• image

    Multi-tier computing networks for intelligent IoT

    Yang Yang

    Different Internet of Things (IoT) applications demand different levels of intelligence and efficiency in processing data. Multi-tier computing, which integrates cloud, fog and edge computing technologies, will be required in order to deliver future IoT services.

    Sensing, communication, computing and networking technologies continue to generate more and more data, and this trend is set to continue. Future Internet of Things (IoT) devices could, in particular, be widely deployed for tasks such as environmental monitoring, city management, and medicine and healthcare, requiring data processing, information extraction and real-time decision making. Cloud computing alone cannot support such ubiquitous deployments and applications because of infrastructure shortcomings such as limited communication bandwidth, intermittent network connectivity, and strict delay constraints. To address this challenge, and ensure timely data processing and flexible services, multi-tier computing resources are required, which can be deployed and shared along the continuum from the cloud to things1,2.

    The cloud, fog, edge and things

    Cloud computing technologies are usually centralized and used for global tasks. Multi-tier computing involves collaborations between cloud computing and fog computing, edge computing and sea computing technologies, which have been developed for regional, local and device levels, respectively (Fig. 1). The integration of these different computing resources is vital for the development of intelligent IoT services3,4.

    imageFig. 1: A multi-tier computing network architecture.

    IoT applications are increasingly intelligent due to more meaningful data, powerful processors and sophisticated algorithms. Typical IoT applications are also shifting from simple data sensing, collection and representation tasks towards complex information extraction and analysis. However, the applications usually follow rules and principles set by a specific industrial domain. Multi-tier computing resources, when integrated with environment cognition, big data and artificial intelligence (AI) technologies, could be used to develop a user-centric approach in which different IoT services are autonomously customized according to specific applications and user preferences.

    Intelligent IoT networks and services with integrated, multi-tier computing resources can be thought of as a large company with a top-down, multi-tier organizational structure: managers and employees at different levels in the company have different resources, capabilities and responsibilities in terms of data access and processing, task assignment, customer development and decision making. Cloud computing is equivalent to the top hierarchical level in the company, possessing the most information sources, the strongest analytical intelligence, the maximum storage space and the highest decision-making authority. As such, cloud computing is expected to handle challenging tasks at the global level, such as cross-domain data analysis and processing, abnormal behaviour diagnosis and tracing, hidden problem prediction and searching, new knowledge discovery and creation, and long-term strategic planning and decisions. Edge computing, on the other hand, is equivalent to front-line staff, having the least resources and capabilities but being able to directly interact with customers in different application domains. Therefore, edge computing is good at handling delay-sensitive tasks at the local level, such as data collection, data compression, information extraction and event monitoring.

    Between the cloud and the edge within the IoT network, there is fog computing, which is equivalent to mid-level management in the company. Like an efficient management system with many levels of resources, duties and responsibilities, fog computing is a hierarchy of shared computing, communication, storage resources and AI algorithms that can collaboratively handle complex and challenging tasks at the regional level, such as cross-domain data analysis, multi-source information processing and on-site decision making for large service coverage. Because user requirements are usually dynamic in terms of time and space, fog computing can provide a flexible approach to incorporate distributed resources at different geographical or logical locations in the IoT network, thus offering timely and effective services to customers5,6,7.

    The devices, or things, of the IoT network are equivalent to the customers of the company, which have numerous different requests and demands for intelligent applications and services. Each device has limited processing, communication, storage and power resources. But, collectively, they contribute to the concept of sea computing at the device level, which supports data sensing, environment cognition, mobility control and other basic functions for individual things in real time3.

    To make the company a success, it is essential to have effective communication and collaboration mechanisms across different levels and units. Similarly, interaction and collaboration between cloud, fog, edge and sea computing are vital in order to create an intelligent collaborative service architecture. As a result, this architecture actively connects the shared computing, communication and storage resources of all the nodes in the IoT network, and fully utilizes their capabilities at different locations and levels, in order to provide intelligent, timely and efficient services according to user requirements. Since most applications and their data do not require superior computing power, this architecture can significantly improve service quality and user experience while saving time, resources and costs4.

    An integrated approach

    Intelligent on-demand services can be created through the interoperability and integration of multi-tier computing sources in the IoT network. To best meet the requirements of any user, centralized cloud computing with huge resources, secure environments and powerful algorithms is needed, but also distributed fog and edge computing with shared resources, accessible environments and simple algorithms for real-time decision making.

    With heterogeneous computing resources and the collaborative service architecture, future multi-tier computing networks can effectively support a full-range of services in different environments and applications. For example, smart cars and drones require low-latency communications for receiving monitoring data and control messages. Autonomous driving and three-dimensional virtual-reality games need powerful computing capabilities at device and edge levels, as well as broad communication bandwidths. Industrial IoT and smart city management systems demand extreme network reliability, data security and service availability.

    Fog computing is the bridge that connects centralized clouds and distributed edges of the network, and thus plays a crucial role in managing multi-tier resources. It is, for example, responsible for vertical and horizontal interoperations, coordination of cross-domain collaborations, deployment of hierarchical rules and policies, and integration of multi-level services. Together with the edge, fog computing makes computing resources and intelligent services in the IoT network more accessible, flexible, efficient and cost-effective.

    The development and standardization of multi-tier computing technologies has just begun, and numerous technical challenges remain1,8. Specifically, in terms of security, trust and privacy, end-users should be able to use a nearby shared computing node without compromising the protection of identity and personal data. Moreover, virtualization and resource visibility capabilities need to be developed to allow the sharing of physical computing resources in different machines and hardware. Efficient orchestration, which refers to managing the allocation of heterogeneous resources and services, requires interoperability between the nodes within the network. Finally, the design of an architecture that is able to serve various groups of users needs the development of a new business model that encourages an ecosystem of shared resources and collaborative services. To address these issues will require a comprehensive research effort that incorporates multidisciplinary approaches across various technological and economic fields8,9,10.

    A case study

    SLAM (simultaneous localization and mapping) is the key technology that helps a robot to sense its environment, generate a navigation map, identify its current position and track its movements. It is useful in a variety of applications including rescue operations, firefighting, underwater exploration and autonomous surveillance. The SLAM task is challenging because it involves delay-constrained processing of a large volume of data from heterogeneous sensors such as cameras, inertial measurement units and laser rangers. Moreover, in life-or-death applications, the task must be completed in real-time despite the limited on-board computing and storage capabilities available in SLAM robots.

    Recently, my colleagues and I at the Shanghai Institute of Fog Computing Technology (SHIFT) have developed a three-tier computing network with collaborative service architecture to help mobile robots accomplish the SLAM task in a timely and effective manner11. Here, the bottom tier is the device level, which consists of multiple robots with limited computing, communication, storage and energy resources. The second tier is the local level, which consists of distributed edge nodes. The edge nodes exist near the robots and can effectively collect data from them. These nodes can also support real-time data processing for local applications and apply protocols to transmit data to the upper tiers. The third tier is the regional level, which is a distributed stream processing framework. Taking advantage of the batch processing engines in the upper-tier fog nodes, regional data can be quickly processed and the final results or decisions can be returned to the robots. Different applications and services execute sophisticated data analytics and decision-making algorithms within this framework, which can process streaming data in real time.

    The multi-tier computing network developed for collaborative SLAM robots is, I believe, an indication of what can be achieved more broadly. In the coming years, there will be a transformation from technology-driven, performance-centric computer plus communication networks towards service-oriented, user-centric multi-tier computing networks, which are composed of heterogeneous shared resources and collaborative service capabilities. This technical trend will promote and accelerate the evolution of intelligent IoT applications and services, leading to improvements in business operations and our everyday lives.


    1. OpenFog Reference Architecture for Fog Computing (OpenFog Consortium, 2017);

    2. Chiang, M. & Zhang, T. IEEE Internet Things J. 3, 854–864 (2016).

    3. Jiang, M. H. Urbanization and Cyberization: Historical Opportunity for China’s Development (EXPO 2010 Shanghai China Forum, 2010).

    4. Chen, N. et al. IEEE Commun. Mag. 56, 95–101 (2018).

    5. Yang, Y. et al. IEEE Internet Things J. 5, 4076–4087 (2018).

    6. Yang, Y. et al. IEEE Internet Things J. 5, 2094–2106 (2018).

    7. Zhao, S. et al. IEEE Internet Things J. 5, 1169–1183 (2018).

    8. IEEE Standard for Adoption of OpenFog Reference Architecture for Fog Computing 1934-2018 (IEEE, 2018); https://standards.ieee.org/standard/1934-2018.html.

    9. Byers, C. C. IEEE Commun. Mag. 55, 14–20 (August, 2017).

    10. Wen, Z. et al. IEEE Internet Comput. 21, 16–24 (March/April, 2017).

    11. Yang, Y. et al. Chinese J. Internet Things 2, 33–40 (2018).

    Author information

    Shanghai Institute of Fog Computing Technology (SHIFT), School of Information Science and Technology, ShanghaiTech University, Shanghai, China, Yang Yang

    More information here.

  • image

    只听说过云计算,雾计算是什么鬼?| 科普帖

    唐婷 畅游IT时空


    和名声大噪的云计算相比,刚刚崭露头角的雾计算可谓是“新生代”。日前,在电气电子工程师学会(IEEE)年度媒体交流会上,国际雾计算产学研联盟大中华区主任、上海雾计算实验室联合主任、IEEE会士杨旸教授透露,全球首个雾计算参考架构国际标准(IEEE 1934)已经发布,同时相关机构正在积极推动开发雾计算节点设备。



    1. 负责上传下达的“中层干部”

    “雾计算是一个从云(Cloud)到物(Thing)的系统级多层次计算架构,具有分发计算、通信、存储、控制和联网等多种功能,更加靠近用户端。它通过资源共享机制、协同服务架构来有效提升生产效率和用户体验。” 杨旸解释道。







    2. 可有效减少数据负载、提升效率

    基于国际雾计算产学研联盟(OpenFog Consortium)的前期积累,雾计算参考架构的第一个国际标准(IEEE 1934)已由IEEE正式发布。

    罗喜良认为,随着IEEE 1934的发布、演进和完善,雾计算将成为通用的多层次计算技术框架,支持智能物联网、5G通信和人工智能等数据本地化和计算密集型的应用需求。










    杨旸举例说,如今在个人运算设备上,例如笔记本、智能手机、智能手表和平板电脑,我们已经能看到雾计算和边缘计算技术的初步应用。比如, Windows 10的重启管理器就是典型案例之一。在自动下载更新后,Windows 10系统可以自主学习用户使用模式,进而计算出最合适的重启系统和安装更新的时间。





    More information here.

  • image


    Q: 改变未来通信的头号技术是什么?

    A: 过去,互联网和不同的无线网络都关注在数据的通信方面,主要是人和人之间的数据通信。未来,由于各种各样的物联网(IoTs)应用,通过资源有限的异构网络传输大量的原始数据将是非常昂贵和低效的。我认为未来的网络应该足够智能,以支持知识的创造和交流,而知识是未知的,隐藏在大量的数据中,因此,传统的透明网络正在向新型智能网络发展,这种新型智能网络利用了整个网络内部越来越多的计算、通信、存储和人工智能(AI)能力,将事物与云端连接起来。

    Q: 中国如何引领通信科技的未来?

    A: 在我看来,中国最大的优势是其在不同应用领域和领域的巨大市场,这将有效地推动新的商业模式和相应的生态系统在多个行业中被创建、发展和成熟。


    A: 在我看来,未来通信最大的障碍是我们现有的思维模式,这些思维模式已经被不同垂直行业的传统商业模式所形成和巩固。为克服这一问题,在互联网技术(IT)、通信技术(CT)、运营技术(OT)等的学术界和工业界,建立的一个覆盖范围广、具有国际影响力的跨学科标准化组织,应率先架起桥梁,统一多个行业的共同要求和不同流程及方法。



    杨旸教授是国家科技重大项目“新一代移动无线宽带通信网”(2008-2020)首席技术委员会委员。该项目由中国工业和信息化部资助。此外,他还是由科技部(大部分)资助的国家863高新技术研发项目“5G系统研发重大项目”的首席技术委员。自2017年1月起,他一直担任 OpenFog 联盟的董事会成员和大中华区总监。



    More information here.

  • image

    The Future of Communications: 5G & Beyond

    Dr. Yang Yang shares his view on the future of transportation.

    What is the number one technology that will change the future of communications?

    In the past, the Internet and different wireless networks are concentrated on the communication of data, mainly from/to human users. In the future, thanks to a variety of Internet of Things (IoTs) applications, it will be very expensive and inefficient to transmit huge-volume of raw data through heterogeneous networks with limited resources. I believe future networks should be intelligent enough to support the creation and communication of knowledge, which is unknown and hidden in massive data. So, traditional transparent networks are evolving towards new intelligent networks, which utilize more and more computation, communication, storage, and Artificial Intelligent (AI) capabilities inside the entire networks connecting things to clouds.

    How is China leading the way to the future of communications?

    In my opinion, the biggest advantage for China is her massive markets in different application areas and domains, which will effectively drive new business models and the corresponding ecosystems to be created, evolve and mature across multiple industry sectors.

    What is the biggest barrier to the future of communications?

    In my opinion, the biggest barrier to the future of communications is our existing mindsets, which have been formulated and consolidated by traditional business models in different vertical industries. To overcome this, a cross-disciplinary standardization organization with wide coverage and international influence, in academic and industrial communities of Internet Technology (IT), Communication Technology (CT), and Operation Technology (OT), should take the lead to bridge and unify the common requirements and different processes/approaches at multiple industry sectors.


    Dr. Yang Yang is currently a full professor with School of Information Science and Technology, ShanghaiTech University, China, serving as the Co-Director of Shanghai Institute of Fog Computing Technology (SHIFT). Prior to that, he has held faculty positions at The Chinese University of Hong Kong, Brunel University (UK), University College London (UCL, UK), and SIMIT, Chinese Academy of Sciences (CAS, China).

    Yang is a member of the Chief Technical Committee of the National Science and Technology Major Project “New Generation Mobile Wireless Broadband Communication Networks” (2008-2020), which is funded by the Ministry of Industry and Information Technology (MIIT) of China. In addition, he is on the Chief Technical Committee for the National 863 Hi-Tech R&D Program “5G System R&D Major Projects”, which is funded by the Ministry of Science and Technology (MOST) of China. Since January 2017, he has been serving the OpenFog Consortium as a Board Member and the Director of Greater China Region.

    Yang’s current research interests include wireless sensor networks, Internet of Things, Fog computing, Open 5G, and advanced wireless testbeds. He has published more than 180 papers and filed over 80 technical patents in wireless communications. He is a Fellow of the IEEE.

    More information here.

  • image




  • image


    来源: 浦计协会 2018/11/18











  • image

    Congratulations to Prof. Yang Yang who was nominated and elected to be the next ASC Chair for the term 2019-2020!



    The 24th Asia-Pacific Conference on Communications (APCC) will be held in Ningbo, China from the 12th to the 14th of November, 2018. The theme of this year's conference is IoT for Smart City: Green and Sustainability. In addition to high-quality technical sessions, the symposium will feature exciting keynotes, tutorials and workshops. It will also offer a fantastic social program.

    More information about APCC 2018.

  • image


    来源: NCEL 网络通信与经济 2018/8/28


    关键词: 边缘计算,深度学习,边缘智能,协同推理
    Key words: Edge Computing, Deep Learning, Edge Intelligence, Co-Inference


    作为人工智能领域的当红炸子鸡,深度学习技术近年来得到了学术界与产业界的大力追捧。目前,深度学习技术已在计算机视觉、自然语言处理以及语音识别等领域大放异彩,相关产品正如雨后春笋般涌现。由于深度学习模型需要进行大量的计算,因此基于深度学习的智能通常只存在于具有强大计算能力的云计算数据中心。考虑到当下移动终端设备的高度普及,如何将深度学习模型高效地部署在资源受限的终端设备,从而使得智能更加贴近用户这一问题以及引起了学术界与工业界的高度关注。针对这一难题,边缘智能(Edge Intelligence)技术通过协同终端设备与边缘服务器,来整合二者的计算本地性与强计算能力的互补性优势,从而达到显著降低深度学习模型推理的延迟与能耗的目的。

    image 图1.基于终端设备与边缘服务器协同的深度学习推断




    image 图2.边缘服务器与终端设备协同推理示例

    除了对模型进行切分(DNN partitioning),加速深度学习模型推断的另一手段为模型精简(DNN right-sizing),即选择完成时间更快的“小模型”,而非对资源需求更高的“大模型”。如图3所示,对于任意深度学习任务,我们可以离线训练具有多个退出点的分支网络,其中,退出点越靠后,模型越“大”, 准确率也越高但相应地推断时延越大。因此,当深度学习任务的完成时间比较紧迫时,我们可以选择适当地牺牲模型的精确度来换取更优的性能(即时延)。值得注意的是,此时我们需要谨慎权衡性能与精度之间的折衷关系(tradeoff)。

    image 图3.具有多个退出点的深度学习分支网络






    image 图4. 基于边缘与终端协同的深度学习模型运行时优化框架Edgent


    陈旭教授2012年于香港中文大学信息工程系获得博士学位,2012年到2014年在美国亚利桑那州立大学网络信息实验室从事博士后研究,2014年到2016年,获洪堡基金会资助成为洪堡学者,在德国哥廷根大学从事科研工作。2016年加入中山大学数据科学与计算机学院,任教授、博导,并入选第13批国家中组部“千人计划”青年项目。目前担任数字家庭互动应用国家地方联合工程实验室、广东省数字家庭互动应用工程实验室副主任。迄今在IEEE Journal on Selected Areas in Communications、IEEE/ACM Transactions on Networking、IEEE Transactions on Mobile Computing、 IEEE INFOCOM、IEEE ICDCS、ACM MOBIHOC、 ACM MM等国际高水平会议与权威期刊发表论文70余篇,ESI高被引论文4篇,热点论文1篇。获得IEEE ComSoc协会亚太区杰出青年学者奖、IEEE ComSoc Young Professional最佳论文奖、CCF A类国际会议IEEE INFOCOM的最佳论文亚军奖、IEEE通信协会旗舰会议ICC最佳论文奖以及国际会议IEEE ISI的最佳论文荣誉提名奖。 周知副研究员2017年于华中科技大学计算机学院获得博士学位,并加入中山大学数据科学与计算机学院,任特聘副研究员。近年来从事云计算、边缘计算、数据中心网络、分布式大数据分析、绿色通信与计算等方面的研究,目前在包括IEEE Journal on Selected Areas in Communications、IEEE Transactions on Parallel and Distributed Systems、IEEE INFOCOM、IEEE ICDCS、ACM SIGMETRICS、IEEE MASCOTS等国际高水平会议以及期刊上发表论文多篇。曾作为主要技术骨干参与国家重点基础研究发展计划973专题项目、国家自然科学重点国际合作项目等多个科研项目。

    En Li, Zhi Zhou and Xu Chen, “Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy”, in ACM SIGCOMM 2018 Workshop on Mobile Edge Communications (SIGCOMM-MECOMM 2018), Budapest, Hungary, August 20, 2018.


  • image


    来源:北邮许昌基地 2018/8/25

    2018年8月16日,IEEE以及IEEE标准协会宣布正式出版“IEEE 1934”标准——《采用OpenFog参考体系结构的雾计算:IEEE标准》。

    IEEE 1934概述

    “IEEE 1934”的制定得到了IEEE通信学会的支持。该标准以OpenFog联盟颁布的参考架构为基础,定义了雾计算的网络架构标准。





    IEEE 1934:基于雾计算的IoT架构



    在这种场景下,可采用分级处理的方式,第一级处理靠近场景的边缘,及时处理本地数据并实时反馈,处理结果分析和汇总可以在云端进行,本地节点同样具备存储能力,不需要将所有数据都传送到云端 。云端处理结果可以根据策略反馈给第一级的边缘处理节点。


    在IoT网络中引入雾计算之后,如图1所示,在IoT网关处引入具备存储、计算、路由能力的雾计算平台,并与 IoT架构的融合,使IoT网关不仅具备路由器的功能,还可根据实际应用场景拥有存储、计算的能力。本地即成为一个智能节点,实现了边缘智能化。

    image 图1 基于雾计算的IoT架构





    IEEE 1934:实现“云雾协同”计算



    IEEE 1934引入“云雾协同”的概念,即边缘的微数据中心可以通过云端的集中管理中心进行管理,简化本地节点的运维复杂度。另外,IoT网关与云端的IoT云平台实现了对接,将本地处理的通用性数据上传给IoT云平台进行处理,形成更高级别的分析结果,为上层应用开发提供数据支撑。




    2017年11月,IEEE与OpenFog联盟联合成立了IEEE P1934工作组,目标是制定雾计算的网络架构标准。


  • image


    杨旸 《秘书工作》杂志





    为了能够及时有效地处理这些数据并提供高质量服务,需要实现资源可视化和网络智能化,即通过资源共享机制和协同服务架构,充分利用网络环境中分散存在的计算、存储、通信和控制等资源,有效提升用户体验,这就是雾计算技术。 雾计算可以有效地对本地物联网数据实施分布式、实时性的智能处理和决策。





    作为云计算的延伸和拓展,雾计算技术充分挖掘和利用用户周边和通信网络中的资源,通常采用便捷灵活的分散式服务,可以实现低成本、本地化的实时数据分析和智能控制优化。 就好比在公司里,处于不同层级的人员具有不同的数据分析、任务处理和决策控制的能力和权限,一线工作人员擅长收集数据,负责完成本地数据压缩、信息提取和异常事件监测;中层干部不仅负责上传下达的信息通信管道,而且能够分析和处理更大区域范围内的复杂数据,做出及时而准确的决策;最高管理者拥有最广控制范围、最多信息来源、最强分析智能、最大存储空间和最高决策权力,负责全局核心数据的统筹分析和处理、异常诊断和溯源、隐患预测和搜寻、知识发现和创造、长期规划和战略决策等重要任务。

    相比云计算模式,雾计算模式更能充分发挥不同位置、不同层次节点的能力和作用,更能体现广泛物联网应用和服务的智能化和高效率。现实中,并非所有的数据都需要传输到远方的云计算中心,并非所有的服务都需要超强计算能力和存储空间。于是, 雾计算在节约时间、资源和成本的同时,显著提升了服务质量和用户体验。雾计算的主要优势包括:更短的服务响应时间、更强的本地化计算能力、更少的数据传输负载、更安全的分散式服务架构,以及更快更精准的分析、决策和控制机制。









  • image

    2018 IEEE ComSoc Summer School on Fog Computing取得圆满成功!


    6月26-29日,为期4天的 2018 IEEEComSoc Summer School on Fog Computing在上海科技大学举办并取得圆满成功。此次活动由IEEE Communications Society (ComSoc) 和国际雾计算产学研联盟(OpenFogConsortium)联合主办,在上海科技大学和中国科学院上海微系统与信息技术研究所指导下,由上海雾计算实验室组织承办,得到了上海科技大学DIAL实验室、赛灵思、思科、日立、IEEE标准协会(IEEE SA)、国家仪器(NI)和中山大学等单位的大力赞助和支持。活动吸引了超过120名来自20多个国家的大学生报名。

    此次活动包括课程和挑战赛两部分。上海科技大学常务副校长印杰教授、中科院上海微系统与信息技术研究所常务副所长谢晓明研究员、上海科技大学信息学院副院长虞晶怡教授分别致欢迎辞。演讲嘉宾包括Russell Hsing教授、候自强先生、杨旸教授、刘军先生、Makoto Yasuda先生、John Zao博士、赵峰先生、宗家友先生等。内容涵盖雾计算技术,及它在5G/6G、智能物联网、工业互联网、安全计算和区块链等最新领域的应用。课程部分还包括由来自中山大学和上海科技大学的老师讲解雾计算关联技术如人工智能、大数据、机器人、凸优化等。学员在课后获得了由IEEE ComSoc 、国际雾计算产学研联盟和上海科技大学颁发的结业证书。

    28日开始了雾计算挑战赛,有11支来自包括中山大学、北京邮电大学、天津大学、浙江大学、上海科技大学、悉尼科技大学、新竹交通大学等国内外知名高校的队伍参加,主题为雾计算使能的智能机器人应用。经过连续24小时的激烈角逐,在29日上午圆满结束,比赛作品精彩多样,创意十足。经过Rob Fish、Russell Hsing、刘军、Mehmet Ulema 、Makoto Yasuda五位评委的独立评判,Foggy Star队荣获冠军,WWG和Misty队分别赢得了亚军和季军。


  • image

    2018 IEEE ComSoc Summer School on Fog Computing 6月26-27日课程圆满结束!


    2018 IEEE ComSoc Summer School on Fog Computing 6月26-27日课程圆满结束,OpenFog Hackathon火热进行中,让我们期待今天中午冠军的产生,敬请关注!

  • image


    Standard provides industry-accepted framework to enable performance and security while accelerating innovation and market growth in IoT, 5G and AI

    FREMONT, CA (June 26, 2018) – The OpenFog Consortium’s OpenFog Reference Architecture for fog computing has been adopted as an official standard by the IEEE Standards Association (IEEE-SA). The new standard, known as IEEE 1934™, relies on the reference architecture as a universal technical framework that enables the data-intensive requirements of the Internet of Things (IoT), 5G and artificial intelligence (AI) applications.

    “We now have an industry-backed and -supported blueprint that will supercharge the development of new applications and business models made possible through fog computing,” said Helder Antunes, chairman of the OpenFog Consortium and senior director, Cisco. “This is a significant milestone for OpenFog and a monumental inflection point for those companies and industries that will benefit from the ensuing innovation and market growth made possible by the standard.”

    Fog computing is a system-level horizontal architecture that distributes resources and services of computing, storage, control and networking anywhere along the cloud-to-things continuum. It supports multiple industry verticals and application domains, enables services and applications to be distributed closer to the data-producing sources, and extends from the things, over the network edges, through the cloud and across multiple protocol layers. The OpenFog Consortium was founded more than two years ago to accelerate adoption of fog computing through an open, interoperable architecture.

    “The reference architecture provided a solid, high-level foundation for the development of fog computing standards,” said John Zao, Chair, IEEE Standards Working Group on Fog Computing & Networking Architecture Framework, which was sponsored by the IEEE Communications Society’s Edge, Fog, and Cloud Communications Standards Committee. “The OpenFog technical committee and the IEEE standards committee worked closely during this process and benefited from the collaboration and synergies that developed. We’re very pleased with the results of this standards effort.”

    The OpenFog Reference Architecture, released in February 2017, is based on eight core technical principles, termed pillars, which represent the key attributes that a system needs to encompass to be defined as “OpenFog.” These are security, scalability, openness, autonomy, RAS (reliability, availability, and serviceability), agility, hierarchy and programmability. The reference architecture, and now the IEEE standard, addresses the need for an interoperable end-to-end data connectivity solution along the cloud-to-things continuum.

    “As a consortium, we developed the OpenFog Reference Architecture with the intention that it would serve as the framework for a standards development organization,” Antunes said. “We’re pleased to have worked so closely with the IEEE in this effort as the result is a standardized computing and communication platform that will serve as a catalyst to the next digital revolution.”

    IEEE standards form the building blocks for product development by establishing consistent protocols that can be universally understood and adopted. This fuels compatibility and interoperability and simplifies product development, and speeds time-to-market.

    The massive and growing amounts of data produced, transported, analyzed and acted upon within industries such as transportation, healthcare, manufacturing and energy—collectively measured in zettabytes—is exposing challenges in cloud-only architectures and operations that reside only at the edge of the network. Fog computing works in conjunction with the cloud and across siloed operations to effectively enable end-to-end IoT, 5G and AI scenarios.

    The new fog standard, along with numerous fog computing-related technologies, uses cases, applications, and tutorials will be featured at the upcoming Fog World Congress, October 1-3 in San Francisco. For more information, visit fogcongress.com.

    The OpenFog Consortium is a thriving ecosystem of organizations who share a collective vision that fog computing is a key enabler to IoT and other advanced concepts in the digital world. For information on membership, visit https://www.openfogconsortium.org/membership-information/.

    About OpenFog

    The OpenFog Consortium was founded to accelerate the adoption of fog computing and address bandwidth, latency and communications challenges associated with IoT, 5G and AI applications. Committed to creating open technologies, its mission is to create and validate a framework for secure and efficient information processing between clouds, endpoints, and services. OpenFog was founded in November 2015 and today represents the leading researchers and innovators in fog computing. For more information, visit www.openfogconsortium.org; Twitter @openfog; and LinkedIn /company/openfog-consortium.

    About Fog World Congress

    Fog World Congress is the largest fog-centric conference, created to bring business, technology and research together to explore the technologies, challenges, deployments and opportunities in fog computing—the enabler for AI, IoT and 5G. The 3-day conference will take place in San Francisco from October 2 – 3, with a pre-conference day on October 1 for technical tutorials and the latest research findings. For more information, visit fogcongress.com

    About the IEEE Standards Association

    The IEEE Standards Association, a globally recognized standards-setting body within IEEE, develops consensus standards through an open process that engages industry and brings together a broad stakeholder community. IEEE standards set specifications and best practices based on current scientific and technological knowledge. The IEEE-SA has a portfolio of over 1,250 active standards and over 650 standards under development. For more information visit http://standards.ieee.org.

    About IEEE ComSoc

    The IEEE Communications Society (IEEE ComSoc) is a leading global community comprised of a diverse set of professionals with a common interest in advancing all communications and networking technologies. IEEE ComSoc has over 26,000 members in more than 138 countries. For more information, visit www.comsoc.org.

    Media contact

    Ken Zeszutko | Z Corp PR | kenz@zcorppr.com | 321-213-1818


  • image




    若你好不容易才弄清楚技术界所说的“云端”是什么意思(没人能100%肯定其含义),那我们带来的可能是坏消息:人们已经开始谈论 “雾端”了。



    而另外一些时候,你需要的是云端,比如在Google Docs上与他人协作,在微博上分享照片,或上传公司年度报告供地球另一端的同事查看。







    类似技术界开放雾联盟(Open Fog Consortium)的支持者认为随着物联网的快速普及,雾计算将大有前途——因为在物联网中,大大小小的设备连接起来产生的数据必须快速进行处理,其对速度的要求超过了云端宽带的能力。比如,自动驾驶汽车就能用到雾计算:这些汽车依赖的是远程服务器,但在紧急关头它们必须可以自己做决定,即使在没有网络连接的情况下。

    若雾端和云端的比喻还不够,有些网络还添加了一层“the mist”。这通常包括比雾端更靠近网络边缘的传感器和其他设备的低功耗计算机,目标是实现更低的延迟。


    文|Steven Melendez




  • image



    2018年6月2日,第五次上海无线通信研讨会在上海大学成功举办。本次研讨会由上海大学和IEEE VTS上海分会联合举办,会议邀请了工业界与学术界相关领域的专家学者齐聚上海大学,分享各自在车联网、太赫兹、大规模MIMO、边缘计算/雾计算等方面的最新研究成果,探讨无线通信的未来与发展。上海雾计算实验室联合主任罗喜良教授和实验室王昆仑博士受邀在会上作了关于雾计算网络中大规模MIMO技术和任务调度技术的报告,并向与会专家、领导介绍了上海雾计算实验室。

  • image












  • image


    2018年3月7日中午,上海雾计算实验室(SHIFT: Shanghai Institute of Fog Computing Technology)午餐会在上海科技大学信息学院顺利举办。

    2018年3月7日中午,上海雾计算实验室(SHIFT: Shanghai Institute of Fog Computing Technology)午餐会在上海科技大学信息学院顺利举办。此次午餐会旨在答谢上海科技大学信息学院各位老师对SHIFT实验室成立近一年来的关心与厚爱,并借此机会汇报实验室的科研进展,以便进一步探讨互利共赢的合作机会。





  • image



    图说:上海雾计算实验室 新民晚报见习记者 郜阳 摄







    图说:雾计算节点与机器人协同配合避障实验 来源/郜阳 摄











    有些用户需求和数据经过分布式的雾计算节点处理后无需再上传云端,更好满足了实时服务的需求,其特有的灵活配置、低成本等优势也让其前景被普遍看好。 罗喜良表示,“‘双十一’那天相信很多人都有网卡的经历,这就是数据集中到云端延时的一个典型表现。当数据处理分散到本地后,这样的情况就会大大减少。”在解决交通拥堵、勘测复杂地形、视频监控等方面,雾计算也都能大显身手。


    新民晚报见习记者 郜阳


  • image

    Fog Computing:Computing Gets Foggy

    Samuel Greengard
    March 13, 2018
    image Fog computing, through a combination of hardware and software, determines where to tackle processing for optimized performance and cost efficiency.

    Today's highly distributed computing frameworks introduce an array of practical and technical challenges. Yet, none is bigger than ensuring that processing takes place at exactly the right place and that the optimal level of resources is devoted to the task. Over the last few years, as the boundaries of computing have expanded and the Internet of Things (IoT) has taken shape, boosting speed and reducing latency has become paramount.

    "There's a growing recognition that traditional computing approaches aren't effective or sustainable for the IoT," says Sam Bhattarai, director of technology and engagement for Toshiba America Research Institute. Even cloud and conventional edge computing, which place resources closer to the point of data processing, often have limited impact for highly distributed systems, such as those used by smart cities or specialized medical applications. In many cases, latency introduces problems and risks.

    Consequently, a new concept is taking shape: fog computing. It pushes data processing through an intermediary layer of computing and communications, such as an IoT gateway or "fog node" that connects to multiple IoT devices and data points. Fog computing, through a combination of hardware and software, determines where to tackle processing for optimized performance and cost efficiency.

    "The system provides computing services along the continuum from cloud to things," says Yang Yang, a professor at ShanghaiTech University and the Shanghai Institute of Microsystem and Information Technology (SIMIT) of the Chinese Academy of Sciences, and director for the Greater China Region of the OpenFog Consortium.

    Beyond the Clouds

    The idea of pushing processing closer to the precise point at which it is needed at any given moment is part of the natural evolution of computing, Yang says. The term "fog computing" was introduced by Cisco Systems in 2012. The goal is to extend computing capabilities from the cloud to the edge of the network in order to more efficiently process the terabytes of data generated by millions of applications daily. Today, technology providers from around the world are updating switches, routers and other gear to better fit a fog computing model, which is promoted by the OpenFog Consortium and the IEEE Standards Association.

    The use cases are significant and span numerous areas and industries. The technology could help autonomous vehicles adapt to changing conditions, smart buildings operate more efficiently, improve the way logistics companies manage shipping, better integrate disparate healthcare functions, boost the delivery of video entertainment over the Internet, and even change the way agricultural firms plant and manage crops.

    Mung Chiang, John A. Edwardson Dean of the College of Engineering at Purdue University, and founder of the Princeton EDGE Lab devoted to research, education and innovation in edge computing and edge networking, describes fog as a superset of edge computing.

    Bhattarai says there are some important distinctions between edge computing and fog computing. Essentially, the edge relies on one-to-one connectivity between the edge machine and the cloud, while the fog relies on a variety of methods and tools, depending on the specific need and the particular requirements of the IOT and the protocols these devices use. In some cases, fog could use smaller clouds mixed with fog infrastructure; it could also reach across horizontal domains in order to reach across industrial and vertical industries and domains, he explains.

    Consider a smart city scenario, where it's critical to manage traffic signals and optimize the flow of vehicles. Data may need to flow from one device or node to another—a block away or across town—in real time. "If you attempt to address the task through basic edge connectivity, the latency can become quite extensive because all the data has to go to the cloud," Bhattarai says. However, "With a fog architecture, you can have processing take place at the point it's required at the exact time it is required. It can take place in a way that best fits the computing requirements."

    The Fog Lifts

    Fog computing ultimately addresses a few challenges: it creates more efficient data pathways while potentially lowering complexity and costs. "There are physical constraints associated with how much data can be transferred when you have upwards of 20 billion IoT devices," Bhattarai explains. "Conventional infrastructure and bandwidth cannot address the data requirements." Similarly, it's not efficient to send all the data from all the devices and sensors to the cloud. "If you try to architect a framework to accommodate the massive data requirements, it becomes completely unaffordable," he adds.

    Yang says fog computing complements emerging technology trends such as 5G mobile communications, embedded AI, and IoT tools and applications. The primary challenges for now are addressing system architecture and interoperability. "You have to manage dispersive computing resources and services properly so that data processing and decisions can take place locally. This also requires new and different interfaces and configuration," says Yang. "You want to be able to use and reuse computing resources and components. A conventional cloud environment is too centralized to provide ideal results for the IoT, especially for various delay-sensitive applications."

    A market report from 451 Research predicts the fog computing market will exceed $18 billion by 2022—with the energy, transportation, healthcare, and industrial markets leading in fog adoption. Notes Christian Renaud, research director for the Internet of Things at 451 Research and lead author of the report: "It's clear that fog computing is on a growth trajectory to play a crucial role in IoT, 5G, and other advanced distributed and connected systems."

    Samuel Greengard is an author and journalist based in West Linn, OR, USA.

    Get fulltext here.

  • image




















    云端,你是否已经习惯将自己的很多照片、音乐、视频等数据,上传到这个神奇的所在? 云计算改变了我们的工作和生活习惯,“把数据交给云去处理”让我们可以用更简单的终端设备,获得更强大的信息处理能力。







    “这就好比一个公司,如果事无巨细都要董事会来开会做决定,在公司业务规模小的时候是可能做到的,但公司发展到一定规模,就不可能实现了。”国际雾计算产学研联盟( OpenFog Consortium)大中华区主任、上海雾计算实验室联合主任杨旸教授介绍。


    那么,能否将终端设备做得足够强大,完全靠自己来处理所有的信息呢? 杨旸说,现在的终端设备处理能力的确比以前强大,也廉价许多,但在很多设备上还是会受限制,火灾救援机器人就是这样。当机器人进入救援现场,第一步要做的是激光扫描现场地形,然后进行数据处理,建立现场地图,最后才能进行搜救行动——如果完全靠机器人自己来处理这些任务,就会浪费宝贵的电池电量和救援时间;如果传送到云端进行处理,又难以及时作出回应。这时,设置在救援现场附近的雾计算节点,就可以发挥及时响应、提供更强大信息处理能力的作用。



















    使用无人机 (也称“飞行机器人”和“无人飞行器”) 这一概念备受关注。无人机在一定程度上可以降低成本、减少拥堵和对环境的影响。然而无人机的部署也面临挑战:网络的带宽和可用性、无人机中枢管理、监管考虑等。这一案例充分展示了雾计算环境中无人机投递包裹的优点、要求和限制。







  • image

    国际开放雾计算产学研联盟(OpenFog Consortium)成员大会在香港召开

    2018年1月31日-2月1日,国际开放雾计算产学研联盟(OpenFog Consortium)2018年度首次成员大会在香港召开。国际开放雾计算产学研联盟大中华区主席、上海雾计算实验室联合主任杨旸教授代表大中华区回顾总结了2017年全年的工作。

    2018年1月31日-2月1日,国际开放雾计算产学研联盟(OpenFog Consortium)2018年度首次成员大会在香港召开。国际开放雾计算产学研联盟大中华区主席、上海雾计算实验室联合主任杨旸教授代表大中华区回顾总结了2017年全年的工作。



  • image


    2018年2月2日,中国雾计算大会在香港圆满举行。本次雾计算大会由国际开放雾计算产学研联盟(OpenFog Consortium)大中华区和上海雾计算实验室共同承办,并得到了中国通信学会的大力支持。会议邀请了国内外工业界和学术界相关领域的专家学者齐聚香港,分享各自最新的研究成果。本次会议共吸引了来自上海、江苏、香港、澳门、台湾、加拿大、美国等国内外六十余名专家学者和研究生参会。

    2018年2月2日,中国雾计算大会在香港圆满举行。本次雾计算大会由国际开放雾计算产学研联盟(OpenFog Consortium)大中华区和上海雾计算实验室共同承办,并得到了中国通信学会的大力支持。会议邀请了国内外工业界和学术界相关领域的专家学者齐聚香港,分享各自最新的研究成果。本次会议共吸引了来自上海、江苏、香港、澳门、台湾、加拿大、美国等国内外六十余名专家学者和研究生参会。

    image image

    2月2日上午,大会在国际开放雾计算产学研联盟主席Helder Antunes先生的演讲中开场。


    中国通信学会的常务副秘书长宋彤发来视频致辞,祝贺2018年中国雾计算首次大会在香港举办,中国通信学会作为IEEE Communication Society的长期合作伙伴,将一如既往地全力支持雾计算和联盟在国内发展。




    Intel美国的首席工程师Katalin K. Bartfai-Walcott女士介绍了“雾计算技术:架构概述”。


    ADLINK的首席技术官(CTO)Angelo Corsaro先生做了“智慧城市新时代”的分享。




    来自香港中文大学网络编码中心的Alfred Ho教授给大家演示了分批稀疏编码技术。















  • image

    China Fog Computing Forum

    Hong Kong

    Friday, 2 Feb 2018

    Fog computing is rapidly emerging as the necessary architecture in IoT, 5G and other advanced digital scenarios, due to latency, cloud networking and bandwidth challenges in traditional architectural approaches. Please join us for the first China Fog Computing Conference in 2018 on fog computing in Hong Kong, hosted by the OpenFog Consortium Great China Region. This free event will help you understand why fog computing is considered to be one of the top technologies. You will learn:

    - Why fog computing is the necessary architecture for IoT, 5G and AI

    - How customers are deploying fog computing via real-world use cases

    - Technical advantages and challenges of fog computing

    - The OpenFog Reference Architecture

    - Security challenges in fog computing


    9:00am-17:00pm, Friday, 2 Feb 2018


    Sung Room, 4th Floor, SHERATON HONG KONG HOTEL & TOWERS, 20 Nathan Road, Kowloon, Hong Kong


    Please send email to lizq@shanghaitech.edu.cn and mingtuo.zhou@wico.sh to register for the conference

    Registration Deadline: January 22, 2018


    Single/Double Room Rate: 1600 HKD/1800 HKD night + tax + fees

    Deadline to book rooms at this rate is January 18, 2018.

    Click here to make your room reservation.



    Helder Antunes, Senior Director, Corporate Strategic Innovation Group at Cisco; Chair, OpenFog Consortium


    Yang Yang, Shanghai Institute of Microsystem and Information Technology (SIMIT) | ShanghaiTech University


    Angelo Corsaro, Chief Technology Officer (CTO) at ADLINK Technology Inc


    Katalin K. Bartfai-Walcott, Principal Engineer, Fog Computing Architecture, Intel Corporation; OpenFog Consortium, Manageability and Orchestration Work Group Chair


    Yang Liu, the II-IDS Research Project Lead of the technology and standards research institute, CAICT


    Norikatsu Takaura, Senior Researcher, Center for Technology Innovation – Electronics, Hitachi


    Hank Ching-Yao Huang, Professor, National Chiao-Tung University


    Ming Yi, Senior Policy Manager, Intel


    Jianwei Huang, IEEE Fellow, Professor, The Chinese University of Hong Kong


    John K. Zao, Professor, National Chiao Tung University, Chair, IEEE Communication Society Standard Working Group on Fog Computing and Networking Architecture Framework


    Jun Liu, Global Distinguished Engineer, Cisco






    Opening Comments

    Helder Antunes, Senior Director, Corporate Strategic Innovation Group at Cisco; Chair, OpenFog Consortium


    Talk 1: Fog Computing for 5G/IoT Development

    Yang Yang, IEEE Fellow, Shanghai Institute of Microsystem and Information Technology (SIMIT) & ShanghaiTech University


    Talk 2: The New Age of Smart Cities

    Angelo Corsaro, CTO, ADLINK


    Talk 3: The Technology of Fog Computing: Architectural Overview

    Katalin K. Bartfai-Walcott, Principal Engineer, Intel USA


    Tea Break & Demo


    Talk 4: Industrial Internet of Things and Edge Computing in China

    Yang Liu, the II-IDS Research Project Lead of the technology and standards research institute, CAICT


    Talk 5: The Era of Fog Computing and Testbed for Interoperability

    Norikatsu Takaura, Senior Researcher, Center for Technology Innovation – Electronics, Hitachi


    Panel Topic: Standardization and Technical Trends

    Moderator(s):John K. Zao

    Panelist(s): Yang Yang, Angelo Corsaro, Katalin K. Bartfai-Walcott, Yang Liu, Ming Yi




    Talk 6: Fog Testbed at GCR Taiwan

    Hank Ching-Yao Huang, Professor, National Chiao Tung University


    Talk 7: Fog Computing: Enabling Autonomy and AI

    Ming Yi, Senior Policy Manager, Intel


    Talk 8: A General Framework for Crowdsourcing Mobile Resources

    Jianwei Huang, IEEE Fellow, Professor & Director of the Network Communications and Economics Lab, The Chinese University of Hong Kong


    Tea Break & Demo


    Talk 9: IoT + Fog Security, Challenges and Opportunities

    John K. Zao, National Chiao Tung University, Chair, IEEE Communication Society Standard Working Group on Fog Computing and Networking Architecture Framework


    Talk 10: Fog Application in IoT

    Jun Liu, Global Distinguished Engineer, Cisco



  • image

    Fog and Fogonomics

    Challenges and Practices of Fog Computing, Networking, Strategy, and Economics

    Call for Contributors

    With the development of Internet of Things technology, connected devices will generate huge amounts of data every single day. It becomes a big challenge to analyze and create actionable information from the data. Fog computing, as a promising solution to extend the capability of Clouds, has attracted considerable attention. Fogs are lightweight distributed technology platforms. To improve efficiency and reduce the amount of data transported to the cloud for processing, analysis and storage, it extends cloud computing and services to the edge of the network, bringing the advantages and power of the cloud closer to where data is created and acted upon. Fog computing aims to create a smart environment with networked devices, which distributes computing, storage, control, and networking functions in the most logical, efficient place between the data source and the cloud. To successfully build upon, integrate with, or create a fog environment requires an understanding of its common inner mechanics, architectural layers, and models, as well as an understanding of the business and economic factors that result from the adoption and real-world use of fog-based services.

    This book aims to establish concrete, technology-centric coverage with a focus on the system model, architectures, and well-defined building blocks for fog computing platforms and solutions. Subsequent to the technology-centric coverage, the book proceeds to establish business models and metrics that allow for the economic assessment of fog-based ICT resources, especially for mobile resources. In some cases, the fog enables new business models, strategies, and competitive differentiation, as with ecosystems of connected, smart, digital products and services. In other cases, costs can be minimized through statistical workload aggregation effects or backhaul data transport reduction, customer experience and safety can be enhanced through reduced response time, and revenue and competitive advantage can be enhanced through new fog-enabled business models.

    We are soliciting chapter contributions with technical and economic insights for the scopes of this book. Topics of interest include, but are not limited to:

    1. Fog Computing Reference Architecture

    2. Fog Standardization Activities

    3. Manageability of Fog Networks

    4. Interoperability between Cloud, Fog, Edge and Things

    5. Software Infrastructure for Fog Services

    6. Fog-Enabled Applications

    7. Fog-Enabled Competitive Strategies

    8. Economic Modeling and Analysis of Fog Computing and Networking

    9. Fogonomics and Potential Advantages

    10. Mobile Data Trading and Task Offloading

    11. Fog Business Models and Challenges

    12. Distributed SLA Negotiation

    13. Fog Security and Privacy

    14. Fog As A Service Technology

    15. Fog Services and Case Studies

    Important Dates

    Chapter Abstract Submission (<2 pages, including a chapter structure): 15 Jan. 2018

    Invitation for Chapter Contributors: 1 Feb. 2018

    Full Chapter Submission (magazine-style): 15 Mar. 2018

    Review Result to Chapter Contributors: 1 May 2018

    Final Version Submission: 1 Jun. 2018

    Final Acceptance Notification: 1 Jul. 2018

    Camera-Ready Submission: 1 Aug. 2018


    Yang Yang, SIMIT, Chinese Academy of Sciences, yang.yang@wico.sh

    Jianwei Huang, The Chinese University of Hong Kong, jwhuang@ie.cuhk.edu.hk

    Tao Zhang, Cisco, tazhang2@cisco.com

    Joe Weinman, joeweinman@gmail.com

    Publisher: Wiley

    Publication Date: First Quarter, 2019

  • image

    IEEE Globecom 2017雾计算Tutorial圆满完成

    IEEE Globecom 2017于12月4-8日在新加坡举办,在8日上午举行的学术讲座(Tutorial) - “Fog as a Service Technology (FA2ST): a New Approach for the Development of 5G Applications”中,上海雾计算实验室联合主任杨旸教授、罗喜良教授对雾计算在5G开发中的应用做了精彩演讲。

    IEEE Globecom 2017于12月4-8日在新加坡举办,吸引了来自世界各地的2000多位科学家、研究人员和行业从业者,是世界通信界最重要的一次学术盛事。

    在8日上午举行的学术讲座(Tutorial) - “Fog as a Service Technology (FA2ST): a New Approach for the Development of 5G Applications”中,上海雾计算实验室联合主任杨旸教授、罗喜良教授对雾计算的本质和其在5G中的应用做了精彩演讲,雾计算实验室顾问、思科公司(美国)首席科学家张涛博士,同时台湾大学Ai-Chun Pang教授分别就雾计算研发背景和雾计算无线接入网做了精彩演讲。

    image image image image image
  • image

    上海雾计算实验室参展IEEE Globecom 2017

    IEEE Globecom 2017大会于12月4-8日在新加坡举办,上海雾计算实验室机“Fog-enabled Robot SLAM”项目成功参展。

    IEEE Globecom是通信领域全球最高规格、最大规模、最具影响力的顶级学术会议,覆盖包括语音、数据、图像和多媒体通信等热点问题的技术和其他活动。

    IEEE Globecom 2017于12月4-8日在新加坡举办,吸引了来自世界各地的2000多位科学家、研究人员和行业从业者。上海雾计算实验室"Fog-enabled Robot SLAM"项目在本次大会上成功展示,并获得参会人员的热烈关注和积极反馈。大家对雾计算、机器人SLAM等提出了很多有意义的问题,这次活动不但成功展示了雾计算实验室的研究成果,宣传了雾计算实验室,也借此机会成功地宣传了雾计算技术和国际开放雾计算产学研联盟,对实验室以后的工作做了很好的铺垫作用。

    image image
  • image







  • image

    中国科学院百人学者论坛 —上海雾计算学术研讨会

    上海雾计算学术研讨会暨中国科学院百人学者论坛于2017年11月18-19日在中国科学院上海微系统与信息技术研究所成功举办。研讨会由中国科学院百人学者论坛主办, 中国科学院上海微系统与信息技术研究所、中科院无线传感网与通信重点实验室、上海雾计算实验室、上海无线通信研究中心、国际开放雾计算(OpenFog)产学研联盟大中华区共同承办。

    上海雾计算学术研讨会暨中国科学院百人学者论坛于2017年11月18-19日在中国科学院上海微系统与信息技术研究所成功举办。研讨会由中国科学院百人学者论坛主办, 中国科学院上海微系统与信息技术研究所、中科院无线传感网与通信重点实验室、上海雾计算实验室、上海无线通信研究中心、国际开放雾计算(OpenFog)产学研联盟大中华区共同承办。

    雾计算(Fog Computing)是一种将数据、计算处理、应用程序、网络传输服务等分散在网络边缘设备上而非全部集中在云上的一种计算模式,是云计算(Cloud Computing)的延伸概念。本次研讨会以 “雾计算的应用场景、理论问题和技术挑战” 为主题。旨在推广雾计算在教育、科研及产业领域的深度合作与协同创新,促进产学研领域更广泛、深入的研发合作与交流。

    11月18日大会中,中科院微系统与信息技术研究所袁晓兵副所长致欢迎辞。之后,华中科技大学葛晓虎教授做“5G移动通信与计算能耗研究”报告;中科院微系统所沈斐副研究员做“雾计算网络的能效分析和架构优化设计”报告;中科院微系统所王昆仑博士做“高能效无线通信与边缘存储”报告。专家学者还饶有兴致地对实验室的雾计算Open 5G和Open Fog验证和实验平台进行了考察和参观。

    11月19日大会中,中科院微系统所狄增峰处长致辞,对参会嘉宾表示欢迎和感谢。中科院上海微系统与信息技术研究所中国科学院无线传感网与通信重点实验室主任、上海雾计算实验室联合主任杨旸教授做“支持5G物联网应用研发的雾计算”报告;悉尼科技大学毛国强教授做“边缘计算、雾计算、云计算及其在智能交通系统中的应用”报告;中山大学陈旭教授做“Computation Offloading for Fog Computing”报告。研讨会还邀请了思科(中国)全球杰出工程师刘军、中科院苏州生物医学工程技术研究所贾宏博研究员、中科院计算所高通量计算机研究中心尤海航研究员、中科院计算所无线通信技术研究中心周一清研究员、中国科学技术大学龚晨研究员、上海交通大学华存卿教授、华东师范大学刘虹副研究员、中科院微系统与信息技术研究所张武雄副研究员和陈南希博士等分别做了精彩报告,与听众分享了雾计算与其他计算方式的异同、在5G与IoT技术中的垂直应用和发展、雾计算技术架构、面临的挑战和在车联网中的应用等内容。来自西安电子科技大学、华为公司等单位的众多专家学者参加了本次研讨会,现场气氛热烈。


  • image




  • image

    Fog World Congress 2017

    Fog World Congress(FWC) 2017于10月30日至11月1日在美国圣克拉拉,由OpenFog联盟和IEEE通信学会联合举办,作为雾计算的第一次国际大会首次将产业和研究人员聚集在一起探讨雾计算和网络的最新技术与发展。

    Fog World Congress(FWC) 2017于10月30日至11月1日在美国圣克拉拉,由OpenFog联盟和IEEE通信学会联合举办,作为雾计算的第一次国际大会首次将产业和研究人员聚集在一起探讨雾计算和网络的最新技术与发展。


    image image image
  • image


    中山大学边缘雾计算研讨会定于 2017 年 11 月 11 日在中山大学东校区举行,地点为广州市广州大学城外环东路 132 号中山大学-卡内基梅隆大学联合工程学院 102 讲学厅,本次研讨会由中山大学数据科学与计算机学院及电子与信息工程学院主办。

    边缘/雾计算(Edge and Fog Computing)技术通过将计算存储能力与业务服务能力向网络边缘迁移,使应用、服务和内容可以实现本地化、近距离、分布式部署,从而有力支撑未来5G 与智能物联网应用的高容量、强计算、以及低延时、高可靠等任务业务需求。同时,充分利用边缘/雾计算,通过网络大数据深度学习与挖掘,实现智能化移动网络信息感知与性能优化,促进通信、计算和存储的深度协同融合。由于潜力巨大和应用广泛,边缘/雾计算已成为当前学术界和产业界极其关注的研究热点之一。本研讨会的内容将围绕边缘/雾计算的基础理论与关键技术展开,探讨和交流边缘/雾计算分布式资源协同调度、边缘-云端融合计算、通信、计算和存储资源协同、以及边缘/雾计算编程架构等多个方向的最新研究进展与成果。 Read More

  • image

    Call for Papers: Fog Networks - JCN

    Publication Date: June 2018

    Fog computing as an extension of cloud computing is able to deploy data storage, computing and communication, control and management along the cloud to things continuum. From a systematic perspective, fog networks provide a distributed computing system with a hierarchical topology. Fog networks aim at meeting stringent latency requirements, reducing power consumption of end devices, providing real-time data processing and control with localized computing resources, and decreasing the burden of backhaul traffic to centralized data centers. However, in the era of fog computing and networks, we need to rethink about end-to-end network architecture, fog-enabled service management mechanisms, computing offloading and task allocation among fog-cloud or fog-fog nodes, context-aware computing and communication tradeoff analysis, fogonomics and operational models, and scalability and security issues. Read More

  • image

    Sherman Shen和Winston Seah参观上海雾计算实验室

    10月25日上午,IEEE Fellow、加拿大工程院院士、滑铁卢大学(University of Waterloo)教授Sherman Shen 和惠灵顿维多利亚大学(Victoria University of Wellington)教授Winston Seah,在SHIFT联合主任杨旸教授的陪同下参观了上海雾计算实验室。

  • image



    以“新技术•新架构•新网络”为主题的“GNTC全球网络技术大会” 将于2017年11月28日-11月30日在北京长城饭店会议中心火热开幕。去年,共有超过2000名网络通信领域相关代表和观众参与GNTC网络技术大会,盛况空前。今年,作为主办方的天地互连下一代互联网国家工程中心将邀请更多全球顶尖技术专家,增设多场峰会与热点Workshop,在3天会议里分享最纯粹的技术趋势,展示最新最全的网络技术应用案例,与在座行业精英共话全球网络重构。



    想要了解更多的信息或注册大会,请访问 大会网站

  • image

    Call for Papers: Fog Services and Enabling Technologies


    Recently, Fog computing has received considerable attention in various application domains such as time-sensitive transactions in intelligent manufacture, smart transportation, and cellular networks. Fog computing derives benefits from the increasingly smarter and capable devices that reside not only at the network perimeter but also along the cloud-to-things continuum. This means that Fog-enabled services can be deployed anywhere in a network. Such continuous service provisioning and management have great potential to elevate the intelligence within computing networks to realize context-awareness, timely response, and network traffic offloading. As a new way of delivering services, Fog computing has the great potential to reshape the landscape of the ICT industry and provide tremendous novel business opportunities to customers. Read More

  • image

    AT&T副总裁David H. Lu和Chi-Ming Chen博士参观上海雾计算实验室

    10月16日,AT&T副总裁David H. Lu和Chi-Ming Chen博士,在SHIFT联合主任杨旸教授的陪同下参观了上海雾计算实验室。

  • image



    2017年9月30日,“雾计算与通信:技术与经济学术研讨会”在香港中文大学蒙民伟工程学楼举行。此次学术研讨会由香港中文大学杨伟豪教授、刘绍强教授和黄建伟教授组织,并邀请了内地、香港、新加坡各高校相关领域的教授、学者,共同分享最新的研究成果,探讨“雾计算”(Fog Computing)的未来与发展。阅读更多

  • image


    经国际开放雾计算产学研联盟(OpenFog Consortium)成员投票选举,2017年9月12日,在美国西雅图举行的该联盟全球成员大会上,上海雾计算实验室联合主任杨旸教授当选为该联盟大中华区委员会主席(OpenFog GCR Chair),实验室成员周明拓博士当选为该联盟测试床工作组主席(OpenFog Testbed Working Group Chair)。

    经国际开放雾计算产学研联盟(OpenFog Consortium)成员投票选举,2017年9月12日,在美国西雅图举行的该联盟全球成员大会上,上海雾计算实验室联合主任杨旸教授当选为该联盟大中华区委员会主席(OpenFog GCR Chair),实验室成员周明拓博士当选为该联盟测试床工作组主席(OpenFog Testbed Working Group Chair)。


    联盟测试床工作组是联盟技术认证委员会(Certification Committee)的工作机构之一,主要负责联盟成员的开放雾计算测试床框架的创建、运行和演进。测试床工作组与联盟其他成员组织紧密合作,将开放雾计算联盟的参考架构及实现应用于测试平台,并定义开放雾计算技术解决方案的测试标准以及评估测试方法。


  • image

    Prof. Xiliang Luo’s Research Group Won “Excellent Paper Award” from IEEE ICUFN 2017

    During the Ninth International Conference on Ubiquitous and Future Networks (ICUFN), which was held in Milan, Italy, from July 4th to July 7th, the paper “DL CSI Acquisition and Feedback in FDD Massive MIMO via Path Aligning” from Prof. Xiliang Luo’s research group was selected by the technical program committee (TPC) to receive the “Excellent Paper Award”.

    During the Ninth International Conference on Ubiquitous and Future Networks (ICUFN), which was held in Milan, Italy, from July 4th to July 7th, the paper “DL CSI Acquisition and Feedback in FDD Massive MIMO via Path Aligning” from Prof. Xiliang Luo’s research group was selected by the technical program committee (TPC) to receive the “Excellent Paper Award”. 

    ICUFN is co-organized by Korea Institute of Communications and Information Sciences (KICS), IEEE Communication Society, and the Institute of Electronics, Information, and Communication Engineers (IEICE). The topics in 2017 ICUFN include next-generation information and networking solutions, big data and cloud, autonomous systems, and ubiquitous IoT. 

    The TPC only selected 2 papers as “Excellent Paper Awards” from more than 200 accepted papers. The paper from Prof. Xiliang Luo’s research group proposed to align the downlink channel paths to facilitate the channel state information (CSI) acquisition and feedback in FDD massive MIMO systems. In a sense, this work paved the way for a scalable CSI feedback framework and can be utilized as a design philosophy for FDD massive MIMO in next-generation cellular networks.

  • image


    2017年7月2日,由国际雾计算产学研联盟(OpenFog Consortium)和上海科技大学联合举办的”国际雾计算产学研联盟大中华区论坛”在上海科技大学信息学院科技报告厅隆重举行。

    201772日,由国际雾计算产学研联盟(OpenFog Consortium)和上海科技大学联合举办的国际雾计算产学研联盟大中华区论坛在上海科技大学信息学院科技报告厅隆重举行。


    中国科学院上海微系统与信息技术研究所副所长谢晓明博士,上海科技大学副校长兼教务长印杰教授,美国普林斯顿大学Robert S. Fish教授,国际雾计算产学研联盟联合创始人张涛博士,上海科技大学信息学院副院长周宇教授,联盟大中华区主任杨旸教授,共同为上海科技大学雾计算节点揭幕。 

    国际雾计算产学研联盟联合创始人张涛博士,美国普林斯顿大学Robert S. Fish教授,挪威奥斯陆大学张彦教授,香港中文大学黄建伟教授,中山大学陈旭教授,美国内华达大学杨磊教授,联盟大中华区主任杨旸教授各自就雾计算的发起、标准化工作、在5GIoT中的应用、雾计算经济学等方向做了精彩的发言。研讨会上,参会人员积极交流互动,各位专家针对雾计算当前研究的进展、雾计算技术挑战及雾计算未来应用前景等方面和大家进行了广泛和深入的探讨。各位专家的报告生动有趣、深入浅出,让大家对雾计算这个当今国际研究热点的认识越来越清晰,也对今后雾计算的研究方向和所面临的机遇和挑战有了新的认识和思考,对推动大中华区雾计算的研究和发展具有重要意义。


    国际雾计算产学研联盟 – OpenFog Consortiumhttp://www.openfogconsortium.org

    国际雾计算产学研联盟大中华区 – OpenFog GCR: http://www.openfogconsortium.cn


  • image

    OpenFog GCR Workshop

    One workshop focusing on recent advances in fog computing is going to be held on July 2nd in SIST Auditorium at ShanghaiTech University. As one prototype of fog node from SHIFT, “ShanghaiTech Node” will also be unveiled.


    OpenFog Greater China Region Workshop Agenda


    Time        9:00-12:00, Sunday 2 July 2017

    Venue      Auditorium, SIST Building, ShanghaiTech University

    Address    393 Middle Huaxia Road, Pudong, Shanghai, 201210


    Sunday 2 July 2017


    Welcome Speech

    Jie Yin, Xiaoming Xie


    The Road Ahead for Fog Computing

    Tao Zhang


    Fog Standardization in the IEEE

    Robert S. Fish


    Announcement of ShanghaiTech Node

    Jie Yin, Xiaoming Xie, Tao Zhang, Robert S. Fish, Yu Zhou, Yang Yang, Xiliang Luo


    Photo and Tea Break


    Mobile Edge Computing for Internet of Things

    Yan Zhang


    Economics of Wi-Fi Networks

    Jianwei Huang


    Data Analytics for Wind Energy Integration: Spatio-Temporal Wind Power Analysis and Stochastic Optimization

    Lei Yang


    Socially-Aware Mobile Edge Computing

    Xu Chen




    For more information, click here please.


  • image



    主办单位:国际雾计算产学研联盟(OpenFog Consortium GCR)




    For more information, click here please.

  • image




    会上,陈旭老师做了名为“Hybrid Mobile Task Offloadings in Fog Computing”的技术报告,与会的各位老师也纷纷发言积极讨论,提出了许多宝贵意见与建议,希望今后会有进一步合作机会。


  • image

    Call for paper (Deadline June 15, 2017)


    The first Fog World Congress will be held in Santa Clara, California, USA, from 30 Oct to 1 Nov 2017. You are very encouraged to submit your latest research results to this important conference and meet with colleagues with similar R&D interests in fog computing. Please note the deadline for paper submission is now 15 June. Thanks a lot.. Read More

  • image

    Is China Outsmarting America in A.I.?

    HONG KONG — Sören Schwertfeger finished his postdoctorate research on autonomous robots in Germany, and seemed set to go to Europe or the United States, where artificial intelligence was pioneered and established.

    HONG KONG — Sören Schwertfeger finished his postdoctorate research on autonomous robots in Germany, and seemed set to go to Europe or the United States, where artificial intelligence was pioneered and established.Instead, he went to China.“You couldn’t have started a lab like mine elsewhere,” Mr. Schwertfeger said.The balance of power in technology is shifting. China, which for years watched enviously as the West invented the software and the chips powering today’s digital age, has become a major player in artificial intelligence, what some think may be the most important technology of the future. Experts widely believe China is only a step behind the United States. Read More

  • image



    “有别于云计算,雾计算采取分散的架构、比较接近终端用户,可利用靠近服务需求的计算资源进行数据处理,从而改善由于庞大的数据量传送至云计算中心带来的带宽不足或时延过长的情况。” 在近日举行的“2017中国(上海)国际物联网大会”上,国际雾计算产学研联盟大中华区委员会主任、上海雾计算实验室主任杨旸教授提出这样的观点。Read More

  • image

    Delegation of OpenFog Consortium Visited Four Leading Companies in China

    April 27, 2017 – A delegation of OpenFog Consortium visited  China Unicom, China Academy of Information and Communications Technology  (CAICT),iSoftStone, and National Institute of Clean and Low Carbon Energy of Shenhua Group (NICE).

    BEIJING, April 27, 2017 – A delegation of OpenFog Consortium, including Helder Antunes (Chairman), Tao Zhang (Co-Founder), Yang Yang (Director of Greater China Region), and Ming-Tuo Zhou (SIMIT, Chinese Academy of Sciences), visited  China Unicom, China Academy of Information and Communications Technology  (CAICT), iSoftStone, and National Institute of Clean and Low Carbon Energy of Shenhua Group (NICE) today. China Unicom and Shenhua Group are among the Fortune Global 500 companies. China Unicom is one of the world leading telecom operators in terms of its customer base and market capitalization. With the merging of Information Technology (IT) and Operation Technology (OT), the telecom infrastructures of China Unicom could be enabled by fog computing technologies to meet a variety of user requirements in vertical industries. Shenhua Group is demanding fog-based technical solutions for high energy efficiency and safety guarantees in its coal mining business.  CAICT is a leading telecom standardization organization in China and is very interested in further collaborations with OpenFog Consortium. iSoftStone is a leading Chinese company providing IoT-based solutions for smart city applications and believes fog computing could be the key enabler of various intelligent software and smart applications for the effective management of giant cities.
  • image



    本次大会是在中国科学院、工业与信息化部和中国科学技术协会的大力支持下,由中国科学院上海微系统与信息技术研究所、中国电子学会联合主办,中国电子学会物联网专家委员会、上海嘉定工业开发区管委会和上海物联网有限公司承办。大会吸引了超过1500名行业精英和业界领袖。Read More

  • image

    Successful Workshop Held by OpenFog Consortium Greater China Region

    On April 24th, The Fog Computing workshop, organized by OpenFog and ShanghaiTech University (ShanghaiTech), was held in the auditorium of the School of Information Science and Technology (SIST), ShanghaiTech University.

    On April 24th, The Fog Computing workshop, organized by OpenFog and ShanghaiTech University (ShanghaiTech), was held in the auditorium of the School of Information Science and Technology (SIST), ShanghaiTech University. Together with the workshop, the OpenFog Consortium Greater China Regional Committee and the Shanghai Institute of Fog Computing Technology (SHIFT) were officially launched.  Officials and researchers from ShanghaiTech, Shanghai Institute of Microsystem and Information Technology (SIMIT), China Institute of Communications, Intel, CISCO, etc. attended this event.

    Dr.Yang Yang, Director of the OpenFog Consortium Greater China Regional Committee, and Dr. Xiliang Luo, associate professor. of ShanghaiTech, served as the chairs of the meeting. Mr. Helder Antunes, the OpenFog Chairman, announced the establishment of the OpenFog Consortium Greater China Regional Committee. Prof. Jie Yin, the vice President & provost of ShanghaiTech, and Academician Xi Wang, Director of Shanghai Institute of Microsystem and Information Technology, inaugurated the Shanghai Institute of Fog Computing Technology.

    Fog Computing is an extension of Cloud Computing. Fog computing extends the cloud computing model, and it can be widely used in a variety of services. Especially the application of Internet of things. With the rapid development of Internet of things, Fog Computing technology will have broad prospects for development

    Leading researchers from Singapore, Taiwan, Hongkong, and other countries/regions gave enlightening talks on fog computing. During the panel session, eight panelists offered their views on the significance, methods, and application fields of fog computing technology.

    The OpenFog Consortium (OpenFog) is a public-private ecosystem formed to accelerate the adoption of fog computing. It was founded by ARM, Cisco, Dell, Intel, Microsoft and Princeton University in November 2015 and currently has over 50 member organizations throughout the world.

    On January 16, following the election results of the Board of Directors of the OpenFog Consortium, ShanghaiTech was elected as Director unit of Greater China Region, ShanghaiTech Distinguished Professor-in-Residence Yang Yang was appointed Director of the OpenFog Consortium Greater China Region (GCR) Committee. During the term, ShanghaiTech will lead and promote the research, development, testing, and standardizing efforts in the GCR, including Taiwan, Hong Kong, Singapore, and mainland China. The OpenFog GCR Committee will accelerate the adoption of fog computing to solve the bandwidth, latency and communications challenges associated with the Internet of Things, Artificial Intelligence, Robotics, the Tactile Internet and other advanced concepts in the digitized world.

    The Shanghai Institute of Fog Computing Technology (SHIFT) was jointly established by ShanghaiTech University and Shanghai Institute of Microsystem and Information Technology. The institute will serve the construction of Zhangjiang Comprehensive National Science Center, and actively participate in major strategic projects and major infrastructure projects including advanced sensors and networking, Smart grid, Smart cars and new energy vehicles, Big data and cloud computing. Finally built a major strategic project scientific research and experimental base with world leading level.

    For more...

  • image

    ShanghaiTech Leads OpenFog Consortium Greater China

    On January 16, following the election results of the Board of Directors of the OpenFog Consortium, ShanghaiTech Distinguished Professor-in-Residence Yang Yang was appointed Director of the OpenFog Consortium Greater China Region (GCR) Committee.

    On January 16, following the election results of the Board of Directors of the OpenFog Consortium, ShanghaiTech Distinguished Professor-in-Residence Yang Yang was appointed Director of the OpenFog Consortium Greater China Region (GCR) Committee. During his term, Professor Yang, representing ShanghaiTech will lead and promote the research, development, testing, and standardizing efforts in the GCR, including Taiwan, Hong Kong, Singapore, and mainland China. The OpenFog GCR Committee will accelerate the adoption of fog computing to solve the bandwidth, latency and communications challenges associated with the Internet of Things (IoT), Artificial Intelligence, Robotics, the Tactile Internet and other advanced concepts in the digitized world.

    The OpenFog Consortium (OpenFog) is a public-private ecosystem formed to accelerate the adoption of fog computing. It was founded by ARM, Cisco, Dell, Intel, Microsoft and Princeton University in November 2015 and currently has over 50 member organizations throughout the world.

    Website of the OpenFog Consortium:https://www.openfogconsortium.org/