面向服务的云-端动态协作方法

边缘计算可以通过将计算转移至边缘设备,以提高大型物联网流数据的处理质量并降低网络运行成本。然而,实现大型流数据云计算和边缘计算的集成面临两个挑战。首先,边缘设备的计算能力和存储能力有限,不能支持大规模流数据的实时处理。其次,流数据的不可预测性导致边缘端的协作不断地发生变化。因此,有必要实现边缘服务和云服务之间的灵活划分。提出一种面向服务的云端与边缘端的无缝集成方法,用于实现大规模流数据云计算和边缘计算的协作。该方法将云服务分成两部分,分别在云端和边缘端上运行。同时,提出了一种基于改进的二分图动态服务调度机制。当产生事件时,可以在适当的时间将云服务部署到边缘节点。基于真实的电能质量监控数据对提出的方法进行了有效性验证。     

边缘计算环境下安全协议综述

物联网的迅速普及使得数据规模以几何式上升.集中在云中心处理数据的方式逐渐出现通信时延及隐私泄露等问题.边缘计算将部分云中心业务下沉到设备边缘,使得数据处理在终端网络完成,从而实现数据快速处理.同时,由于避免了远距离通信,用户数据在本地处理,使得用户隐私数据得以安全保护.然而网络架构的改变对边缘计算环境下的安全协议又提出...     

区块链赋能的高效物联网数据激励共享方案

近年来,随着大量设备不断地加入物联网中,数据共享作为物联网市场的主要驱动因素成为了研究热点.然而,当前的物联网数据共享存在着出于安全顾虑和缺乏激励机制等原因导致用户不愿意参与共享数据的问题.在此背景下,区块链技术为解决用户的信任问题和提供安全的数据存储被引入到物联网数据共享中.然而在构建基于区块链的安全分布式数据共享系统的探索中,如何突破区块链固有的性能瓶颈仍然是一个关键挑战.为此,本文研究了基于区块链的高效物联网数据激励共享方案.该方案首先提出了一个高效的区块链物联网数据激励共享框架,称为ShareBC.ShareBC利用分片技术构建能够并行处理数据共享交易的异步共识区,并在云/边缘服务器上和分片异步共识区上部署高效的共识机制,从而提高数据共享交易的处理效率.然后,为激励物联网用户参与数据共享,提出了一种基于智能合约实现的层次数据拍卖模型的共享激励机制.该机制解决了物联网数据共享中涉及的多层数据分配有效性问题,能够最大限度地提高整体社会福利.最后,实验结果证明了该方案的经济效益、激励兼容性和实时性以及可扩展性,且具有较低的计算成本和良好的实用性.     

边缘计算的物联网深度学习及任务卸载调度策略

为解决物联网深度学习模型的网络性能和隐私问题,提出一种边缘计算的物联网深度学习应用及任务卸载策略,以优化网络性能,保护数据上传中的用户隐私。深度学习的多层结构适用于边缘计算,边缘节点上传缩减的中间数据,因此减少了从物联网设备到云服务器的网络流量。考虑到边缘节点有限的服务能力,提出一种边缘计算环境中最大化任务数量的卸载调度策略,优化边缘计算的物联网深度应用性能。实验结果表明,该策略能够在边缘计算环境中执行多个深度学习任务,并且性能优于其他物联网深度学习优化解决方案。     

非规则流中高维数据流典型相关性分析并行计算方法?

为了满足在计算资源受限的环境下高维数据流处理的实时性要求,提出一种方法——基于 GPU(graphic processing unit)的非规则流中高维数据流的处理模型和具体的可行架构,并分析设计了相关的并行算法。该六层模型是将 GPU 处理数据的高宽带性能结合进滑动窗口中数据流的分析,进而在该框架下基于统一计算设备架构(compute unified device architecture,简称CUDA),使用数据立方模型以及降维约简技术并行分析了多条高维数据流的典型相关性。理论分析和实验结果均表明,该并行处理方法能够在线精确地识别同步滑动窗口模式下高维数据流之间的相关性。相对于纯 CPU 方法,该方法具有显著的速度优势,很好地满足了高维数据流的实时性需求,可以作为通用的分析方法广泛应用于数据流挖掘领域。     

面向车联网的时空事件处理语言STEP

车联网是物联网技术应用于智能交通领域所形成的重要研究领域。复杂事件处理技术是车联网系统数据流处理的重要方法。有别于经典的物联网系统,车联网中数据流包含大量的时间和空间信息。在复杂事件处理技术中,如何有效地表达和处理车联网的时空数据流成为亟待解决的问题。针对该问题,提出了一种时空事件处理语言(spatial-temporal event processing language,STEP)。STEP分别采用时间段和栅格地图作为时间和空间模型。基于该时空模型,首先给出STEP语言的相关时空算子和完整语法,从而有效地表达车联网中时空事件流的时空信息。然后,分别从形式语义学角度引入STEP语言的操作语义,并且从实现角度给出了基于Petri网模型的时空事件流处理算法,从而建立车联网时空事件流处理机制。最后,通过实验说明了基于STEP语言的车联网时空事件流处理机制的有效性。     

非规则流中高维数据流典型相关性分析并行计算方法

为了满足在计算资源受限的环境下高维数据流处理的实时性要求,提出一种方法——基于GPU(graphic processing unit)的非规则流中高维数据流的处理模型和具体的可行架构,并分析设计了相关的并行算法.该六层模型是将GPU处理数据的高宽带性能结合进滑动窗口中数据流的分析,进而在该框架下基于统一计算设备架构(compute unified device architecture,简称CUDA),使用数据立方模型以及降维约简技术并行分析了多条高维数据流的典型相关性.理论分析和实验结果均表明,该并行处理方法能够在线精确地识别同步滑动窗口模式下高维数据流之间的相关性.相对于纯CPU方法,该方法具有显著的速度优势,很好地满足了高维数据流的实时性需求,可以作为通用的分析方法广泛应用于数据流挖掘领域.     

面向XPath执行的XML数据流压缩方法

由于XML(extensible markup language)本身是自描述的,所以XML数据流中存在大量冗余的结构信息.如何压缩XML数据流,使得在减少网络传输代价的同时有效支持压缩数据流上的查询处理,成为一个新的研究领域.目前已有的XML数据压缩技术,都需要扫描数据多遍,或者不支持数据流之上的实时查询处理.提出了一种XML数据流的压缩技术XSC(XML stream compression),实时完成XML数据流的压缩和解压缩,XSC动态构建XML元素事件序列字典并输出相关索引,能够根据XML数据流所遵从的DTD,产生XML元素事件序列图,在压缩扫描之前,产生更加合理的结构序列编码.压缩的XML数据流能够直接解压缩用于XPath的执行.实验表明,在XML数据流环境中,XSC在数据压缩率和压缩时间上要优于传统算法.同时,在压缩数据之上查询的执行代价是可以接受的.     

基于物联网技术的医院智慧化建设与研究

当存在大量物联网通信设备时,通信效率不高,设备终端数据计算能力滞后,本研究针对该问题,融合了RFID射频识别装置、红外传感器、GPS定位系统、激光扫描器等多种物联设备,能够实现数据的直接采集和传递.本研究还设置了基于IPv6协议的6LoWPAN通信方式,构建了边缘计算硬件结构,并设计出新型的边缘计算模型,提高了数据通信和计算能力.试验结果表明,本文研究方法通信能力强,计算速度快,准确率高.     

面向AI数据流处理的边缘GPU集群通信系统

在边缘计算场景中,GPU集群需要应对终端设备所产生的数量庞大的AI计算任务.AI计算任务在边缘GPU集群内的响应耗时不仅包括计算时间,还包括数据传输和排队等待延时.因此,任务数据传输和AI数据流调度也是影响GPU集群数据处理性能的关键因素.传统网络协议栈的低效率和专用高速网络设备的高成本,并不适用于边缘场景中大规模AI数据流的实时处理.本文基于DPDK技术提出多核多网卡的并行通信机制,利用集群空闲的CPU资源加快数据传输;兼顾节点计算能力和网络负载分析节点实时处理能力制定数据流分配策略,并实现了由数据接入量驱动的动态多核多缓冲区模型,减少了任务计算的等待时间.实验结果表明,提出的通信调度方案不仅能够增加约30%的集群数据流容量,而且带宽利用率能够达到90%;在总AI任务量相同的情况下,归功于DPDK高效的数据包处理能力,避免了大量的AI任务因传输失败而被丢弃的情况.     

Privacy-preserving edge-assisted image retrieval and classification in IoT

Internet of Things (IoT) has drawn much attention in recent years. However, the image data captured by IoT terminal devices are closely related to users’ personal information, which are sensitive and should be protected. Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support privacy-preserving computing, they consume a significant amount of computation and storage resources. Thus, it becomes a heavy burden on IoT terminal devices with limited resources. In order to reduce the resource consumption of terminal device, we propose an edge-assisted privacy-preserving outsourced computing framework for image processing, including image retrieval and classification. The edge nodes cooperate with the terminal device to protect data and support privacy-preserving computing on the semitrusted cloud server. Under this framework, edge-assisted privacy-preserving image retrieval and classification schemes are proposed in this paper. The security analysis and performance evaluation show that the proposed schemes greatly reduce the computational, communication and storage burden of IoT terminal device while ensuring image data security.     

基于DICE的证明存储方案

信息技术的不断发展和智能终端设备的普及导致全球数据存储总量持续增长,数据面临的威胁挑战也随着其重要性的凸显而日益增加,但目前部分计算设备和存储设备仍存在缺乏数据保护模块或数据保护能力较弱的问题.现有数据安全存储技术一般通过加密的方式实现对数据的保护,但是数据的加解密操作即数据保护过程通常都在应用设备上执行,导致应用设备遭受各类攻击时会对存储数据的安全造成威胁.针对以上问题,本文提出了一种基于DICE的物联网设备证明存储方案,利用基于轻量级信任根DICE构建的可信物联网设备为通用计算设备(统称为主机)提供安全存储服务,将数据的加解密操作移至可信物联网设备上执行,消除因主机遭受内存攻击等风险对存储数据造成的威胁.本文工作主要包括以下3方面:(1)利用信任根DICE构建可信物联网设备,为提供可信服务提供安全前提.(2)建立基于信任根DICE的远程证明机制和访问控制机制实现安全认证和安全通信信道的建立.(3)最终利用可信物联网设备为合法主机用户提供可信的安全存储服务,在实现数据安全存储的同时,兼顾隔离性和使用过程的灵活性.实验结果表明,本方案提供的安全存储服务具有较高的文件传输速率,并具备较高...     

基于区块链的边缘计算IIoT架构研究

在智能制造系统中,工业物联网通过先进的管理技术将制造设备互连,实现了信息的实时传输、设备的范在化感知和数据的快速分析处理。但是由于制造设备的异构性、物联网网关（IoT网关）数据分析能力的有限性、制造设备的存储力低下,设备和数据的低安全性等缺陷严重阻碍了智能制造的发展。BEIIoT架构从制造企业的实际生产过程与应用角度出发,将区块链技术与边缘计算相结合,通过对服务器进行P2P组网以实现对设备去中心化管理;通过对边缘设备进行服务化封装,增强设备的安全性与实时分析能力,降低设备的异构性;使用DAG双链式数据存储结构,提高数据的冗余度与安全性,实现生产线数据的异步并发备份存储。BEIIoT架构为智能制造的实施提供了体系支持。     

DECENT: Secure and fine-grained data access control with policy updating for constrained IoT devices

The Internet of Things (IoT) is a novel paradigm where many of the objects that surround us can be connected to the internet. Since IoT is always related to user’s personal information, it raises lot of data security and privacy issues. In this paper, we present a secure and fine-grained data access control scheme for constrained IoT devices and cloud computing based on hierarchical attribute-based encryption, which reduces the key management by introducing hierarchical attribute authorities. In order to relieve local computation burden, we propose an outsourced encryption and decryption construction by delegating most of laborious operations to gateway and cloud server. Further, our scheme achieves efficient policy updating, which allows the sender device to update access policies without retrieving and re-encrypting the data. The security and performance analysis results show that our scheme is secure and efficient.     

A secure and scalable storage system for aggregate data in IoT

In recent years, with the impressive rapid development of integrated circuit and networking technologies, computers, devices and networking have become highly pervasive, incurring the introduction, development and deployment of the Internet of Things (IoT). The tiny identifying devices and wearables in IoT have transformed daily life in human society, as they generate, process and store the amount of data increasing at exponential rate all over the world. Due to high demand on data mining and analytics activities in IoT, secure and scalable mass storage systems are highly demanded for aggregate data in efficient processing. In this paper, we propose such a secure and scalable IoT storage system based on revised secret sharing scheme with support of scalability, flexibility and reliability at both data and system levels. Shamir’s secret sharing scheme is applied to achieve data security without complex key management associated with traditional cryptographic algorithms. The original secret sharing scheme is revised to utilize all coefficients in polynomials for larger data capacity at data level. Flexible data insert and delete operations are supported. Moreover, a distributed IoT storage infrastructure is deployed to provide scalability and reliability at system level. Multiple IoT storage servers are aggregated for large storage capacity whereas individual servers can join and leave freely for flexibility at system level. Experimental results have demonstrated the feasibility and benefits of the proposed system as well as tangible performance gains.     

基于区块链的农业物联网可信溯源体系

随着农业信息化的快速发展,农业物联网逐渐成为智慧农业必要的基础设施.未来智慧农业依赖大量的物联网传感器,为了解决农业物联网中数据孤立、不可靠、容易被篡改、难以追踪追责的问题,本文提出了一种基于区块链的农业物联网可信溯源体系.考虑农业物联网数据量大、种类繁多的特点,本方案基于Hyperledger fabric智能合约,...     

Efficient Blockchain-Empowered Data Sharing Incentive Scheme for Internet of Things

In recent years, with many devices continuously joining the Internet of Things (IoT), data sharing as the main driver of the IoT market has become a research hotspot. However, the users are reluctant to participate in data sharing due to security concerns and lacking incentive mechanisms in the current IoT. In this context, blockchain is introduced into the data sharing of IoT to solve the trust problem of users and provide secure data storage. However, in the exploration of building a secure distributed data sharing system based on the blockchain, how to break the inherent performance bottleneck of blockchain is still a major challenge. For this reason, the efficient blockchain-based data sharing incentive scheme is studied for IoT. In the scheme, an efficient data sharing incentive framework based on blockchain is proposed, named ShareBC. Firstly, ShareBC uses sharding technology to build asynchronous consensus zones that can process data sharing transactions in parallel and deploy efficient consensus mechanisms on the cloud/edge servers and asynchronous consensus zones in sharding, thus improving the processing efficiency of data sharing transactions. Then, a sharing incentive mechanism based on a hierarchical data auction model implemented by a smart contract is presentedto encourage IoT users to participate in data sharing. The proposed mechanism can solve the problem of multi-layer data allocation involved in IoT data sharing and maximize the overall social welfare. Finally, the experimental results show that the proposed scheme is economically efficient, incentive-compatible, and real-time, with scalability, low cost, and good practicability.     

A secure authentication scheme based on elliptic curve cryptography for IoT and cloud servers

The Internet of Things (IoT) is now a buzzword for Internet connectivity which extends to embedded devices, sensors and other objects connected to the Internet. Rapid development of this technology has led to the usage of various embedded devices in our daily life. However, for resource sharing and communication among these devices, there is a requirement for connecting these embedded devices to a large pool of resources like a cloud. The promising applications of IoT in Government and commercial sectors are possible by integrating cloud servers with these embedded devices. But such an integration of technologies involves security issues like data privacy and authentication of devices whenever information is exchanged between them. Recently, Kalra and Sood proposed an authentication scheme based on elliptic curve cryptography (ECC) for IoT and cloud servers and claimed that their scheme satisfies all security requirements and is immune to various types of attacks. However, in this paper, we show that Kalra and Sood scheme is susceptible to offline password guessing and insider attacks and it does not achieve device anonymity, session key agreement, and mutual authentication. Keeping in view of the shortcomings of Kalra and Sood’s scheme, we have proposed an authentication scheme based on ECC for IoT and cloud servers. In the proposed scheme in this paper, we have formally analyzed the security properties of the designed scheme by the most widely accepted and used Automated Validation of Internet Security Protocols and Applications tool. Security and performance analysis show that when compared with other related schemes, the proposed scheme is more powerful, efficient, and secure with respect to various known attacks.     

物联网体系架构的研究

物联网应用于生活的方方面面。物联网(IOT)的大量终端设备不断接入网络,产生大量的数据,物联网的各种终端设备之间的如何连接,如何进行数据通信,如何保证通信安全都是一个很复杂的问题。物联网体系结构的研究是将物联网的功能划分为不同的层次,每一层完成相应的任务,从而保证物联网的功能的正确完成。随着边缘计算的发展,传统物联网体系结构的内容发生了一些变化。物联网中引入边缘计算,可以更好地解决网络安全、负载和延迟等问题。随着未来5G技术的发展,物联网体系结构将在继续发生变化。     

An anonymous authentication and secure data transmission scheme for the Internet of Things based on blockchain

With the widespread use of network infrastructures such as 5G and low-power wide-area networks, a large number of the Internet of Things (IoT) device nodes are connected to the network, generating massive amounts of data. Therefore, it is a great challenge to achieve anonymous authentication of IoT nodes and secure data transmission. At present, blockchain technology is widely used in authentication and s data storage due to its decentralization and immutability. Recently, Fan et al. proposed a secure and efficient blockchain-based IoT authentication and data sharing scheme. We studied it as one of the state-of-the-art protocols and found that this scheme does not consider the resistance to ephemeral secret compromise attacks and the anonymity of IoT nodes. To overcome these security flaws, this paper proposes an enhanced authentication and data transmission scheme, which is verified by formal security proofs and informal security analysis. Furthermore, Scyther is applied to prove the security of the proposed scheme. Moreover, it is demonstrated that the proposed scheme achieves better performance in terms of communication and computational cost compared to other related schemes.