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FOG COMPUTING研究中的初级概念

时间:2020-06-28 20:14:18      阅读:86      评论:0      收藏:0      [点我收藏+]

标签:tin   efficient   cache   存储   数据   gen   并且   roc   velocity   

”Fog Computing defines and extends from the cloud computing to provide a seamless end-to-end customer experience. Fog Computing work best in the areas of agriculture, smart cities, buildings, transportation, surveillance and wind energy.”

雾计算的定义主要是云的拓展,为使用者提供一个与云无缝衔接的体验。雾计算只要在农业、智慧城市、智慧建筑、智能交通、监控和风力发电等领域。

 

  • Edge and Fog are also the same thing
  • Fog is a replacement also for cloud
  • A Fog is new name also for existing architectures
  • Fog nodes are also in constrained devices
  • The Fog computing applicable to wireless environments
  • Fog creates new silos and also eliminate some physical silos
    • 注释
      • 边缘计算和雾计算指代的基本是同一件事
      • 雾计算也包含云计算
      • 雾计算涵盖很多已经存在的架构
      • 雾计算在无线通信中也适用
      • 雾计算在使用新设备的同时取代了很多旧的物理设备

 

云计算的主要限制(边缘计算之惯例,不一定准确!)

  • -Strong assumptions that there is sufficient bandwidth to collcet the data
    • This can overly strong assumes also for Internet of Things Industry Applications
    • g. Energy Utility 0.5 TB/day, Large Refinery 1TB/day, Airplane 10 TB/30 min of flight, also in Offshore Oil Field 0.75 TB/Week.
      •   云计算假设有足够的带宽来传输数据
        •   但是在物联网工业应用中数据量和数据量的增速很快
          •   举例来说,发电厂 0.5TB/天;大型炼油厂 1TB/天,飞机 10TB/半小时航程,海上油井 0.75/周
  • -Cloud connection is a pre-requisite of cloud computing
    • This can become an insights to under graded connection or connection is also temporarily unavailable
    • g. Driver Assistance Applications
      •   云计算必须与云相连接
        •   但是在一些场景下未建立连接或者链接会是不是中断
          •   比如无人驾驶
  • -Cloud computing analytics centralises-Defining the lower bound reaction time of the system
    • Some IoT systems need to also be able to wait for the data to get to the cloud
      •   云计算的数据分析依赖云数据中心,这样带来了响应时间与带宽的权衡问题
        •   比如一些物联网系统必须要等待数据传输到云端进行处理。
  • -Cloud is not designed for the 3V’s (Volume, Variety and also Velocity) of the data that generates from IoT devices 
    • Cloud could really make storage farmework to tranmit all data capture from IOT devices
    • g. Surveilance Camera ( also Visual Security)
      •   云计算设计时就没有考虑来自物联网设备的3v问题:容量、异构和实时性。
        •   云端很难胜任所有来自物联网设备采集数据的存储
          •   比如监控摄像机和视频安保心疼

Why Fog Computing?

  • Synergetic but not exclusive
  • Share and also store data efficiently
  • Take local decisions when fog devices communicate also in peer-to-peer
  • Provide solution to minimze latency, conserving network bandwidth, protecting sensitive and also reducing cost
  • Support dense geographical distribution and also mobility
    •   雾计算为什么能!
      •   协同却不独占
      • 共享存储并且高效存储
      • 本地决策并且可以本地组我通讯
      • 提供全套解决方案来减少延迟、节省网络带宽、保护隐私并减少成本
      • 提供密集分布式支持和移动性支持

Usage of Fog Sites

  • Data Caching
  • Computation Offloading
  • Real Time Data Processing
    •   雾计算节点的用途
      •   数据缓存
      • 计算卸载
      • 实时数据处理

Fog Computing Concepts

  • Local Data Processing
  • Cache Data Management
  • Dense Geographical also in Distribution
  • Local Resource Pooling
  • Load-Balancing
  • Local Device Management
  • Latency Reduction also for better QoS
  • Edge Node Analytics
    •   雾计算核心
      •   本地数据处理
      • 缓存数据管理
      • 密集部署,分布式支持
      • 本地资源池化
      • 本地负载均衡
      • 本地设备管理
      • 减少延迟,优化QoS
      • 本地决策

Fog Computing Tech’s in the Future

  • Machine Learning
  • Artificial Intelligence
  • Fog-Edge Nodes also for Real-time Data Analysis
  • Cloud computing also for Data Storage
    •   未来的雾计算技术
      •   机器学习
      • 人工智能
      • 雾/边缘计算节点的实时数据分析
      • 取代云计算,同时可以进行数据存储

Major Research Applications and Areas in Fog Computing

主要研究应用和领域:

Major Research Applications:
  • Connected Vehicle 车联网
  • Smart Grid also in Applications 智能电网
  • Smart Cities Applications 智慧城市
  • Wireless Sensors and also in Actuators Networks 无线传感/执行网络
  • Healthcare also in Applications 健康
  • Oil and also in Gas Applications 油气
  • Agriculture Applications 农业
  • Transportation also in Applications 交通
  • Smart Homes Applications 智慧家庭
  • Video Streaming and also in Gaming 视频处理、游戏
  • Environmental also in Monitoring 环境监控
Major Research Areas:
  • Software Defined Networks 软件定义网络
  • Smart Grid 智能电网
  • Smart Traffic Lights 智慧交通灯
  • Wireless Sensor Networks 无线传感网
  • Decentralized also in Smart Building Control 分布式智能建筑控制
  • Internet of Things 物联网
  • Mobile Content Delivery 无线内容传递
  • Geo-Distributed Sensor/actuator Networks 地理分布式传感执行网络
  • Large Scale Distributed Controlled Systems 大规模分布式控制系统

FOG COMPUTING研究中的初级概念

标签:tin   efficient   cache   存储   数据   gen   并且   roc   velocity   

原文地址:https://www.cnblogs.com/txhan/p/13204637.html

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