Edge Cloud Selection in Mobile Edge Computing(MEC)-Aided Applications for Industrial Internet of Things(IIoT)Services

In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.

An Industrial Internet Platform for Massive Pig Farming (IIP4MPF)

Pig farming is becoming a key industry of China’s rural economy in recent years. The current pig farming is still relatively manual, lack of latest Information and Communication Technology (ICT) and scientific management methods. This paper proposes an industrial internet platform for massive pig farming, namely, IIP4MPF, which aims to leverage intelligent pig breeding, production rate and labor productivity with the use of artificial intelligence, the Internet of Things, and big data intelligence. We conducted requirement analysis for IIP4MPF using software engineering methods, designed the IIP4MPF system for an integrated solution to digital, interconnected, intelligent pig farming. The practice demonstrates that the IIP4MPF platform significantly improves pig farming industry in pig breeding and productivity.

Smart and collaborative industrial IoT: A federated learning and data space approach

Industry 4.0 has become a reality by fusing the Industrial Internet of Things(IIoT)and Artificial Intelligence(AI),providing huge opportunities in the way manufacturing companies operate.However,the adoption of this paradigm shift,particularly in the field of smart factories and production,is still in its infancy,suffering from various issues,such as the lack of high-quality data,data with high-class imbalance,or poor diversity leading to inaccurate AI models.However,data is severely fragmented across different silos owned by several parties for a range of reasons,such as compliance and legal concerns,preventing discovery and insight-driven IIoT innovation.Notably,valuable and even vital information often remains unutilized as the rise and adoption of AI and IoT in parallel with the concerns and challenges associated with privacy and security.This adversely influences interand intra-organization collaborative use of IIoT data.To tackle these challenges,this article leverages emerging multi-party technologies,privacy-enhancing techniques(e.g.,Federated Learning),and AI approaches to present a holistic,decentralized architecture to form a foundation and cradle for a cross-company collaboration platform and a federated data space to tackle the creeping fragmented data landscape.Moreover,to evaluate the efficiency of the proposed reference model,a collaborative predictive diagnostics and maintenance case study is mapped to an edge-enabled IIoT architecture.Experimental results show the potential advantages of using the proposed approach for multi-party applications accelerating sovereign data sharing through Findable,Accessible,Interoperable,and Reusable(FAIR)principles.

Recent advances in Industrial Internet:insights and challenges

The Industrial Internet is a promising technology combining industrial systems with Internet connectivity to significantly improve the product efficiency and reduce production cost by cooperating with intelligent devices,in which the advanced computing,big data analysis and intelligent perception techniques have been involved.This paper comprehensively surveys the recent advances of the Industrial Internet,including reference architectures,key technologies,relative applications and future challenges.Reference architectures which have been proposed for different application scenarios and their corresponding characteristics are summarized.Key technologies,such as cloud computing,mobile edge computing,fog computing,which are classified according to different layers in the architecture,are presented to support a variety of applications in the Industrial Internet.Meanwhile,future challenges and research trends are discussed as well to promote further research of the Industrial Internet.

An Overview of Privacy Preserving Schemes for Industrial Internet of Things

The concept of Internet of Everything is like a revolutionary storm,bringing the whole society closer together.Internet of Things(IoT)has played a vital role in the process.With the rise of the concept of Industry 4.0,intelligent transformation is taking place in the industrial field.As a new concept,an industrial IoT system has also attracted the attention of industry and academia.In an actual industrial scenario,a large number of devices will generate numerous industrial datasets.The computing efficiency of an industrial IoT system is greatly improved with the help of using either cloud computing or edge computing.However,privacy issues may seriously harmed interests of users.In this article,we summarize privacy issues in a cloud-or an edge-based industrial IoT system.The privacy analysis includes data privacy,location privacy,query and identity privacy.In addition,we also review privacy solutions when applying software defined network and blockchain under the above two systems.Next,we analyze the computational complexity and privacy protection performance of these solutions.Finally,we discuss open issues to facilitate further studies.

Improve the industrial digital transformation through Industrial Internet platforms

1 Introduction 1.1 Definition and stakeholders of the Industrial Internet The Industrial Internet is a novel network technology system that applies the Internet of Things(IoT)to the manufacturing and industrial sectors.It facilitates the connection of various sensors,devices,systems,factories,and enterprises,enabling the sharing and exchange of data to improve production efficiency,reduce costs,enhance product quality,and enable smart manufacturing.The Industrial Internet serves as a crucial cornerstone and essential support for the Fourth Industrial Revolution,offering specific approaches for industrial digital transformation.Through the comprehensive interconnection of people,machines,and things,the Industrial Internet analyzes various data from intelligent feedback,fostering the development of a new manufacturing and service system.

Cloud control for IIoT in a cloud-edge environment

The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.

场景赋能驱动下的工业互联网平台成长演化——“柠檬豆”案例研究

工业互联网平台是工业领域的数字新经济,是数字经济与实体经济融合的关键载体。以“柠檬豆”平台为案例研究对象分析工业互联网平台成长演化机理,研究发现,工业互联网平台场景赋能以平台用户需求场景为牵引,开发冗余数据资源,整合异质资源,实现资源共享、知识传导和数字协同;工业价值网络中的资源映射到工业互联网平台上成为可调用的数据资源,数字孪生产生更丰富的场景,驱动网络效应强化;工业互联网平台成长演化的本质是基于场景赋能体系构建的价值创造过程与基于网络效应形成的生态构建过程之间的交互共演。响应场景驱动创新范式,研究有助于完善平台组织理论,丰富网络效应研究情境,为我国工业互联网平台高质量发展提供理论依据。

工业互联网平台赋能、价值共创与制造企业服务化绩效研究

实施服务化是制造企业形成差异化优势的重要手段,工业互联网平台对推进制造企业服务化具有重要意义。然而当前学术界有关工业互联网平台赋能对制造企业服务化绩效的作用机理缺乏探讨。为了揭示工业互联网平台赋能对制造企业服务化绩效的影响机制,本文基于服务主导逻辑,构建从工业互联网平台赋能到价值共创,再到制造企业服务化绩效的逻辑框架,采用383份来自制造企业的调查数据,通过回归分析发现:工业互联网平台赋能显著提高了制造企业服务化绩效,价值共创的两个维度即互动合作、资源整合,在工业互联网平台赋能对制造企业服务化绩效的正向影响中,发挥了部分中介作用。本文为推动工业互联网平台建设与提高制造企业服务化绩效提供了重要启示。

基于“互联网+交互式”技术的安全教育培训服务平台的建设——以冶金行业为例

冶金企业安全培训的诸多痛点如线下集中脱产培训难以组织、无体系化课程资源、培训形式单一等制约了安全培训工作质量的提高,进而制约了企业安全生产管理水平的提升。针对这些痛点,利用“互联网+交互式”技术的优势,建设了一套集培训学习、练习考试、档案管理、数据统计等功能于一体的安全教育培训服务平台,取得了较好的培训效果,可为企业安全教育转型发展开拓新的局面,具有较好的借鉴意义。

产业互联网时代企业跨组织动态能力的构念与测量

以平台为本质的平台型企业将成为未来企业的主流,而产业互联网的蓬勃发展为新型平台企业的成长提供了助推剂。与传统企业技术开发平台和消费互联网平台(如淘宝、京东)相比,产业互联网平台企业需要跨组织边界的能力,以便在快速变化的环境中推动多元异质主体实现交互赋能和价值共创。针对经典动态能力在解释产业互联网平台企业相关实践方面的不足,以及经典动态能力理论演进的趋势,结合产业互联网的时代特征,提出并阐释了企业跨组织动态能力的概念,明确了企业跨组织动态能力的结构维度,开发出一个包含16个题项的测量量表。以符合条件的89份中国产业互联网平台企业样本数据进行实证检验,结果证实该量表具备良好的信度和效度。该研究旨在为产业互联网平台化场景下企业跨组织动态能力相关的实证研究奠定构念基础。

互联网平台经济下的“炒物”及其治理初探

在互联网平台经济发展背景下,以球鞋为代表的特殊商品在使用性基础上衍生出符号性、贮藏性、圈层性以及投机性,研究此类商品在互联网平台下的炒作机制和治理途径,有助于引导互联网平台资本健康有序发展。平台经济相关业态和商业模式为“炒物”提供了技术手段并开拓了交易空间,消费需求膨胀和消费结构升级是“炒物”的潜在推力,产业转型则是“炒物”的现实条件,流通环节是“炒物”现象的主要场域,资本则是炒作机制形成中的主导力量和背后推手。在炒作过程中,球鞋供给端的品牌方、互联网平台、经销商和炒鞋客共同参与利润的分割,一方面从多维度促使商品转型升级,改善质量和效益,优化了消费体验,另一方面也暴露出一系列矛盾和问题。治理“炒物”现象需要政府和市场形成合力,引导相关产业和业态健康发展,打造合法合规的商业模式,并使消费者理性消费。

平台经济促进江苏现代乡村服务业发展研究

江苏省乡村经济发展良好,但是乡村之间发展不均衡、乡村产业融合深度不够等问题依然存在。要高质量地发展现代乡村服务业,实现全面乡村振兴和共同富裕,政府主导构建乡村数字电商平台是一个可选方案,既能兼顾弱势乡村和弱势产业,也能用数据和流量激活乡村现代服务业,并为乡村数字平台将来的融合发展打好基础。

有色金属加工数字化工厂建设探索

文章从有色金属加工企业数字化转型实际需求出发,探讨了以工业互联网平台为统一底座的有色金属加工数字化工厂总体框架,从设备自动化、生产数字化、运营数字化、数据安全防护四个方面开展研究,提出了有色金属加工数字化工厂的建设思路,赋能有色金属加工企业提高生产效率,优化产品质量,增强设备运行保障,降低生产能源消耗,强化安全生产,提高竞争力。

基于随机演化博弈的工业互联网平台建设策略研究

工业互联网平台存在的高门槛及复杂的应用场景决定了工业互联网平台与消费互联网平台之间建设模式的巨大差异。当前龙头企业主导的工业互联网平台建设模式存在不足。提出“政府引导-平台提供者牵头-中小制造企业协作”的工业互联网平台建设模式,并构建政府、平台提供者、中小制造企业三方随机演化博弈模型,分析各方在建设工业互联网平台时的策略选择。研究发现:外界不确定因素只会对平台提供者和中小制造企业的决策策略造成影响,政府的决策结果不受干扰;政府决策不受初始支持意愿影响,都将选择支持建设工业互联网平台,而平台提供者以及中小制造企业的决策受彼此的意愿正向影响;平台提供者的决策对政府的政策支持更加敏感,中小制造企业决策对政府的资金支持和惩罚力度更为敏感;成本分配系数增大或减小对于中小制造企业和平台提供者具有相反的影响。

场景驱动背景下面向产业互联智能协同的云平台

随着数字技术的迭代升级与实践应用,场景驱动成为新经济时代科技型产业创新的新引擎,并赋能产业互联向数字化、智能化的方向革新。然而,场景驱动下产业供应链合作成员不断增加而引发的资源信息堵塞壁垒、业务繁多交叉以及协同关系错综复杂等问题往往会影响组织间的协同效率及服务质量。为此,提出一种场景驱动下的产业联盟业务智能协同解决方案。该方案首先分析了场景驱动产业互联下多联盟成员之间新的协同需求,提出面向云平台的产业供应链业务协同模型,并构建支撑多源异构业务数据交互的云平台服务架构体系。最后,以应急防疫物资供需产业库存协同为例,验证了云平台智能协同模型的可行性,以期为该领域研究提供参考借鉴。

工业互联网平台赋能研究:前沿探析、内在机理与未来展望

作为一种赋能型数字技术平台,工业互联网平台能够赋能中小企业数智化转型,成为培育新质生产力的重要引擎。本文基于理论分析和案例阐释,明晰了工业互联网平台赋能的内涵、特征、要素和类型,揭示了其内在机理。研究发现:①工业互联网平台赋能是对多元主体利用数智技术基于机会和资源互动生成价值的阐释,具有数智技术集成性、生成性和多主体性,包含数智化工业技术、数智化工业机会、数智化工业资源和多元主体等要素;②工业互联网平台赋能包含结构、场域、心理和资源赋能,遵循“价值主张、价值创造和传递、价值捕获”的价值逻辑;③构建工业互联网平台赋能内在机理的IPO框架,技术、组织和环境层面因素能够影响平台赋能过程进而产生积极和消极作用。本文从新的主题、新的视角、新的机制丰富和细化工业互联网平台赋能研究,为激活工业互联网平台赋能效应提供决策依据,为基于工业互联网平台培育新质生产力助推平台高质量发展提供实践指导。

工业互联网平台资源重构机制研究——基于广度与深度的双重视角

新工业革命背景下传统企业如何利用工业互联网平台进行组织重构具有现实紧迫性。本文基于工业互联网平台广度与深度双重视角,构建企业市场感知能力通过平台连通性和兼容性增强资源重构能力的多重中介模型,并采用214名管理者的调研数据进行实证检验。研究结果表明:市场感知能力促使企业提高资源整合重构能力;企业除了通过工业互联网平台累积的海量数据提高连通性,在数据挖掘基础上满足潜在需求之外,还可以通过平台赋能的泛在化连接增强技术层面与组织层面的兼容性,从而助推企业实现组织重构;工业互联网平台的连通性和兼容性在市场感知与组织重构之间起中介作用。本文研究结论拓展了工业互联网平台的理论研究,为企业利用工业互联网平台实现数字化转型重构提供参考借鉴。

基于BIM的产业协同平台构建及其在智能建造中的应用研究

在工程建设的传统管理模式存在诸多问题以及BIM技术逐步成熟的双重背景下。本论文基于BIM技术,构建了一种基于BIM技术的产业平台,以云计算、大数据、人工智能等技术为支撑的微服务架构,集成数据管理、模型构建、协同管理、决策支持等核心功能,并探究了该平台在智能建造领域的应用场景,如项目规划、施工管理及设施维护等,展示了BIM技术如何提升工程项目的设计精度,优化施工流程,提高建设质量和效率。本文的研究不仅为城市建设的数字化转型提供了理论支持,也为相关行业的实践提供了有益的参考。

钢铁产业互联网平台与企业价值提升——基于微观企业数据的实证分析

钢铁产业互联网平台作为一种新兴商业模式,正在迅速崛起并深刻影响着钢铁行业的发展。研究基于微观企业数据,实证检验钢铁产业互联网平台对企业价值提升的影响,发现加入钢铁产业互联网平台能够显著提升企业价值。从政府、平台和企业角度对于钢铁产业互联网平台的未来决策与发展提供相关建议,扶持钢铁企业入驻钢铁产业互联网平台,平台本身可以进行多方面优化以提高供应链的协调性和运营效率,钢铁企业可以利用平台降低库存成本、提高物流效率,提升企业价值。