function approximation to train an adaptive traffic signal controller. We use the asynchronous n-step Q-learning algorithm with a two hidden layer artificial neural network as our reinforcement learning agent. A dynamic, stochastic rush hour simulation is developed to test the agent’s performance. Compared against traditional loop detector actuated and linear Q-learning traffic signal control methods, our reinforcement learning model develops a superior control policy, reducing mean total delay by up 40% without compromising throughput. However, we find our proposed model slightly increases delay for left turning vehicles compared to the actuated controller, as a consequence of the reward function, highlighting the need for an appropriate reward function which truly develops the desired policy.     

Gantry crane operations to transfer containers between trains: A simulation study of a Spanish terminal

Freight transfer operations are critical in combined transport networks. In this paper a simulation model and modelling approach to the transfer of cargo between trains at rail terminals is presented. The model is used to study the Port-Bou terminal, the main intermodal terminal at the Spanish-French frontier. Four different gantry crane operation modes to interchange containers between trains are evaluated. These operation rules are tested in several scenarios to examine the critical factors of the system and the best operation rule for each situation. Latest generation software is used to develop the model that incorporates modular programming and enhanced graphic systems for output representation. It allows a dynamic display of the simulated system and, likewise, the possibility of developing modules that can be reused in other studies. The research shows how simulation can be a useful planning tool in the rail transportation context.