基于MCU的无源Wi-Fi散射通信方法

与有源Wi-Fi相比,Wi-Fi散射通信具有功耗低、成本低的优势.但目前大多数研究都存在现场可编程门阵列（FPGA）功耗大和专用集成电路（IC）制作成本高的问题.为此该文提出一种基于微控制器（MCU）的无源Wi-Fi散射通信方法,用低主频MCU生成了纳秒级时序精度的Wi-Fi散射调制波形,并进行了低功耗设计和优化,开展了基于能量收集的MCU电源管理和无源系统设计,并首次展示了基于室内弱光能量收集的无源Wi-Fi原型样机.测试表明,通信瞬时功耗1.8mW,比有源器件降低了2~3个数量级.系统待机功耗2.5μW,有效通信距离15m,兼容现有的商用Wi-Fi设备,且成本低,无需电池.     

未来网络应用场景与网络能力需求

以TCP/IP为体系架构的互联网已经发展为当前信息社会的重要基础设施。但随着网络流量的迅速增长和各种新兴应用的不断出现,现有网络体系结构在各方面的问题日益突出。分析了未来网络的新型应用,并明确了未来网络应用的性能需求会给网络体系结构的研究和设计提供更清晰的方向。对浸入式体验、物联网、触觉互联网和智能交通这几类典型未来网络应用的应用场景进行了分析,总结出未来网络应用对未来网络的能力需求,导出关键的网络性能指标需求。     

Exploring Factors Affecting the Adoption of Internet of Things Services

The Internet of things (IoT) is seen as a potentially effective means of integrating multiple technologies to improve the quality of life. However, little attention has been paid to factors that may have a significant effect on a user’s intention to use the IoT services. This study applies the value-based adoption model to examine the influences of benefits (i.e. perceived usefulness and perceived enjoyment) and sacrifices (i.e. perceived privacy risk and perceived costs) on the user’s perceived value of and intention to use the IoT services. A structural equation modeling approach is applied to a survey of 489 IoT users, with results indicating that perceived usefulness and perceived enjoyment significantly affect behavioral intention through perceived value. Moreover, perceived privacy risk also plays a key factor in determining IoT adoption. The implications of this study are discussed.     

Internet of Things-based student performance evaluation framework

In recent years, solutions based on Internet of Things (IoT) are gaining impetus in educational institutions. It is observed that student performance evaluation system in education institutions is still manual. The performance score of student in traditional evaluation system is confined to its academic achievements while activity-based performance attributes are overlooked. Moreover, the traditional system fails to capitalise information of each student related to different activities in learning environment. In relation to this context, we propose to facilitate automated student performance evaluation system by exploring ubiquitous sensing capabilities of IoT. The system deduces important results about the performance of the students by discovering daily spatial–temporal patterns. These patterns are based on the data collected by the sensory nodes (objects) in the institution learning environment. The information is generated by applying data mining algorithms for each concerned activity. The automated decisions are taken by management authority for each student using game theory. In addition, to effectively manage IoT-based activity data, tensor-based storage mechanism is proposed. The experimental evaluation compares the student performance score generated by the proposed system with the manual student performance evaluation system. The results depict that the proposed system evaluates the performance of the student efficiently.     

A BIM-based visualization and warning system for fire rescue

Structural fires are common disasters. In Taiwan, about 100 firefighters die during fire rescues each year, primarily because they are unaware of the causes of the fire and unfamiliar with the location’s environment. Meanwhile, evacuees often die in the panic of evacuation. To solve these problems, this research proposes a Building Information Modeling (BIM)-based visualization and warning system for fire rescue. A fire dynamics simulator (FDS) simulates various conditions of structural fires in conjunction with the visualization and integration properties of BIM, and the simulation results for temperature, carbon monoxide, and visibility can be integrated and presented in the BIM model for briefing purposes before rescue operations begin. In addition, this research integrates Internet of Things (IoT) technology, which allows real-time situation monitoring. In the event of a fire, the BIM model will immediately display the situation of the fire scene and control LED escape route pointers according to the actual situation. The primary objective of this system is to provide useful information to firefighters such that they can be aware of the fire’s environment and create an effective rescue plan. Moreover, the automated LED escape route pointer may assist the building’s occupants to escape, provide the firefighters with valuable information, and allow them quickly to discover hazards so that the number of casualties can be minimized.     

The MIDAS touch: Thermal dissipation resulting from everyday interactions as a sensing modality

We contribute MIDAS as a novel sensing solution for characterizing everyday objects using thermal dissipation. MIDAS takes advantage of the fact that anytime a person touches an object it results in heat transfer. By capturing and modeling the dissipation of the transferred heat, e.g., through the decrease in the captured thermal radiation, MIDAS can characterize the object and determine its material. We validate MIDAS through extensive empirical benchmarks and demonstrate that MIDAS offers an innovative sensing modality that can recognize a wide range of materials – with up to 83% accuracy – and generalize to variations in the people interacting with objects. We also demonstrate that MIDAS can detect thermal dissipation through objects, up to 2 mm thickness, and support analysis of multiple objects that are interacted with.     

Random forest classifier‐based safe and reliable routing for opportunistic IoT networks

Designing a safe and reliable way for communicating the messages among the devices and humans forming the Opportunistic Internet of Things network (OppIoT) has been a challenge since the broadcast mode of message sharing is used. To contribute toward addressing such challenge, this paper proposes a Random Forest Classifier (RFC)‐based safe and reliable routing protocol for OppIoT (called RFCSec) which ensures space efficiency, hash‐based message integrity, and high packet delivery, simultaneously protecting the network against safety threats viz. packet collusion, hypernova, supernova, and wormhole attacks. The proposed RFCSec scheme is composed of two phases. In the first one, the RFC is trained on real data trace, and based on the output of this training, the second phase consists in classifying the encountered nodes of a given node as belonging to one of the output classes of nodes based on their past behavior in the network. This helps in proactively isolating the malicious nodes from participating in the routing process and encourages the participation of the ones with good message forwarding behavior, low packet dropping rate, high buffer availability, and a higher probability of delivering the messages in the past. Simulation results using the ONE simulator show that the proposed RFCSec secure routing scheme is superior to the MLProph, RLProph, and CAML routing protocols, chosen as benchmarks, in terms of legitimate packet delivery, probability of message delivery, count of dropped messages, and latency in packet delivery. The out‐of‐bag error obtained is also minimal     

电信边缘云概述

随着5G和物联网的发展,集中式的云计算模型不能适应新的应用场景,出现了边缘云技术。本文从运营商的角度介绍了电信边缘云的概念、框架、关键技术和服务能力,简介了中国电信一些实践。最后对电信边缘云的发展提出了一些建议。     

面向物联网的近地轨道超大规模卫星星座数据命名机制

基于信息中心网络（ICN）的近地轨道（LEO）超大规模卫星星座是一种支持物联网（IoT）非常理想的网络架构,而数据命名是ICN基本问题之一。针对IoT低时延传输、高吞吐量的数据分发的需要,提出了一种基于ICN的面向IoT的LEO超大规模卫星星座数据命名机制。首先,该数据命名机制采用一种融合分层、多分量、哈希的扁平一体结构。然后,采用前缀标记描述分层名称,满足网内功能中多源快速检索的需要。最后,为检验所提数据命名机制的性能,设计开发了一个基于网络仿真器3（NS-3）的面向IoT的LEO超大规模卫星星座仿真平台。测试仿真结果表明,与传统的基于互联网协议（IP）的体系结构相比,所提出的数据命名机制能够为面向IoT的LEO超大规模卫星星座提供高吞吐量和低延时等更高的服务质量（QoS）。     

基于物联网平台的动态权重损失函数入侵检测系统

随着物联网（IoT）接入设备越来越多,以及网络管理维护人员缺乏对IoT设备的安全意识,针对IoT环境和设备的攻击逐渐泛滥。为了加强IoT环境下的网络安全性,利用基于IoT平台制作的入侵检测数据集,采用卷积神经网络（CNN）+长短期记忆（LSTM）网络为模型架构,利用CNN提取数据的空间特征,LSTM提取数据的时序特征,并将交叉熵损失函数改进为动态权重交叉熵损失函数,制作出一个针对IoT环境的入侵检测系统（IDS）。经实验设计分析,并使用准确率、精确率、召回率和F1-measure作为评估参数。实验结果表明在CNN-LSTM网络架构下采用了动态权重损失函数的模型与采用传统的交叉熵损失函数的模型相比,前者比后者在使用数据集的地址解析协议（ARP）类样本中在F1-Measure上提升了47个百分点,前者比后者针对数据集中的其他少数类样本则提升了2个百分点~10个百分点。实验结果表明,动态权重损失函数能够增强模型对少数类样本的判别能力,且该方法可以提升IDS对少数类攻击样本的判断能力。