一种轻量级的雾计算属性基外包加密算法

为减少属性基加密算法占用的资源,在安全数据访问控制的属性基加密算法的基础上提出了一种改进的属性基外包加密算法。改进算法将加密算法中的复杂双线性对计算外包给雾节点以减少用户的计算开销;同时通过简化系统参数,减少属性中心为属性生成的随机因子以缩短密文和密钥长度,降低了用户和雾节点的存储和通信开销。同时对提出的改进算法进行了安全性证明,证明了该改进算法是安全的。     

Load balancing aware scheduling algorithms for fog networks

Fog networks have attracted the attention of researchers recently. The idea is that a part of the computation of a job/application can be performed by fog devices that are located at the network edge, close to the users. Executing latency sensitive applications on the cloud may not be feasible, owing to the significant communication delay involved between the user and the cloud data center (cdc). By the time the application traverses the network and reaches the cloud data center, it might already be too late. However, fog devices, also known as mobile data centers (mdcs), are capable of executing such latency sensitive applications. In this paper, we study the problem of balancing the application load while taking account of security constraints of jobs, across various mdcs in a fog network. In case a particular mdc does not have sufficient capacity to execute a job, the job needs to be migrated to some other mdc. To this end, we propose three heuristic algorithms: minimum distance, minimum load, and minimum hop distance and load (MHDL). In addition, we also propose an ILP-based algorithm called load balancing aware scheduling ILP (LASILP) for solving the task mapping and scheduling problem. The performance of the proposed algorithms have been compared with the cloud only algorithm and another heuristic algorithm called fog-cloud-placement (FCP). Simulation results performed on real-life workload traces reveal that the MHDL heuristic performs better as compared to other scheduling policies in the fog computing environment while meeting application privacy requirements.     

相干激光引信在云雾干扰下的回波特性研究

为分析相干激光引信在云雾干扰下的探测性能,基于Mie散射理论和Monte Carlo方法建立了相干激光引信在云雾中的探测模型,仿真获取相干激光引信在多种云雾干扰场景下的探测回波,分析回波信号的时域和频域特性,以及云雾能见度、探测位置和探测角度对回波特性的影响。研究结果表明,相干激光引信可利用回波频域特征准确探测和识别目标,且不易受云雾能见度、探测位置和探测角度等因素的影响。结果证明:相干激光引信在云雾干扰下具有优良的探测性能。     

基于深度卷积神经网络的自适应图像去雾算法

室外拍摄图像由于受雾气、雾霾、沙尘等大气颗粒杂质的影响呈现出图像灰白化,而现有的图像去雾算法存在过度依赖先验信息、透射率计算不精确的问题。针对上述问题,文中提出了一种基于深度卷积神经网络的自适应图像去雾算法。该算法基于大气散射模型实现了有雾图像的去雾,设计浅层提取、并行提取和深度融合共3个全卷积网络实现图像浅层特征与深层特征的融合,大幅提高了透射率图的准确性。去雾实验测试结果表明,文中所提出的算法对室外露天雾图具有良好的去雾效果,且去雾细节效果更加理想。     

浙江电网合成绝缘子运行使用评估与分析

本文评估了浙江电网合成绝缘子的运行使用情况,分析了合成绝缘子污（雾）闪络和雷击闪络及芯棒脆断的原因,并提出了防止闪络的有效措施。     

基于CFD的挑流泄洪雾化特性研究

针对泄洪雾化影响范围不易采用数学模型直接模拟的问题,以某高坝电站泄洪为研究对象,先采用三维数学模型计算挑流水舌入水流速、入水角度等水力特征值,再基于此特征值选用原型观测校正后的计算公式预报泄洪雾化范围,并通过物理模型试验对计算结果进行验证分析。结果表明,受比尺效应影响,物理模型试验预测的雾化影响范围小于公式计算的范围,但两者的变化趋势一致;雾流受惯性力和水舌风作用,沿水舌轴线做爬坡运动,与原型观测现象一致;受出口挑流影响,泄洪雾化影响集中在水舌落入点的下游,而水垫塘上游、右岸降雨强度较小,影响范围有限。     

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

The evolutionary advancements in the field of technology have led to the instigation of cloud computing. The Internet of Things paradigm stimulated the extensive use of sensors distributed across the network edges. The cloud datacenters are assigned the responsibility for processing the collected sensor data. Recently, fog computing was conceptuated as a solution for the overwhelmed narrow bandwidth. The fog acts as a complementary layer that interplays with the cloud and edge computing layers, for processing the data streams. The fog paradigm, as any distributed paradigm, has its set of inherent challenges. The fog environment necessitates the development of management platforms that effectuates the orchestration of fog entities. Owing to the plenitude of research efforts directed toward these issues in a relatively young field, there is a need to organize the different research works. In this study, we provide a compendious review of the research approaches in the domain, with special emphasis on the approaches for orchestration and propose a multilevel taxonomy to classify the existing research. The study also highlights the application realms of fog computing and delineates the open research challenges in the domain.     

Genetic algorithm‐based content distribution strategy for F‐RAN architectures

Fog radio access network (F‐RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm‐based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F‐RAN. First, an F‐RAN system model is presented that includes a certain number of randomly distributed fog access points (F‐APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F‐RANs is described. Third, the details of the proposed optimal genetic algorithm‐based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.     

车联网中基于雾计算和多TA的条件隐私保护认证方案

车联网在生活中扮演着越来越重要的角色,它可以有效地防止交通拥堵从而减少交通事故。然而,在车联网中总是有非法车辆试图接入车联网并发布虚假消息。此外,现有方案多数存在计算效率低下的问题。针对上述存在的问题进行了研究,提出了一种车联网中基于雾计算和多TA的条件隐私保护认证方案。在保护车辆用户身份的条件下实现了车辆、雾节点、TA三者之间的身份认证,且在车辆追踪阶段可以还原车辆用户的真实身份,从而实现条件隐私保护。雾计算的使用降低了方案的计算和通信开销,同时多TA模型的使用也解决了单TA单点故障的问题。安全性证明和性能分析的结果表明该方案是安全且高效的。最后对当前方案进行了总结以及对未来研究作出了展望。     

纤维除雾器及其在化工生产中的应用

介绍了雾粒的形成原因，纤维除雾器的除雾机理，床层设计，产品分类，清洁状态下压力降计算及安装方法，以及纤维除雾在化工行业的典型应用，建议在我国进一步推广应用。