Big data analytics meets social media: A systematic review of techniques,open issues,and future directions

Social Networking Services (SNSs) connect people worldwide, where they communicate through sharing contents, photos, videos, posting their first-hand opinions, comments, and following their friends. Social networks are characterized by velocity, volume, value, variety, and veracity, the 5 V’s of big data. Hence, big data analytic techniques and frameworks are commonly exploited in Social Network Analysis (SNA). By the ever-increasing growth of social networks, the analysis of social data, to describe and find communication patterns among users and understand their behaviors, has attracted much attention. In this paper, we demonstrate how big data analytics meets social media, and a comprehensive review is provided on big data analytic approaches in social networks to search published studies between 2013 and August 2020, with 74 identified papers. The findings of this paper are presented in terms of main journals/conferences, yearly distributions, and the distribution of studies among publishers. Furthermore, the big data analytic approaches are classified into two main categories: Content-oriented approaches and network-oriented approaches. The main ideas, evaluation parameters, tools, evaluation methods, advantages, and disadvantages are also discussed in detail. Finally, the open challenges and future directions that are worth further investigating are discussed.     

基于GRU和LSTM组合模型的车联网信道分配方法

针对车联网中高通信需求和高移动性造成的车对车链路(Vehicle to Vehicle, V2V)间的信道冲突及网络效用低下的问题,提出了一种基于并联门控循环单元(Gated Recurrent Unit, GRU)和长短期记忆网络(Long Short-Term Memory, LSTM)的组合模型的车联网信道分配算法。算法以降低V2V链路信道碰撞率和空闲率为目标,将信道分配问题建模为分布式深度强化学习问题,使每条V2V链路作为单个智能体,并通过最大化每回合平均奖励的方式进行集中训练、分布式执行。在训练过程中借助GRU训练周期短和LSTM拟合精度高的组合优势去拟合深度双重Q学习中Q函数,使V2V链路能快速地学习优化信道分配策略,合理地复用车对基础设施(Vehicle to Infrastructure, V2I)链路的信道资源,实现网络效用最大化。仿真结果表明,与单纯使用GRU或者LSTM网络模型的分配算法相比,该算法在收敛速度方面加快了5个训练回合,V2V链路间的信道碰撞率和空闲率降低了约27%,平均成功率提升了约10%。     

车联网场景下基于内容中心网络的优化缓存策略

车联网中,如何有效选择缓存位置和缓存内容对于提高整体网络性能至关重要。针对上述问题,引入了内容中心网络技术,提出了一种新的优化缓存策略——缓存位置和缓存内容的选择取决于车辆节点值和内容流行度(Vehicle Node Value and Content Popularity,VNVCP)。首先,定义了连通性、中间中心性和特征向量中心性3个车辆节点属性用来评估车辆节点的值,具有不同值的车辆节点缓存具有不同流行度的内容,内容的重要性由其受欢迎程度决定。其次,该策略利用不同类型内容受欢迎程度的差异确保缓存内容分布均匀,同时评估来自多个属性的车辆节点的值以提高车辆节点利用率。仿真结果表明,VNVCP在缓存命中率、平均跳数和传输延迟方面明显优于传统的LCE(Leave Copy Every where)、Prob(0.5)和MPC(Most Popular Content)。     

车联网中可证安全的分布式匿名高效边缘认证协议

针对当前车联网(IoV)中的分布式认证协议直接依赖于半可信路边单元(RSU)的问题,该文提出一种新的分布式认证模型。该模型中的RSU通过3阶段广播自发建立边缘认证区,利用区域内的RSU同步保存车辆的认证记录,RSU可以通过校验节点同步保存的认证记录来防止恶意RSU的异常认证行为。然后,利用切比雪夫混沌映射设计了IoV中的分布式匿名认证协议,通过车辆发送消息不直接携带身份信息的方式来避免假名机制所带来的存储负担。最后,利用随机预言机对协议安全性进行了证明。仿真结果表明所提方案具有更低的认证时延和通信成本。     

车联网中基于NOMA-MEC的卸载策略研究

随着车联网(IoV)的迅猛发展,请求进行任务卸载的汽车终端用户也逐渐增长,而基于移动边缘计算(MEC)的通信网络能够有效地解决任务卸载在上行传输时延较高的挑战,但是该网络模型同时也面临着信道资源不足的问题。该文引入的非正交多址(NOMA)技术相较于正交多址(OMA)能够在相同的信道资源条件下为更多的用户提供任务卸载,同时考虑到任务卸载过程中多方面的影响因子,提出了混合NOMA-MEC卸载策略。该文设计了一种基于深度学习网络(DQN)的博弈算法,帮助车辆用户进行信道选择,并通过神经网络多次迭代学习,为用户提供最优的功率分配策略。仿真结果表明,该文所提出的混合NOMA-MEC卸载策略能够有效地优化多用户卸载的时延以及能耗,最大限度保证用户效益。     

车联网中基于NOMA-MEC的卸载策略研究

随着车联网(IoV)的迅猛发展,请求进行任务卸载的汽车终端用户也逐渐增长,而基于移动边缘计算(MEC)的通信网络能够有效地解决任务卸载在上行传输时延较高的挑战,但是该网络模型同时也面临着信道资源不足的问题。该文引入的非正交多址(NOMA)技术相较于正交多址(OMA)能够在相同的信道资源条件下为更多的用户提供任务卸载,同...     

车联网中的协同通信平均传输时间计算

车联网(Internet of Vehicles,Io V)是智能交通和通信领域的热点课题,协同通信算法的研究是Io V通信的重要技术之一。针对Io V环境下因通信拓扑结构快速变化导致数据信号利用单一通信方式难以高效传输的问题,提出Io V环境下协同通信算法,利用车对车(Vehicle-to-Vehicle,V2V)和车对路(Vehicle-to-Infrastructure,V2I)协同通信方法,对目标数据从请求到完成的平均传输时间进行了理论分析和推导。仿真结果表明,该算法的传输效率比基于移动边缘计算(Mobile Edge Computing,MEC)车联网协作传输算法提升40%,比基于分簇V2X车载广播传输算法提升25%;该算法的平均传输时间随着路侧单元(Road Side Unit,RSU)缓存概率从0.5增加至1可提高9%,随着车辆缓存概率从0.5增加至1可提高46%。     

车联网安全防护问题分析

车联网作为物联网在智能交通方面的应用,已经成为了国内外广泛关注的焦点.通过介绍车联网概念和功能架构,引出车联网可能存在的安全风险,并结合车联网安全事件案例,同时在此基础上给出各国车联网安全防护政策,提出车联网安全防护体系.     

车联网中基于Q学习的地理位置路由协议

由于道路拓扑结构的限制以及车辆节点的快速变化,车联网路由协议正面临着很多挑战,例如道路的低连通性、较大的延时以及高开销等。为解决此类问题,提出了一种基于Q学习的地理位置路由协议。该协议将地理区域划分成大小一致的正方形,称为网格。在给定目的地的情况下,根据历史交通流信息计算出车辆从当前网格向不同方向的邻居网格移动的Q值,每辆车存储Q值表,通过查询Q值表选择最优下一跳网格。在选定的下一跳网格中,选择距离目的地最近的车辆,当最优下一跳网格中没有邻居车辆时,选择次优下一跳网格中的车辆。仿真结果表明,与其他基于地理位置的路由协议相比,所提协议能够提高分组投递率,降低传输延时并减少通信跳数。     

A novel approach of tensor‐based data missing estimation for Internet of Vehicles

In the face of the current huge amount of intelligent traffic data, collecting and statistical processing is a necessary and important process. But the inevitable data missing problem is the current research focus. In this paper, a novel approach of tensor‐based data missing estimation for Internet of Vehicles is proposed for the problem of missing the Internet of Vehicles data: Integrated Bayesian tensor decomposition (IBTD). In the data model construction stage, the random sampling principle is used to randomly extract the missing data to generate a subset of data. And the optimized Bayesian tensor decomposition algorithm is used for interpolation. Introduce the integration idea, analyze, and sort the error results after multiple interpolations, consider the space‐time complexity, and choose the optimal average to get the best result. The performance of the proposed model was evaluated by mean absolute percentage error (MAPE) and root mean square error (RMSE). The experimental results show that the proposed method can effectively interpolate the traffic data sets with different missing quantities and get good interpolation results.     

车联网中基于网络编码的优先级信息分发方案

车联网中信息的共享尤其是紧急信息的分发至关重要。然而,传统的广播方式易引起网络风暴,导致信息传输时延高,预警效果差。为了实现海量信息的共享以及紧急信息的快速分发,提出了一种基于优先级的信息网络编码算法（Priority-based Information Network Coding Algorithm,PINCA）,根据信息类别确定优先级别,优先对高优先级数据包进行线性网络编码与传输。仿真结果表明,相同仿真环境下,采用所提的PINCA时,紧急信息传输时延比现有传输方案下的时延减小了至少23.494 4 ms,同时算法的时间复杂度也低于现有方案,可应用于路边设备稀疏的车联网系统中。     

一种基于车边云协同的车联网计算卸载策略

随着智能交通的快速发展和车联网中数据流量爆炸式的增长,汽车终端请求卸载的任务对时延和带宽有了更加严苛的要求。在现有的云计算服务模式中,车辆可以访问云服务器来获得强大的计算、存储和网络资源,但缺点是通信传输时延较大,仅依靠云计算可能会导致过度的延迟。为了更加合理利用资源、减小时延、优化卸载策略,提出了一种基于粒子群优化算法的“车-边-云”协同卸载方案。首先通过接入点附近的软件定义网络（Software Define Network,SDN)控制器根据终端用户附近边缘节点、本地终端和云计算节点的计算资源和容量情况得出最优的卸载策略,充分利用本地、移动边缘计算（Mobile Edge Computing,MEC）设备、云端的计算资源,然后通过粒子群优化算法得出“车-边-云”各计算节点的卸载系数,即最优卸载策略。实验结果表明,相比于其他卸载策略,所提的卸载机制对时延优化效果明显,提高了计算资源的利用率。     

Internet of Things offloading: Ongoing issues,opportunities, and future challenges

Internet of Things (IoT) has very remarkable advantages over customary communication technologies. However, IoT suffers from different issues, such as limited battery life, low storage capacity, and little computing capacity. For this reason, in many IoT applications and devices, we require an alternative unit to execute the tasks from the user's device and return results. In general, the problem of limited resources by transferring the computation workload to other devices/systems with better resources is addressed by offloading computation. It can be focused on improving the application, extending battery life, or expanding storage capacity. The offloading operation can be performed based on various quality of service (QoS) parameters that contain computational demands for load balancing, response time, application, energy consumption, latency, and other things. Moreover, the systematic literature review (SLR) method is used to identify, assess, and integrate findings from all relevant studies that address one or more research questions on IoT offloading and conduct a comprehensive study of empirical research on offloading techniques. However, we present a new taxonomy for them based on offloading decision mechanisms and overall architectures. Furthermore, we offer a parametric comparison for the offloading methods. As well, we present the future direction and research opportunities in IoT offloading computation. This survey will assist academics and practitioners to directly understand the progress in IoT offloading.     

A comprehensive and systematic review of the network virtualization techniques in the IoT

Internet of Things (IoT) as one of the last technology in the network domain is an environment of associated physical objects that are reachable through the Internet. Virtualization as the primary technology of IoT has a significant role in its popularization. The visualization strategies have a great impact on the IoT, but, as far as we know, there is not a comprehensive and systematic study in this field. Also, there is no systematic and complete way to discuss and analyze the related strategies. Henceforth, a systematic survey of virtualization techniques is presented in this paper. Different parameters based on the examination of the prevailing methods are considered in three main categorizations. Furthermore, the benefits and weaknesses connected with selected techniques have been discussed, and the significant issues of these techniques are addressed to improve the more efficient virtualization technique for the future.     

Integration of Internet of Things and blockchain technology in healthcare domain: A systematic literature review

Healthcare is a vitally important field in the industry and evolving day by day in the aspect of technology, services, computing, and management. Its potential significance can be increased by incorporating Internet of Things (IoT) technology to make it smart in the aspect of automating activities, which is then further reformed in the healthcare domain with the help of blockchain technology. Blockchain technology provides many features to IoT-based healthcare domain applications such as restructuring by securing traditional practices, data management, data sharing, patient remote monitoring, and drug analysis. In this study, a systematic literature review has been carried out in which a total of 52 studies were selected to conduct systematic literature review from databases PubMed, IEEE Access, and Scopus; the study includes IoT technology and blockchain integration in healthcare domain-related application areas. This study also includes taxonomy that mentions the aspects and areas in healthcare domain incorporating the traditional system with the integration of IoT and blockchain to provide transparency, security, privacy, and immutability. This study also includes the incorporation of related sensors, platforms of blockchain, the objective focus of selected studies, and future directions by incorporating IoT and blockchain in healthcare domain. This study will help researchers who want to work with IoT and blockchain technology integration in healthcare domain.     

Determinants of Internet skills,uses and outcomes. A systematic review of the second- and third-level digital divide

Recently, several digital divide scholars suggested that a shift is needed from a focus on binary Internet access (first-level digital divide) and Internet skills and use (second-level digital divide) to a third-level digital divide in which the tangible outcomes of Internet use are highlighted. A plethora of studies have been conducted to identify determinants of digital divides. Unfortunately, there is a lack of consistency in the terminology used. Moreover, terms are often not theoretically grounded. Therefore, we conducted a systematic literature review of digital divide determinants. The results show that the third-level digital divide was underexposed. The primary focus is on Internet use. More importantly, the identified determinants show that digital divide research is largely limited to sociodemographic and socioeconomic determinants.     

A review on evolving domains of Internet of Things: Architecture,applications, and technical challenges

The Internet of Things (IoT) is a system that includes smart items with different sensors, advanced technologies, analytics, cloud servers, and other wireless devices that integrate and work together to create an intelligent environment that benefits end users. With its wide spectrum of applications, IoT is revolutionizing both the current and future generations of the Internet. IoT systems can be employed for broad-ranging real applications, such as agriculture, the environment, cities, healthcare, and the industrial sector. In this paper, we briefly discuss the three-tier architectural view of IoT, its different communication technologies, and the smart sensors. Moreover, we study various application areas of IoT such as the environmental domain, healthcare, agriculture, smart cities, and industrial, commercial, and general aspects. A critical analysis is shown for the existing schemes and techniques related to this work. Further, this paper addresses the basic context, tools and evaluation approaches, future scope, and the advantages and disadvantages of the aforestated IoT applications. A comprehensive analysis is provided for each domain along with its fundamental parameters like the quality of service (QoS), network longevity, scalability, energy efficiency, accuracy, and cost. Finally, this study highlights the technical challenges and open research problems existing in different IoT applications.     

嵌入式UICC远程管理在车联网领域的应用研究

汽车行业"一点制造,全球销售,统一管理"的共性需求,引导和推动着嵌入式UICC远程管理技术在车联网领域落地应用.嵌入式UICC卡的封装特性、硬件特性和远程管理能力降低了通信连接服务的复杂性,提高了运营商选择的灵活性.首先对嵌入式UICC远程管理的发展背景、政策标准和发展现状进行了概述,围绕平台、卡和安全架构,描述了嵌入...     

A Novel Secure Data Transmission Scheme in Industrial Internet of Things

The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.     

Health care service delivery based on the Internet of things: A systematic and comprehensive study

Today, the Internet of Things (IoT) becomes a heterogeneous and highly distributed structure which can respond to the daily needs of people and different organizations. With the fast development of IT‐based technologies such as IoT and cloud computing, low‐cost health services and their support, efficient supervision of the centralized management, and monitoring of public health can be realized. Therefore, there has been increasing attention in the integration of IoT and health care both in academic and the business world. However, while the health care service industry fully holds the welfares of information systems for its personnel and patients, there is a need for an improved understanding of the issues and opportunities related to IoT‐based health care systems. But, as far as we know, the detailed review and deep discussion in this field are very rare. Hence, in this paper, we presented a literature review on the IoT‐based health care services from papers published until 2018. Moreover, the drawbacks and benefits of the reviewed mechanisms have been discussed, and the main challenges of these mechanisms are highlighted for developing more efficient IoT techniques over health care services in the future. The results of this paper will be valuable for both practitioners and academicians, and it can provide visions into future research areas in this domain. By providing comparative information and analyzing the current developments in this area, this paper will directly support academics and working professionals for better knowing the progress in IoT mechanisms. As a general result, we found that IoT could help the governments to improve health services in society and commercial interactions.