Mobility-aware coded caching in D2D communication networks

In this paper, we consider a cache-enable device-to-device (D2D) communication network with user mobility and design a mobility-aware coded caching scheme to exploit multicasting opportunities for reducing network traffic. In addition to the static cache memory that can be used to reap coded caching gains, we assign a dynamic cache memory to mobile users such that users who never meet can still exchange contents via relaying. We consider content exchange as an information flow among dynamic cache memories of mobile users and leverage network coding to reduce network traffic. Specifically, we transfer our storage and broadcast problem into a network coding problem. By solving the formulated network coding problem, we obtain a dynamic content replacement and broadcast strategy. Numerical results verify that our algorithm significantly outperforms the random and greedy algorithms in terms of the amount of broadcasting data, and the standard Ford–Fulkerson algorithm in terms of the successful decoding ratio.     

Coded Caching for Broadcast Networks with User Cooperation

Caching technique is a promising approach to reduce the heavy traffic load and improve user latency experience for the Internet of Things (IoT). In this paper, by exploiting edge cache resources and communication opportunities in device-to-device (D2D) networks and broadcast networks, two novel coded caching schemes are proposed that greatly reduce transmission latency for the centralized and decentralized caching settings, respectively. In addition to the multicast gain, both schemes obtain an additional cooperation gain offered by user cooperation and an additional parallel gain offered by the parallel transmission among the server and users. With a newly established lower bound on the transmission delay, we prove that the centralized coded caching scheme is order-optimal, i.e., achieving a constant multiplicative gap within the minimum transmission delay. The decentralized coded caching scheme is also order-optimal if each user’s cache size is larger than a threshold which approaches zero as the total number of users tends to infinity. Moreover, theoretical analysis shows that to reduce the transmission delay, the number of users sending signals simultaneously should be appropriately chosen according to the user’s cache size, and always letting more users send information in parallel could cause high transmission delay.     

An Umbrella Converse for Data Exchange: Applied to Caching,Computing, and Shuffling

The problem of data exchange between multiple nodes with storage and communication capabilities models several current multi-user communication problems like Coded Caching, Data Shuffling, Coded Computing, etc. The goal in such problems is to design communication schemes which accomplish the desired data exchange between the nodes with the optimal (minimum) amount of communication load. In this work, we present a converse to such a general data exchange problem. The expression of the converse depends only on the number of bits to be moved between different subsets of nodes, and does not assume anything further specific about the parameters in the problem. Specific problem formulations, such as those in Coded Caching, Coded Data Shuffling, and Coded Distributed Computing, can be seen as instances of this generic data exchange problem. Applying our generic converse, we can efficiently recover known important converses in these formulations. Further, for a generic coded caching problem with heterogeneous cache sizes at the clients with or without a central server, we obtain a new general converse, which subsumes some existing results. Finally we relate a “centralized” version of our bound to the known generalized independence number bound in index coding and discuss our bound’s tightness in this context.     

UAV caching in 6G networks: A Survey on models,techniques, and applications

The rapid development road map of 6G networks has posed a new set of challenges to both industrial and academic sectors. On the one hand, it needs more disruptive technologies and solutions for addressing the threefold issues including enhanced mobile broadband, massive machine-type communications, and ultra-reliable and low-latency communications. On the other hand, the ever-massive number of mobile users and Internet of Things devices conveys the huge volume of traffic throughout the 6G networks. In this context, caching is one of the most feasible technologies and solutions that does not require any system architecture changes nor costly investments, while significantly improve the system performance, i.e., quality of service and resource efficiency. Ground caching models deployed at macro base stations, small-cell base stations, and mobile devices have been successfully studied and currently extended to the air done by unmanned aerial vehicles (UAVs) to deal with the challenges of 6G networks. This paper provides a comprehensive survey of UAV caching models, techniques, and applications in 6G networks. In particular, we first investigate the entire picture of caching models moving from the ground to the air as well as the related surveys on UAV communications. Then, we introduce a typical UAV caching system and describe how it works in connection with all types of the transceivers, end users, and applications and services (A&Ss). After that, we present the recent advancements and analyses of the UAV caching models and common system performance metrics. Furthermore, the UAV caching with assisted techniques, UAV caching-enabled mechanisms, and UAV caching A&Ss are discussed to demonstrate the role of UAV caching system in 6G networks. Finally, we highlight the ongoing challenges and potential research directions toward UAV caching in 6G networks.     

Caching popularity-unknown contents for massive communication channels via deep Q-learning

In order to reduce the backhaul link pressure of wireless networks, edge caching technology has been regarded as a promising solution. However, with massive and dynamical communication connections, it is challenging to provide analytical caching solution to achieve the best performance, particularly when the requested contents are changing and their popularities are unknown. In this paper, we propose a deep Q-learning (DQN) method to address the issue of caching placement. Considering a content caching network containing multiple cooperating SBSs with unknown content popularity, we need to determine which content to cache and where to cache. Therefore, the learning network has to be designed for dual aims, one of which is to estimate the content popularities while the other is to assign contents to the proper channels. An elaborate DQN is proposed to make decisions to cache contents with limited storage space of base-station by considering channel conditions. Specifically, the content requests of users are first collected as one of the training samples of the learning network. Second, the channel state information for the massive links are estimated as the other training samples. Then, we train the network based on the proposed method thereby improving spectral efficiency of the entire system and reducing bit-error rate. Our major contribution is to contrive a caching strategy for enhanced performance in massive connection communications without knowing the content popularity. Numerical studies are performed to show that the proposed method acquires apparent performance gain over random caching in terms of average spectral efficiency and bit-error rate of the network.     

Coupled vehicle and information flows: Message transport on a dynamic vehicle network

A freeway with vehicles transmitting traffic-related messages via short-range broadcasting is a technological example of coupled material and information flows in complex networks: information on traffic flows is propagated via a dynamically changing ad hoc network based on local interactions. As vehicle and information propagation occur on similar time scales, the network dynamics strongly influences message propagation, which is done by the movement of nodes (cars) and by hops between nearby nodes: two cars within the limited broadcast range establish a dynamic link. Using the cars of the other driving direction as relay stations, the weak connectivity within one driving direction when the density of equipped cars is small can be overcome. By analytical calculation and by microscopic simulation of freeway traffic with a given percentage of vehicles equipped for inter-vehicle communication, we investigate how the equipment level influences the efficiency and velocity of information propagation. By simulating the formation of a typical traffic jam, we show how the non-local information about bottlenecks and jam fronts can travel upstream and reach potential users.     

Economical quantum secure direct communication network with single photons

In this paper a scheme for quantum secure direct communication (QSDC) network is proposed with a sequence of polarized single photons. The single photons are prepared originally in the same state $\vert 0\rangle$ by the servers on the network, which will reduce the difficulty for the legitimate users to check eavesdropping largely. The users code the information on the single photons with two unitary operations which do not change their measuring bases. Some decoy photons, which are produced by operating the sample photons with a Hadamard, are used for preventing a potentially dishonest server from eavesdropping the quantum lines freely. This scheme is an economical one as it is the easiest way for QSDC network communication securely.     

An evolution traffic network model considering the next-nearest neighbor

In this paper, an evolution traffic network model considering the influence of the next-nearest neighbor is constructed. Using the model, we focus on studying the topology of the evolution traffic network in order to understand the traffic dynamics better. First, the influence of the next-nearest neighbor on the cumulative degree distribution is investigated by altering the values of the sensitivity coefficients; then the influence of some important parameters (density, the maximum velocity, etc.) is also discussed; subsequently, we study the trend of the degree of the hub when the values of the parameters change; some hubs of the evolution network are given at last. In this model, the hub is denoted as the node whose ranking of the degree is at the top a fixed percentage. By studying the statistical properties of the traffic network, we can grasp the traffic dynamics so as to take the appropriate methods for the better traffic situations.     

Role of connectivity in congestion and decongestion in a communication network

We study network traffic dynamics in a two dimensional communication network with regular nodes and hubs. If the network experiences heavy message traffic, congestion occurs due to finite capacity of the nodes. We discuss strategies to manipulate hub capacity and hub connections to relieve congestion and define a coefficient of betweenness centrality (CBC), a direct measure of network traffic, which is useful for identifying hubs which are most likely to cause congestion. The addition of assortative connections to hubs of high CBC relieves congestion very efficiently. An erratum to this article is available at .     

Performance analysis of modified optical burst switching (OBS) ring network using dummy node

In the present paper an analytical model of an optical burst switching ring network which is capable to handle the variable incoming traffic intelligently is presented. An efficient node architecture and network operating protocol enhances the data throughput in a congested network. Here we propose a node architecture to ease the traffic congestion in a ring network involving a dummy server connected to backbone of the ring topology to ease the traffic flow into the ring by diverting the packets under the congestion situation. An appropriate mathematical model for the proposed node architecture has been developed employing packet queuing control to estimate the amount of carried traffic for different node parameters and the analysis has been further extended to investigate the network performance under different signaling techniques.     

X光环孔编码成像技术研究

着眼于惯性约束聚变实验研究中的应用,对X光环孔编码成像技术进行了研究。利用数值模拟的手段,分析了环孔的自相关函数及其对环孔编码成像技术图像重建的影响,对不同的图像重建技术进行了初步比较。基于星光II实验装置,利用自行研制的X光环孔编码成像系统进行了激光等离子体X光环孔编码成像技术的演示实验,获得了满意结果。     

Analysis of telephone network traffic based on a complex user network

The traffic in telephone networks is analyzed in this paper. Unlike the classical traffic analysis where call blockings are due to the limited channel capacity, we consider here a more realistic cause for call blockings which is due to the way in which users are networked in a real-life human society. Furthermore, two kinds of user network, namely, the fully connected user network and the scale-free network, are employed to model the way in which telephone users are connected. We show that the blocking probability is generally higher in the case of the scale-free user network, and that the carried traffic intensity is practically limited not only by the network capacity but also by the property of the user network.     

一种有效提高无标度网络负载容量的管理策略

现有研究表明明显的社团结构会显著降低网络的传输性能. 本文基于网络邻接矩阵的特征谱定义了链路对网络社团特性的贡献度, 提出一种通过逻辑关闭或删除对网络社团特性贡献度大的链路以提高网络传输性能的拓扑管理策略, 即社团弱化控制策略(CWCS 策略). 在具有社团结构的无标度网络上分别进行了基于全局最短路径路由和局部路由的仿真实验, 并与关闭连接度大的节点之间链路的HDF 策略进行了比较. 仿真实验结果显示, 在全局最短路径路由策略下, CWCS策略能更有效地提高网络负载容量, 并且网络的平均传输时间增加的幅度变小. 在局部路由策略下, 当调控参数0<α<2, 对网络负载容量的提升优于HDF策略. 关键词： 复杂网络 社团特性 负载容量 拓扑管理     

编码曝光相机系统设计

在研究编码曝光理论基础上,设计了应用型嵌入式编码曝光相机系统。在采集运动目标图像时,按照预设的编码时序控制曝光快门,得到了光生电荷多次叠加一次转移的图像。该图像为具有编码曝光信息的运动模糊图像,有更多的图像细节信息。编码曝光图像信号经过AD转换后将数据暂存在数据存储器,再经核心器件解码模块输出复原图像。实验结果证明,编码曝光相机能有效解决线性运动模糊问题。在相同测试条件下,利用无参考图像评价指标测试,编码曝光条件下复原图像质量的指标平均值均比一般单次曝光条件下复原图像质量提高了近2倍。     

Traffic flow monitoring in software-defined network using modified recursive learning

The recursive network design used in this paper to monitor traffic flow ensures accurate anomaly identification. The suggested method enhances the effectiveness of cyber attacks in SDN. The suggested model achieves a remarkable attack detection performance in the case of distributed denial-of-service (DDoS) attacks by preventing network forwarding performance degradation. The suggested methodology is designed to teach users how to match traffic flows in ways that increase granularity while proactively protecting the SDN data plane from overload. The application of a learnt traffic flow matching control policy makes it possible to obtain the best traffic data for detecting abnormalities obtained during runtime, improving the performance of cyber-attack detection. The accuracy of the suggested model is superior to the MMOS, FMS, DATA, Q-DATA, and DEEP-MC by 19.23%, 16.25%, 47.61%, 16.25%, and 12.04%.     

Performance analysis of a novel 5G architecture via Content-Centric Networking

Content-Centric Networking (CCN) is a recent paradigm conceived for future Internet architectures, where communications are driven by contents instead of host addresses. It binds the storage capacity into the network by using the in-network caching, which can reduce the transmission delay in the network. In this paper, a novel architecture of 5G via CCN, named as CCN-5G, is proposed. Meanwhile, the performance of CCN-5G are tested in the high-speed mobile environment. The simulation results show that the CCN-5G can achieve excellent performance and satisfy the future requirements of 5G.     

Fresnel波带板编码成像技术

介绍了Fresnel波带板编码成像原理,并设计出高空间分辨率的Fresnel波带板编码相机,用双孔可见光源对编码相机的成像进行了实验研究,表明该编码相机可以真实地还原源区的空间大小和形状。     

基于云服务器的地磁感应电流监测系统的设计

地磁暴引起的地磁感应电流(GIC) 可能引起变压器直流偏磁, 对电网的安全稳定运行带来威胁, 远程实时监测GIC对电网的GIC防御具有重要的指导意义。设计了一种基于云服务器的电网GIC远程监测系统, 数据采集终端实时采集变压器中性点的GIC, 多监测点数据经GPRS分端口发送至云服务器的内网进行存储, 用户可通过云服务器的公网IP远程访问并对数据进行绘图、下载等处理, 实现了电网GIC数据的实时发布与共享。结合空间天气的预测数据, 还可以初步实现GIC的预警。对系统的数据采集终端以及基于云服务器的监测软件平台两大模块进行了实验室及变电站现场测试, 测试结果表明该系统实现了设计要求, 满足功能需求。     

A game theory model of urban public traffic networks

We have studied urban public traffic networks from the viewpoint of complex networks and game theory. Firstly, we have empirically investigated an urban public traffic network in Beijing in 2003, and obtained its statistical properties. Then a simplified game theory model is proposed for simulating the evolution of the traffic network. The basic idea is that three network manipulators, passengers, an urban public traffic company, and a government traffic management agency, play games in a network evolution process. Each manipulator tries to build the traffic lines to magnify its “benefit”. Simulation results show a good qualitative agreement with the empirical results.