安家岭储煤场输煤暗道通风除尘技术应用研究

针对输煤暗道的生产工艺现状，提出了采用通风与密闭抽尘净化技术，结合转载落料点密闭干雾降尘等技术措施，实现了输煤暗道内粉尘的的综合治理，通过粉尘浓度在线监测系统进行智能化控制，实现对输煤暗道通风除尘系统的远程连续监测监控，输煤暗道转载点下风侧5 m作业人员通行的位置总粉尘浓度由380.8 mg/m3降至19.8 mg/m3，降尘效率达94.8%，呼吸性粉尘浓度从96.7 mg/m3降至8.4 mg/m3，降尘效率达91.3%，降尘效果较好，有效地解决了输煤暗道及其转载落料点的粉尘污染问题，为输煤暗道内的粉尘防治提供参考依据。     

FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This framework aims to improve the disease prediction accuracy by achieving two objectives: QoS guarantee of fog services and anomaly prediction of Medical data streams. We build a virtual FogMed environment and conduct comprehensive experiments on the public ECG dataset to validate the performance of FogMed. The experiment results show that it performs better than the cloud computing model for processing tasks with different complexities in terms of time efficiency.     

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.     

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。     

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。     

分散计算:技术、应用与挑战

在军事作战等对时延敏感的应用场景中,云计算无法满足用户的实时需求,因此分散计算应运而生。它利用智能手机、平板电脑、联网汽车和物联网终端等全球计算资源提供服务,并将云数据中心视为通用计算节点,彻底消除中心化,实现计算资源的分散化。分散计算将所有具有计算能力的设备连接起来,形成一个网络化的有机体,每个计算节点以协作和共享的方式为用户提供服务。与雾计算和边缘计算的本地化处理不同,该范式利用了网络中的空闲计算资源,绕过了局部计算能力的限制,得到了广泛的关注。首先,介绍了分散计算的研究背景,并给出了分散计算的定义;其次,详细介绍了分散计算的三种核心技术;随后,通过一些具体的应用场景实例化分散计算的概念,更好地分析了分散计算在万物互联时代的优势;最后,阐述了未来分散计算的研究方向以及面临的挑战。     

Securing Parked Vehicle Assisted Fog Computing With Blockchain and Optimal Smart Contract Design

Vehicular fog computing(VFC)has been envisioned as an important application of fog computing in vehicular networks.Parked vehicles with embedded computation resources could be exploited as a supplement for VFC.They cooperate with fog servers to process offloading requests at the vehicular network edge,leading to a new paradigm called parked vehicle assisted fog computing(PVFC).However,each coin has two sides.There is a follow-up challenging issue in the distributed and trustless computing environment.The centralized computation offloading without tamper-proof audit causes security threats.It could not guard against false-reporting,free-riding behaviors,spoofing attacks and repudiation attacks.Thus,we leverage the blockchain technology to achieve decentralized PVFC.Request posting,workload undertaking,task evaluation and reward assignment are organized and validated automatically through smart contract executions.Network activities in computation offloading become transparent,verifiable and traceable to eliminate security risks.To this end,we introduce network entities and design interactive smart contract operations across them.The optimal smart contract design problem is formulated and solved within the Stackelberg game framework to minimize the total payments for users.Security analysis and extensive numerical results are provided to demonstrate that our scheme has high security and efficiency guarantee.