China's cyclists take charge: electric bicycles are selling by the millions despite efforts to ban them

Electric bikes continue to grow in popularity in China despite being banned in some key cities. These bikes provide an attractive option for commuters, service people and couriers who have a need for motorized personal transportation. A major obstacle for the widespread use of electric bikes, however, is the lack of enough bike lanes. While road widening projects are being implemented, these are primarily aimed to accommodate the increasing number of automobiles in the city streets. Nevertheless, experts are optimistic that the electric bikes will ultimately prevail because of the adverse environmental and health effects of automobiles and the rising cost of petroleum products.     

Runtime reconfiguration of data services for dealing with out-of-range stream fluctuation in cloud-edge environments

The integration of cloud and IoT edge devices is of significance in reducing the latency of IoT stream data processing by moving services closer to the edge-end. In this connection, a key issue is to determine when and where services should be deployed. Common service deployment strategies used to be static based on the rules defined at the design time. However, dynamically changing IoT environments bring about unexpected situations such as out-of-range stream fluctuation, where the static service deployment solutions are not efficient. In this paper, we propose a dynamic service deployment mechanism based on the prediction of upcoming stream data. To effectively predict upcoming workloads, we combine the online machine learning methods with an online optimization algorithm for service deployment. A simulation-based evaluation demonstrates that, compared with those state-of-the art approaches, the approach proposed in this paper has a lower latency of stream processing.     

星地协同智能海洋通信网络发展展望

随着国家海洋战略推进实施,海上运输、资源开发等经济活动日趋活跃,海洋通信需求不断增长。尽管地面蜂窝网络已进入5G时代,现有海洋通信仍主要依赖海事卫星和岸基通信手段,通信速率、通信时延和可靠性等远不能满足需求。未来6G网络有望实现天空地海全域覆盖,但由于海上环境的复杂性、海事业务的异构性等挑战,6G海洋通信网络仍面临特殊难题。在综述海洋通信现状的基础上,从传输效率、网络覆盖、信息服务3方面梳理关键技术。面向未来6G智能海洋通信网络发展,展望海上环境感知智能传输、星地协同动态组网和业务驱动资源分配技术方法与研究方向。     

重庆市城乡信息服务市场统筹培育的推进机制

为推动重庆市城乡信息服务市场的进一步发展,基于重庆市城乡信息服务市场现状,分别从需求市场、供给市场以及政策市场3个方面对重庆市推动城乡信息服务市场统筹培育的推进机制进行了分析,为重庆市政府科学地制定统筹城乡信息服务市场的政策提供了依据,为兄弟城市推进城乡信息统筹一体化提供了借鉴。     

A Self-Optimizing QoS-Based Access for IoT Environments

Nowadays, providing Internet of Things (IoT) environments with service level guarantee is a challenging task. Moreover, IoT services should be autonomous in order to minimize human intervention and thus to reduce the operational management cost of the corresponding big scale infrastructure. We describe in this paper a service level-based IoT architecture enabling the establishment of an IoT Service Level Agreement (iSLA) between an IoT Service Provider (IoT-SP) and an IoT Client (IoT-C). The proposed iSLA specifies the requirements of an IoT service, used in a specific application domain (e-health, smart cities, etc.), in terms of different measurable Quality of Service (QoS) parameters. In order to achieve this agreement, several QoS mechanisms are to be implemented within each layer of the IoT architecture. In this context, we propose an adaptation of the IEEE 802.15.4 slotted CSMA/CA mechanism to provide different IoT services with QoS guarantee. Our proposal called QBAIoT (QoS-based Access for IoT) creates different Contention Access Periods (CAP) according to different traffic types of the IoT environment. These CAPs are QoS-based and enable traffic differentiation. Thus, a QoS CAP is configured with several slots during which only IoT objects belonging to the same QoS class can send their data. Furthermore, we specify a self-management closed control loop in order to provide our IoT architecture with a self-optimizing capability concerning QoS CAPs slots allocation. This capability takes into account the actual usage of QoS CAPs as well as the characteristics of the corresponding traffic class.

     

Intelligent Contextual Information Collection in Internet of Things

As we are moving towards the internet of things (IoT), a significant growth of stationary and mobile sensing and computing IoT devices continuously generate enormous amounts of contextual information, e.g., environmental data. Contextual information collection, reasoning, and inference plays critical role in IoT. In this paper, we consider the contextual information collection and harvesting problem in which stationary sensing and computing devices (sources), which are incapable to communicate with each other either due to their long distance, or for energy efficiency, or spatially dispersed network, rely on mobile IoT devices (collectors) to ‘drain’ their acquired contextual information. (e.g., generating from IoT applications: smart cities, smart metering, and smart agriculture). At the contact instances with the collectors, sources have to decide whether to deliver the contextual information obtained so far or postpone their delivery for later hitting epochs in an effort to sense fresher (or more critical) contextual information. We rest on the principles of Optimal Stopping Theory and propose an intelligent context collection scheme in IoT environments. We show through simulations with synthetic and real mobility data the effectiveness of our scheme compared to other approaches.     

通信·导航·物联一体化5G室内通信网络

4G 时代运营商已经沦为数据业务管道,5G 时代运营商将积极寻求业务转型。根据研究机构预测,室内定位及物联网市场前景广阔,运营商正在努力拓展相关领域的垂直行业应用。但是,现有室内通信网络功能单一,无法有效支撑室内定位和物联网业务。提出了一种通信·导航·物联一体化5G室内通信网络,通过在室分天线内部集成蓝牙模块,使其具备下行蓝牙定位、广告信息推送、链路损耗检测、上行物联收集和上行蓝牙定位等功能。该技术方案可应用于智慧医疗场景中,提供智慧导诊、设备管理、安防管理、后备保障和一键告警等服务。     

共享单车-网络架构及质量监测体系的研究

如今,很多上班族和学生将共享单车作为出行的首选工具。每一辆单车都配有一个智能锁,通过运营商的无线网络,连接到单车企业的系统平台。数以千万计的共享单车为市民出行带来了便利,也给通信网络的性能监控和运营带来了新的挑战。文章旨在通过对共享单车应用的系统架构、业务机制进行研究,对行业终端(智能锁)的通信行为进行分析,掌握共享单车的解锁、闭锁流程,提炼出业务流程中的网络行为模型,并建立针对应用的网络性能指标体系,最终利用自动化的大数据分析平台,开发出一套行之有效的业务监测系统。     

基于网络演进的人工智能技术方向研究

国家战略把人工智能（AI）及物联网（IoT）/5G同时定位为信息基础设施的重要组成部分,其中人工智能属于新技术基础设施,IoT/5G属于通信网络基础设施。这引出了“通信技术与人工智能技术融合发展”的技术方向。对于电信运营商而言,如何将人工智能技术与网络融合,重构网络技术架构,将“AI能力”作为“服务”开放,将是重要的技术演进方向。基于这一命题,探讨了未来AI和网络技术的发展方向,为未来AI技术与IoT/5G网络架构的融合发展方向提供了参考思路。     

5G基站智能节能方案研究

提出一种5G基站智能节能方案,用于降低5G基站设备能耗、节省5G网络运营成本、实现移动通信行业节能减排.所提方案是基于人工智能技术,从网络层面统一配置4G/5G基站节能策略,根据网络选定区域内小区的历史业务数据,构建基站业务负荷预测模型,并生成最优的网络节能策略,根据网络节能策略分别执行各基站的节能任务.在节能任务执行...     

基于复杂环境的城市5G移动网络优化设计

随着科学技术的快速发展,信息化技术被全面普及到日常生活中,人们对移动通信提出了更高的要求,这促使了移动通信由传统网络向5G网络发展,以全面增强移动网络的通信能力,给人们带来便捷的上网体验。但在应用无线网络的过程中,其存在各种问题,如受到5G超高频段组网限制,降低了其穿透能力和绕射能力,加上小基站大规模布局难度较高,楼宇建筑结构过于复杂,导致室内常出现深度覆盖不足甚至无覆盖的问题。基于此,文中以复杂城市环境为主要研究对象,概述了5G移动网络技术,分析了5G移动网络的应用现状,规范了城市复杂环境下5G移动网络的优化设计思路,并提出了合理的优化措施,构建了健全的网络评估模型,以充分发挥5G移动网络的作用。     

基于模糊C均值聚类和随机森林的短时交通状态预测方法

交通拥堵长期以来是城市面临的主要问题之一,解决交通拥堵瓶颈刻不容缓。准确的短时交通状态预测有利于市民预知交通出行信息,及时采取措施避免陷入拥堵困境。该文提出一种基于模糊C均值聚类(FCM)和随机森林的短时交通状态预测方法。首先,利用一种新颖的融合时空信息的自适应多核支持向量机(AMSVM)来预测短时交通流参数,包括流量、速度和占有率。其次,基于FCM算法分析历史交通流,获取历史交通状态信息。最后,利用随机森林算法分析所预测的短时交通流参数,得到最终预测的短时交通状态。该方法在融合时空信息的同时采用随机森林算法应用于短时交通状态预测这一全新的研究领域。实验结果表明,FCM对历史交通状态的评估方式适用于不同的高速路和城市道路场景。其次,随机森林比其它常见的机器学习方法具有更高的预测精度,从而提供实时可靠的短时交通出行信息。     

A Survey of IoT Key Enabling and Future Technologies: 5G,Mobile IoT,Sematic Web and Applications

The Internet of Things (IoT) is the communications paradigm that can provide the potential of ultimate communication. The IoT paradigm describes communication not only human to human (H2H) but also machine to machine (M2M) without the need of human interference. In this paper, we examine, review and present the current IoT technologies starting from the physical layer to the application and data layer. Additionally, we focus on future IoT key enabling technologies like the new fifth generation (5G) networks and Semantic Web. Finally, we present main IoT application domains like smart cities, transportation, logistics, and healthcare.     

面向5G业务的乡镇SPN规划及组网架构

切片分组网凭借其技术优势已成为5G业务主流传送承载网的技术之一。伴随乡镇、农村5G业务高速发展及各类5G垂直行业对5G业务的更高更广需求,前期在市区县城区域部署的SPN已无法完全满足业务需求。为满足乡镇、农村的5G业务发展需求,需考虑将SPN下沉至乡镇层级。基于乡镇5G业务发展趋势,综合考虑乡镇SPN建设条件,结合SPN架构、组网拓扑等条件,搭建乡镇SPN架构模型并深入分析获得某地市实际应用场景建设方案,为后期乡镇SPN建设提供参考和思路。     

Smart Prediction and Monitoring of Waste Disposal System Using IoT and Cloud for IoT Based Smart Cities

One of the prominent applications of Internet of Things (IoT) in this digital era is the development of smart cities. In IoT based smart cities, the smart objects (devices) are connected with each other via internet as a backbone. The sensed data by the smart objects are transmitted to the sink for further processing using multi hop communication. The smart cities use the analyzed data to improve their infrastructure, public utilities and they enhance their services by using the IoT technology for the betterment of livelihood of the common people. For IoT based smart cities, waste collection is a prominent issue for municipalities that aim to achieve a clean environment. With a boom in population in urban areas, an increasing amount of waste is generated. A major issue of waste management system is the poor process used in waste collection and segregation. Public bins begin to overflow for a long period before the process of cleaning starts, which is resulting in an accumulation of bacteria causing bad odors and spreading of diseases. In order to overcome this issue, in this paper an IoT based smart predication and monitoring of waste disposal system is proposed which utilizes off-the-shelf components that can be mounted to a bin of any size and measure fill levels. An Arduino microcontroller is employed in the proposed model to interface the infrared (IR), ultraviolet (UV), weight sensors, and a Global Positioning System (GPS) module is used to monitor the status of bins at predetermined intervals. The proposed system transmits the data using the cluster network to the master module which is connected to the backend via Wi-Fi. As data is collected, an intelligent neural network algorithm namely Long Short-Term Memory (LSTM) is used which will intelligently learn and predict the upcoming wastage from waste generation patterns. Moreover, the proposed system uses Firebase Cloud Messaging to notify the appropriate people when the bins were full and needed to be emptied. The Firebase Cloud Messaging (FCM) JavaScript Application Programming Interface (API) is used to send notification messages in web apps in browsers that provide service work support. Hence, the proposed system is useful to the society by providing facilities to the governments for enforcing stricter regulations for waste disposal. Additional features such as automated calibration of bin height, a dynamic web data dashboard as well as collation of data into a distributed real-time firebase database are also provided in the proposed system.

     

基于5G的智慧社区应用探讨

随着新一轮科技革命和产业变革的深入,围绕社区全生活链服务需求,以人本化、生态化、数字化为价值导向的智慧社区将成为人类更加向往的居住地。智慧社区采用5G网络技术,以大数据、物联网、人工智能等主要技术手段为支撑,统筹各类服务资源,搭建智能运营管理平台,构建各种智慧应用场景,创建高品质社区生活。以长三角地区某城市智慧社区建设为例,分析了智慧社区建设需求,阐述了设计思路、建设内容与应用场景设计,并对智慧社区的发展提出了针对性建议。     

Collaboration IoT-Based RBAC with Trust Evaluation Algorithm Model for Massive IoT Integrated Application

With the recent advances in ubiquitous communications and the growing demand for low-power wireless technology, smart IoT device (SID) to access various Internet of Things (IoT) resources through Internet at any time and place alternately. There are some new requirements for integration IoT servers in which each one is individually gathering its local resources in Internet, which cooperatively supports SID to get some flexibility or temporary contract(s) and privileges in order to access their corresponding desired service(s) in a group of collaboration IoT servers. However, traditional access control schemes designed for a single server are not sufficient to handle such applications across multiple collaboration IoT servers to get rich services in IoT environments. It does not take into account both security and efficiency of IoT servers, which securely share their resources. Therefore, the collaboration IoT-based RBAC (Role-based Access Control) with trust evaluation (TE) algorithm model to reducing internal security threats in intra-server and inter server for the massive IoT integrated application is proposed in this paper. Finally, the three trust evaluation algorithms including a local trust evaluation algorithm, a virtual trust evaluation algorithm and a cooperative trust evaluation algorithm in the proposed collaboration IoT-based RBAC model, which are designed and presented for reducing internal security threats in collaborative IoT servers.

     

Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications

Energy is vital parameter for communication in Internet of Things (IoT) applications via Wireless Sensor Networks (WSN). Genetic algorithms with dynamic clustering approach are supposed to be very effective technique in conserving energy during the process of network planning and designing for IoT. Dynamic clustering recognizes the cluster head (CH) with higher energy for the data transmission in the network. In this paper, various applications, like smart transportation, smart grid, and smart cities, are discussed to establish that implementation of dynamic clustering computing-based IoT can support real-world applications in an efficient way. In the proposed approach, the dynamic clustering-based methodology and frame relay nodes (RN) are improved to elect the most preferred sensor node (SN) amidst the nodes in cluster. For this purpose, a Genetic Analysis approach is used. The simulations demonstrate that the proposed technique overcomes the dynamic clustering relay node (DCRN) clustering algorithm in terms of slot utilization, throughput and standard deviation in data transmission.

     

基于AI深度学习的面向业务5G基站节能系统研究

由于5G业务发展,5G基站数量增多,造成运营商的电费成本急剧增加,节能降耗成为运营商的可持续发展需求。在研究主流5G基站节能模式及多方位5G节能方案的基础上,提出了基于多种AI算法的5G基站节能系统,通过单SIM卡级别的高精度业务识别,在保证5G重要业务等各类型业务稳定运行的基础上,实现了最佳策略的5G基站柔性节能。     

The importance of nature-inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Over the last decade, the Internet of Things (IoT) has become ever more popular, as is evident from its role in changing the human lifestyle and conferring remarkable privileges for them. It has a significant presence in various crucial areas, including smart cities, smart factories, manufacturing, transportation, and healthcare. Massive amounts of data generated by IoT devices have the potential to endanger the lifetime of nodes in IoT-based networks due to increased communication power consumption. It has become crucial to propose solutions for network-based issues, such as quality of service, security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation. To address the mentioned problems, routing protocols play a critical role in data transmission among heterogeneous items. In such environments, routing refers to constructing routes between mobile nodes. Since identifying optimal routes among IoT nodes and establishing an effective routing protocol in an IoT network are an NP-hard issue, employing metaheuristic algorithms may be a viable solution to overcome this problem. Various IoT routing protocols based on metaheuristic algorithms have been presented in recent years, but there is still a lack of systematic study for reviewing the existing works. The current study emphasizes the impact of metaheuristic algorithms in the IoT routing problem, discusses the optimization models, presents a comprehensive comparison of protocols based on critical parameters, and eventually suggests some hints for future studies.