基于雾计算的智能工厂实时任务调度架构

针对传统的基于云的任务调度架构中没有充分利用智能工厂的资源,以及远距离传输导致高传输时延的问题,提出了一种基于雾计算的实时任务调度架构。设计了一种基于雾计算的智能工厂网络架构;考虑到工厂任务的时延敏感性和优先级特性,提出了一种基于动态优先级的任务调度模型,该模型被雾节点用来调度和执行等待队列中的任务;基于提出的网络架构和任务调度模型,提出了一种任务卸载策略,该策略可以被用于解决智能工厂中的资源利用问题。仿真结果证明了提出的实时任务调度架构在智能工厂中应用的可行性和有效性。     

Fog Computing for Big Data Analytics in IoT Aided Smart Grid Networks

Wireless Personal Communications - The recent integration of Internet of Things and Cloud Computing (CC) technologies into a Smart Grid (SG) revolutionizes its operation. The scalable and unlimited...     

基于雾计算的智能电表用户虚拟环隐私保护方案

作为智能电网的基础组件,智能电表(SMS)可以定期向电力公司报告用户的详细用电量数据。但是智能电表也带来了一些安全问题,比如用户隐私泄露。该文提出了一种基于虚拟环的隐私保护方案,可以提供用电数据和用户身份的隐私,使攻击者无法知道匹配电力数据与用户身份的关系。在所提方案中,智能电表可以利用其虚拟环成员身份对其真实身份进行匿名化,并利用非对称加密和Paillier同态系统对其获得的用电量数据生成密文数据;然后智能电表将密文数据发送给其连接的雾节点,雾节点定期采集其管理的智能电表的密文数据。同时,雾节点对这些智能电表的虚拟环身份进行验证,然后将收集到的密文数据聚合并发送给控制中心;最后控制中心对聚合后的密文进行解密,得到用电量数据。实验结果表明所提方案在计算和通信成本上具有一定的优势。     

智能环境下基于雾计算的推理节点优化分配研究

智能环境传统的规则推理机制中,网关内布置的推理机从各种传感器中获取推理所需数据并与规则库相匹配,承担整个推理工作.本文利用Rete算法将规则构建为推理网络,并结合雾计算的概念将Rete推理节点分配至环境内配置的智能节点中协同推理以减轻网关负载,由此推理节点的分配成为关键,分配不合理将导致资源利用不平衡及响应延迟.本文利用活动影响下规则触发的规律设计了活动聚类算法CoA（Clustering of Activities）对活动聚类后分别建立其推理网络,计算出智能节点之间的最短路径后将结果代入针对其层次延迟性而设计的分配算法AAoRN（Allocation Algorithm of Rete Inference Nodes）,从而将推理节点最优分配至各个智能节点.理论分析和实验结果表明,本文机制在有效利用智能节点资源的同时降低了大致55%的延迟.     

A Deep Learning-Based Privacy-Preserving Model for Smart Healthcare in Internet of Medical Things Using Fog Computing

Wireless Personal Communications - With the emergence of COVID-19, smart healthcare, the Internet of Medical Things, and big data-driven medical applications have become even more important. The...     

云计算驱动了雾计算的发展

认为雾计算/边缘计算(MEC)是云计算的延伸,其发展源自物联网(IoT)实时反馈型应用需求的驱动,通过雾计算/MEC将数据采集、数据处理和应用分析程序集中在网络边缘设备中,使云端计算、网络、存储能力得以向边缘扩展。提出在IoT中采用中枢智能与边缘智能的两级架构,实现雾计算与云计算的协作,提高IoT处理效率。     

Energy-Harvesting Systems for Green Computing

Energy harvesting technologies provide a promising alternative to battery-powered systems and create an opportunity to achieve sustainable computing for the exploitation of ambient energy sources. However, energy harvesting devices and power generators encompass a number of non-classical system behaviors or characteristics, such as delivering nondeterministic power density, and these would create hindrance for effectively utilizing the harvested energy. Previously, we have investigated new design methods and tools that are used to enable power adaptive computing and, particularly, catering non-deterministic voltage, which can efficiently utilize ambient energy sources. Also, we developed a co-optimization approach to maximize the computational efficiency from the harvested ambient energy. This paper will provide a review of these methods. Emerging technologies, such as 3D-IC, which would also enable new paradigm of green and high-performance computing, will be also discussed.     

Smart Identification Frameworks for Ubiquitous Computing Applications

We present our results of the conceptual design and the implementation of ubiquitous computing applications using smart identification technologies. First, we describe such technologies and their potential application areas, then give an overview of some of the applications we have developed. Based on the experience we have gained from developing these systems, we point out design concepts that we have found useful for structuring and implementing such applications. Building upon these concepts, we have created two frameworks based on Jini (i.e., distributed Java objects) and Web Services to support the development of ubiquitous computing applications that make use of smart identification technology. We describe our prototype frameworks, discuss the underlying concepts and present some lessons learned.     

一种适用于雾计算的终端节点切换认证协议

针对当前雾计算环境下终端节点的切换认证协议在存储量、计算量和安全性等方面还存在缺陷,该文提出一种高效的终端节点切换认证协议。在该协议中,采用双因子组合公钥(TF-CPK)和认证Ticket相结合的方式,实现雾节点和终端节点的相互认证和会话密钥协商。安全性和性能分析结果表明,该协议支持不可跟踪性,可以抵抗众多已知攻击和安全威胁,且具有较小的系统开销。     

A Latency-Aware Multiple Data Replicas Placement Strategy for Fog Computing

Journal of Signal Processing Systems - With the rapid increase of the number of IoT devices, transmitting big amount of data from these devices to data centers which are far away will cause...     

Secure and Efficient Computing Resource Management in Blockchain-Based Vehicular Fog Computing

In vehicular fog computing(VFC),the resource transactions in the Internet of Vehicles(IoV)have become a novel resource management scheme that can improve system resource utilization and the quality of vehicle services.In this paper,in order to improve the security and fairness of resource transactions,we design a blockchain-based resource management scheme for VFC.First,we propose the concept of resource coin(RC)and develop a blockchain-based secure computing reource trading mechanism in terms of RC.As a node of the blockchain network,the roadside unit(RSU)participates in verifying the legitimacy of transactions and the creation of new blocks.Next,we propose a resource management scheme based on contract theory,encouraging parked vehicles to contribute computing resource so that RSU could complete proof of work(PoW)quickly,improve the success probability of block creation and get RC rewards.We use the gradient descent method to solve the computing resource utilization that can maximize the RC revenue of RSUs and vehicles during the block creation.Finally,the performance of this model is validated in simulation result and analysis.     

An Energy-Efficient Load Balancing Approach for Scientific Workflows in Fog Computing

Wireless Personal Communications - Fog computing provides cloud services at the user end. User requests are processed on the fog nodes deployed near the end-user layer in a fog computing...     

TD-SCDMA智能天线电磁辐射计算方法分析

由于TD-SCDMA智能天线的赋形特性不同于一般移动通信天线,智能天线的电磁辐射特性也与其他移动通信电线不同,本文由此提出在智能天线的系统中进行电磁辐射计算时需要考虑的一些因素,以及对智能天线电磁辐射的计算方法。     

Proactive Load Balancing Mechanism for Fog Computing Supported by Parked Vehicles in IoV-SDN

Internet of Vehicles(IoV)is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles’sensors through the internet.These sensors generate different tasks that should be analyzed and processed in some given period of time.They send the tasks to the cloud servers but these sending operations increase bandwidth consumption and latency.Fog computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing facilities.In some situations,fog computing cannot execute some tasks due to lack of resources.Thus,in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation again.Moreover,several fog servers may be fuelled while other servers are empty.This implies an unfair distribution of jobs.In this research study,we shall merge the software defined network(SDN)with IoV and fog computing and use the parked vehicle as assistant fog computing node.This can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud servers.This increases the ratio of time sensitive tasks that meet the deadline.In addition,a new load balancing strategy is proposed.It works proactively to balance the load locally and globally by the local fog managers and SDN controller,respectively.The simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog-Cloud frameworks in terms of average response time and percentage of bandwidth consumption,meeting the deadline,and resource utilization.     

QoE Aware IoT Application Placement in Fog Computing Using Modified-TOPSIS

Mobile Networks and Applications - Over the years, fog computing has emerged as a paradigm to complement the cloud computing in handling the delay sensitive IoT applications in a better manner....     

基于雾计算的NB-IoT框架、关键技术及应用

针对窄带物联网(NB-IoT)技术特点和业务类型,提出了基于雾计算的NBIoT网络架构,通过为NB-IoT接入点(AP)配置雾计算设备,将接入点升级为具有存储和计算能力的雾接入点(F-AP),使得数据收集、传输、处理和计算更靠近终端设备,提高应用系统的响应速度,节约网络带宽。     

Editorial: Big Data Innovation for Sustainable Cognitive Computing

Mobile Networks and Applications -     

云计算在智能电网中的应用及其安全问题研究

文章认为在智能电网中引入云计算,构建智能电网云可以为智能电网的发展提供有效支持。基于智能电网的特征,依托作为一种崭新的存储和计算模式的云计算技术,文章阐述了云计算技术如何为智能电网的数据存储和分析提供技术支持,设计了一种智能电网云计算的结构,分析了云计算技术给智能电网带来的诸多益处;并就智能电网云可能存在的安全威胁和相应的防范措施进行讨论。     

面向绿色计算的车辆协同任务卸载方法

车辆边缘计算(VEC)为处理计算密集、延迟敏感型任务提供了新的范式,然而边缘服务器在整合可再生能源方面的能力较差。因此,为了提高边缘服务器的能效,该文设计了一种面向绿色计算的车辆协同任务卸载框架。在该框架中,车辆配备能源收集(EH)设备,通过彼此间共享绿色能源和计算资源协作执行任务。为有效促进车辆的参与积极性,该文通过动态定价激励车辆,并综合考虑了车辆的移动性、任务优先级等。为了使卸载决策适应动态环境的变化,该文提出了一种基于双延迟深度确定性策略梯度(TD3)的任务卸载方法,以在最大化所有车辆平均任务完成效用的同时减少边缘端电网电力的使用。最后,仿真结果验证了该方法的有效性,相比基于深度确定性策略梯度(DDPG)和基于贪心原则(GPE)的方法在性能上分别提升了7.34%和37.47%。     

Towards a Sustainable Green Design for Next-Generation Networks

Recently distributed real-time database systems are intended to manage large volumes of dispersed data. To develop distributed real-time data processing, a reality and stay competitive well defined protocols and algorithms must be required to access and manipulate the data. An admission control policy is a major task to access real-time data which has become a challenging task due to random arrival of user requests and transaction timing constraints. This paper proposes an optimal admission control policy based on deep reinforcement algorithm and memetic algorithm which can efficiently handle the load balancing problem without affecting the Quality of Service (QoS) parameters. A Markov decision process (MDP) is formulated for admission control problem, which provides an optimized solution for dynamic resource sharing. The possible solutions for MDP problem are obtained by using reinforcement learning and linear programming with an average reward. The deep reinforcement learning algorithm reformulates the arrived requests from different users and admits only the needed request, which improves the number of sessions of the system. Then we frame the load balancing problem as a dynamic and stochastic assignment problem and obtain optimal control policies using memetic algorithm. Therefore proposed admission control problem is changed to memetic logic in such a way that session corresponds to individual elements of the initial chromosome. The performance of proposed optimal admission control policy is compared with other approaches through simulation and it depicts that the proposed system outperforms the other techniques in terms of throughput, execution time and miss ratio which leads to better QoS.